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• I need to use profiler in my IDE.

  - by ashwani66476

  Hello I am using RSA7 as IDE, I need to use profiler in my IDE for memory analysis. Can any one suggest me From where I can free download it? How can I use it with RSA7? Many Thanks

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• .NET coupled with MATLAB or R?

  - by Peter

  I'm writing a program in .NET that will need to utilize the statistical and data analysis functions of R or MATLAB. I have used R but am now contemplating moving to MATLAB since it has a .Net compiler while R can only interface via COM objects. Can anyone recommend going either way? I know MATLAB is infinitely more expensive than R (since R is free) but I'm thinking that may translate to an easier development cycle?

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• Access Voilation in std::pair

  - by sameer karjatkar

  I have an application which is trying to populate a pair . Out of no where the application crashes . The Windbg analysis on the crash dump suggest PRIMARY_PROBLEM_CLASS: INVALID_POINTER_READ DEFAULT_BUCKET_ID: INVALID_POINTER_READ STACK_TEXT: 0389f1dc EPFilter32!std::vector,std::allocator ::size+0xc INVALID_POINTER_READ_c0000005_Test.DLL!std::vector_std::pair_unsigned_int, unsigned_int_,std::allocator_std::pair_unsigned_int,unsigned_int___::size Following is the statement in the code where it fails const branch_info& b1 = en1.m_branches[i1]; where branch_info is std::pair and the en1.m_branches[i1] fetches me a pair value

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• To stack tiff bands 3-4-5 obtained in GLCL?

  - by Dalia A. Conde

  Hi all, I need to do a layer stack of different bands to do some analysis. However, I do not have ERSAS any more. And I do not have the Image extension in arc map. Is there any way to do this with free software? Thank you

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• Is there a shorthand term for O(n log n)?

  - by jemfinch

  We usually have a single-word shorthand for most complexities we encounter in algorithmic analysis: O(1) == "constant" O(log n) == "logarithmic" O(n) == "linear" O(n^2) == "quadratic" O(n^3) == "cubic" O(2^n) == "exponential" We encounter algorithms with O(n log n) complexity with some regularity (think of all the algorithms dominated by sort complexity) but as far as I know, there's no single word we can use in English to refer to that complexity. Is this a gap in my knowledge, or a real gap in our English discourse on computational complexity?

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• need to crawl images and the whole web pages

  - by Kei Situ

  hey, I am starting a project and wonder the relationship between the characters in images and the whole web page where the images reside. so first, i want to crawl some images and their web pages.....need to save the crawl result in local disk for further analysis. I wonder if there is any open source for this issue? thx^_^

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• Java or C for image processing

  - by its-me

  I am looking in to learning a programming language (take a course) for image analysis and processing. Possibly Bioinformatics too. Which language should I go for? C or Java? Other languages are not an option for me. Also please explain why either of the languages is a better option for my application.

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• Why should you choose Oracle WebLogic 12c instead of JBoss EAP 6?

  - by Ricardo Ferreira

  In this post, I will cover some technical differences between Oracle WebLogic 12c and JBoss EAP 6, which was released a couple days ago from Red Hat. This article claims to help you in the evaluation of key points that you should consider when choosing for an Java EE application server. In the following sections, I will present to you some important aspects that most customers ask us when they are seriously evaluating for an middleware infrastructure, specially if you are considering JBoss for some reason. I would suggest that you keep the following question in mind while you are reading the points: "Why should I choose JBoss instead of WebLogic?" 1) Multi Datacenter Deployment and Clustering - D/R ("Disaster & Recovery") architecture support is embedded on the WebLogic Server 12c product. JBoss EAP 6 on the other hand has no direct D/R support included, Red Hat relies on third-part tools with higher prices. When you consider a middleware solution to host your business critical application, you should worry with every architectural aspect that are related with the solution. Fail-over support is one little aspect of a truly reliable solution. If you do not worry about D/R, your solution will not be reliable. Having said that, with Red Hat and JBoss EAP 6, you have this extra cost that will increase considerably the total cost of ownership of the solution. As we commonly hear from analysts, open-source are not so cheaper when you start seeing the big picture. - WebLogic Server 12c supports advanced LAN clustering, detection of death servers and have a common alert framework. JBoss EAP 6 on the other hand has limited LAN clustering support with no server death detection. They do not generate any alerts when servers goes down (only if you buy JBoss ON which is a separated technology, but until now does not support JBoss EAP 6) and manual intervention are required when servers goes down. In most cases, admin people must rely on "kill -9", "tail -f someFile.log" and "ps ax | grep java" commands to manage failures and clustering anomalies. - WebLogic Server 12c supports the concept of Node Manager, which is a separated process that runs on the physical | virtual servers that allows extend the administration of the cluster to WebLogic managed servers that are often distributed across multiple machines and geographic locations. JBoss EAP 6 on the other hand has no equivalent technology. Whole server instances must be managed individually. - WebLogic Server 12c Node Manager supports Coherence to boost performance when managing servers. JBoss EAP 6 on the other hand has no similar technology. There is no way to coordinate JBoss and infiniband instances provided by JBoss using high throughput and low latency protocols like InfiniBand. The Node Manager feature also allows another very important feature that JBoss EAP lacks: secure the administration. When using WebLogic Node Manager, all the administration tasks are sent to the managed servers in a secure tunel protected by a certificate, which means that the transport layer that separates the WebLogic administration console from the managed servers are secured by SSL. - WebLogic Server 12c are now integrated with OTD ("Oracle Traffic Director") which is a web server technology derived from the former Sun iPlanet Web Server. This software complements the web server support offered by OHS ("Oracle HTTP Server"). Using OTD, WebLogic instances are load-balanced by a high powerful software that knows how to handle SDP ("Socket Direct Protocol") over InfiniBand, which boost performance when used with engineered systems technologies like Oracle Exalogic Elastic Cloud. JBoss EAP 6 on the other hand only offers support to Apache Web Server with custom modules created to deal with JBoss clusters, but only across standard TCP/IP networks.  2) Application and Runtime Diagnostics - WebLogic Server 12c have diagnostics capabilities embedded on the server called WLDF ("WebLogic Diagnostic Framework") so there is no need to rely on third-part tools. JBoss EAP 6 on the other hand has no diagnostics capabilities. Their only diagnostics tool is the log generated by the application server. Admin people are encouraged to analyse thousands of log lines to find out what is going on. - WebLogic Server 12c complement WLDF with JRockit MC ("Mission Control"), which provides to administrators and developers a complete insight about the JVM performance, behavior and possible bottlenecks. WebLogic Server 12c also have an classloader analysis tool embedded, and even a log analyzer tool that enables administrators and developers to view logs of multiple servers at the same time. JBoss EAP 6 on the other hand relies on third-part tools to do something similar. Again, only log searching are offered to find out whats going on. - WebLogic Server 12c offers end-to-end traceability and monitoring available through Oracle EM ("Enterprise Manager"), including monitoring of business transactions that flows through web servers, ESBs, application servers and database servers, all of this with high deep JVM analysis and diagnostics. JBoss EAP 6 on the other hand, even using JBoss ON ("Operations Network"), which is a separated technology, does not support those features. Red Hat relies on third-part tools to provide direct Oracle database traceability across JVMs. One of those tools are Oracle EM for non-Oracle middleware that manage JBoss, Tomcat, Websphere and IIS transparently. - WebLogic Server 12c with their JRockit support offers a tool called JRockit Flight Recorder, which can give developers a complete visibility of a certain period of application production monitoring with zero extra overhead. This automatic recording allows you to deep analyse threads latency, memory leaks, thread contention, resource utilization, stack overflow damages and GC ("Garbage Collection") cycles, to observe in real time stop-the-world phenomenons, generational, reference count and parallel collects and mutator threads analysis. JBoss EAP 6 don't even dream to support something similar, even because they don't have their own JVM. 3) Application Server Administration - WebLogic Server 12c offers a complete administration console complemented with scripting and macro-like recording capabilities. A single WebLogic console can managed up to hundreds of WebLogic servers belonging to the same domain. JBoss EAP 6 on the other hand has a limited console and provides a XML centric administration. JBoss, after ten years, started the development of a rudimentary centralized administration that still leave a lot of administration tasks aside, so admin people and developers must touch scripts and XML configuration files for most advanced and even simple administration tasks. This lead applications to error prone and risky deployments. Even using JBoss ON, JBoss EAP are not able to offer decent administration features for admin people which must be high skilled in JBoss internal architecture and its managing capabilities. - Oracle EM is available to manage multiple domains, databases, application servers, operating systems and virtualization, with a complete end-to-end visibility. JBoss ON does not provide management capabilities across the complete architecture, only basic monitoring. Even deployment must be done aside JBoss ON which does no integrate well with others softwares than JBoss. Until now, JBoss ON does not supports JBoss EAP 6, so even their minimal support for JBoss are not available for JBoss EAP 6 leaving customers uncovered and subject to high skilled JBoss admin people. - WebLogic Server 12c has the same administration model whatever is the topology selected by the customer. JBoss EAP 6 on the other hand differentiates between two operational models: standalone-mode and domain-mode, that are not consistent with each other. Depending on the mode used, the administration skill is different. - WebLogic Server 12c has no point-of-failures processes, and it does not need to define any specialized server. Domain model in WebLogic is available for years (at least ten years or more) and is production proven. JBoss EAP 6 on the other hand needs special processes to garantee JBoss integrity, the PC ("Process-Controller") and the HC ("Host-Controller"). Different from WebLogic, the domain model in JBoss is quite new (one year at tops) of maturity, and need to mature considerably until start doing things like WebLogic domain model does. - WebLogic Server 12c supports parallel deployment model which enables some artifacts being deployed at the same time. JBoss EAP 6 on the other hand does not have any similar feature. Every deployment are done atomically in the containers. This means that if you have a huge EAR (an EAR of 120 MB of size for instance) and deploy onto JBoss EAP 6, this EAR will take some minutes in order to starting accept thread requests. The same EAR deployed onto WebLogic Server 12c will reduce the deployment time at least in 2X compared to JBoss. 4) Support and Upgrades - WebLogic Server 12c has patch management available. JBoss EAP 6 on the other hand has no patch management available, each JBoss EAP instance should be patched manually. To achieve such feature, you need to buy a separated technology called JBoss ON ("Operations Network") that manage this type of stuff. But until now, JBoss ON does not support JBoss EAP 6 so, in practice, JBoss EAP 6 does not have this feature. - WebLogic Server 12c supports previuous WebLogic domains without any reconfiguration since its kernel is robust and mature since its creation in 1995. JBoss EAP 6 on the other hand has a proven lack of supportability between JBoss AS 4, 5, 6 and 7. Different kernels and messaging engines were implemented in JBoss stack in the last five years reveling their incapacity to create a well architected and proven middleware technology. - WebLogic Server 12c has patch prescription based on customer configuration. JBoss EAP 6 on the other hand has no such capability. People need to create ticket supports and have their installations revised by Red Hat support guys to gain some patch prescription from them. - Oracle WebLogic Server independent of the version has 8 years of support of new patches and has lifetime release of existing patches beyond that. JBoss EAP 6 on the other hand provides patches for a specific application server version up to 5 years after the release date. JBoss EAP 4 and previous versions had only 4 years. A good question that Red Hat will argue to answer is: "what happens when you find issues after year 5"?  5) RAC ("Real Application Clusters") Support - WebLogic Server 12c ships with a specific JDBC driver to leverage Oracle RAC clustering capabilities (Fast-Application-Notification, Transaction Affinity, Fast-Connection-Failover, etc). Oracle JDBC thin driver are also available. JBoss EAP 6 on the other hand ships only the standard Oracle JDBC thin driver. Load balancing with Oracle RAC are not supported. Manual intervention in case of planned or unplanned RAC downtime are necessary. In JBoss EAP 6, situation does not reestablish automatically after downtime. - WebLogic Server 12c has a feature called Active GridLink for Oracle RAC which provides up to 3X performance on OLTP applications. This seamless integration between WebLogic and Oracle database enable more value added to critical business applications leveraging their investments in Oracle database technology and Oracle middleware. JBoss EAP 6 on the other hand has no performance gains at all, even when admin people implement some kind of connection-pooling tuning. - WebLogic Server 12c also supports transaction and web session affinity to the Oracle RAC, which provides aditional gains of performance. This is particularly interesting if you are creating a reliable solution that are distributed not only in an LAN cluster, but into a different data center. JBoss EAP 6 on the other hand has no such support. 6) Standards and Technology Support - WebLogic Server 12c is fully Java EE 6 compatible and production ready since december of 2011. JBoss EAP 6 on the other hand became fully compatible with Java EE 6 only in the community version after three months, and production ready only in a few days considering that this article was written in June of 2012. Red Hat says that they are the masters of innovation and technology proliferation, but compared with Oracle and even other proprietary vendors like IBM, they historically speaking are lazy to deliver the most newest technologies and standards adherence. - Oracle is the steward of Java, driving innovation into the platform from commercial and open-source vendors. Red Hat on the other hand does not have its own JVM and relies on third-part JVMs to complete their application server offer. 95% of Red Hat customers are using Oracle HotSpot as JVM, which means that without Oracle involvement, their support are limited exclusively to the application server layer and we all know that most problems are happens in the JVM layer. - WebLogic Server 12c supports natively JDK 7, which empower developers to explore the maximum of the Java platform productivity when writing code. This feature differentiate WebLogic from others application servers (except GlassFish that are also managed by Oracle) because the usage of JDK 7 introduce such remarkable productivity features like the "try-with-resources" enhancement, catching multiple exceptions with one try block, Strings in the switch statements, JVM improvements in terms of JDBC, I/O, networking, security, concurrency and of course, the most important feature of Java 7: native support for multiple non-Java languages. More features regarding JDK 7 can be found here. JBoss EAP 6 on the other hand does not support JDK 7 officially, they comment in their community version that "Java SE 7 can be used with JBoss 7" which does not gives you any guarantees of enterprise support for JDK 7. - Oracle WebLogic Server 12c supports integration with Spring framework allowing Spring applications to use WebLogic special transaction manager, exposing bean interfaces to WebLogic MBeans to take advantage of all WebLogic monitoring and administration advantages. JBoss EAP 6 on the other hand has no special integration with Spring. In fact, Red Hat offers a suspicious package called "JBoss Web Platform" that in theory supports Spring, but in practice this package does not offers any special integration. It is just a facility for Red Hat customers to have support from both JBoss and Spring technology using the same customer support. 7) Lightweight Development - Oracle WebLogic Server 12c and Oracle GlassFish are completely integrated and can share applications without any modifications. Starting with the 12c version, WebLogic now understands natively GlassFish deployment descriptors and specific configurations in order to offer you a truly and reliable migration path from a community Java EE application server to a enterprise middleware product like WebLogic. JBoss EAP 6 on the other hand has no support to natively reuse an existing (or still in development) application from JBoss AS community server. Users of JBoss suffer of critical issues during deployment time that includes: changing the libraries and dependencies of the application, patching the DTD or XSD deployment descriptors, refactoring of the application layers due classloading issues and anomalies, rebuilding of persistence, business and web layers due issues with "usage of the certified version of an certain dependency" or "frameworks that Red Hat potentially does not recommend" etc. If you have the culture or enterprise IT directive of developing Java EE applications using community middleware to in a certain future, transition to enterprise (supported by a vendor) middleware, Oracle WebLogic plus Oracle GlassFish offers you a more sustainable solution. - WebLogic Server 12c has a very light ZIP distribution (less than 165 MB). JBoss EAP 6 ZIP size is around 130 MB, together with JBoss ON you have more 100 MB resulting in a higher download footprint. This is particularly interesting if you plan to use automated setup of application server instances (for example, to rapidly setup a development or staging environment) using Maven or Hudson. - WebLogic Server 12c has a complete integration with Maven allowing developers to setup WebLogic domains with few commands. Tasks like downloading WebLogic, installation, domain creation, data sources deployment are completely integrated. JBoss EAP 6 on the other hand has a limited offer integration with those tools.  - WebLogic Server 12c has a startup mode called WLX that turns-off EJB, JMS and JCA containers leaving enabled only the web container with Java EE 6 web profile. JBoss EAP 6 on the other hand has no such feature, you need to disable manually the containers that you do not want to use. - WebLogic Server 12c supports fastswap, which enables you to change classes without redeployment. This is particularly interesting if you are developing patches for the application that is already deployed and you do not want to redeploy the entire application. This is the same behavior that most application servers offers to JSP pages, but with WebLogic Server 12c, you have the same feature for Java classes in general. JBoss EAP 6 on the other hand has no such support. Even JBoss EAP 5 does not support this until now. 8) JMS and Messaging - WebLogic Server 12c has a proven and high scalable JMS implementation since its initial release in 1995. JBoss EAP 6 on the other hand has a still immature technology called HornetQ, which was introduced in JBoss EAP 5 replacing everything that was implemented in the previous versions. Red Hat loves to introduce new technologies across JBoss versions, playing around with customers and their investments. And when they are asked about why they have changed the implementation and caused such a mess, their answer is always: "the previous implementation was inadequate and not aligned with the community strategy so we are creating a new a improved one". This Red Hat practice leads to uncomfortable investments that in a near future (sometimes less than a year) will be affected in someway. - WebLogic Server 12c has troubleshooting and monitoring features included on the WebLogic console and WLDF. JBoss EAP 6 on the other hand has no direct monitoring on the console, activity is reflected only on the logs, no debug logs available in case of JMS issues. - WebLogic Server 12c has extremely good performance and scalability. JBoss EAP 6 on the other hand has a JMS storage mechanism relying on Oracle database or MySQL. This means that if an issue in production happens and Red Hat affirms that an performance issue is happening due to database problems, they will not support you on the performance issue. They will orient you to call Oracle instead. - WebLogic Server 12c supports messaging enterprise features like SAF ("Store and Forward"), Distributed Queues/Topics and Foreign JMS providers support that leverage JMS implementations without compromise developer code making things completely transparent. JBoss EAP 6 on the other hand do not even dream to support such features. 9) Caching and Grid - Coherence, which is the leading and most mature data grid technology from Oracle, is available since early 2000 and was integrated with WebLogic in 2009. Coherence and WebLogic clusters can be both managed from WebLogic administrative console. Even Node Manager supports Coherence. JBoss on the other hand discontinued JBoss Cache, which was their caching implementation just like they did with the messaging implementation (JBossMQ) which was a issue for long term customers. JBoss EAP 6 ships InfiniSpan version 1.0 which is immature and lack a proven record of successful cases and reliability. - WebLogic Server 12c has a feature called ActiveCache which uses Coherence to, without any code changes, replicate HTTP sessions from both WebLogic and other application servers like JBoss, Tomcat, Websphere, GlassFish and even Microsoft IIS. JBoss EAP 6 on the other hand does have such support and even when they do in the future, they probably will support only their own application server. - Coherence can be used to manage both L1 and L2 cache levels, providing support to Oracle TopLink and others JPA compliant implementations, even Hibernate. JBoss EAP 6 and Infinispan on the other hand supports only Hibernate. And most important of all: Infinispan does not have any successful case of L1 or L2 caching level support using Hibernate, which lead us to reflect about its viability. 10) Performance - WebLogic Server 12c is certified with Oracle Exalogic Elastic Cloud and can run unchanged applications at this engineered system. This approach can benefit customers from Exalogic optimization's of both kernel and JVM layers to boost performance in terms of 10X for web, OLTP, JMS and grid applications. JBoss EAP 6 on the other hand has no investment on engineered systems: customers do not have the choice to deploy on a Java ultra fast system if their project becomes relevant and performance issues are detected. - WebLogic Server 12c maintains a performance gain across each new release: starting on WebLogic 5.1, the overall performance gain has been close to 4X, which close to a 20% gain release by release. JBoss on the other hand does not provide SPECJAppServer or SPECJEnterprise performance benchmarks. Their so called "performance gains" remains hidden in their customer environments, which lead us to think if it is true or not since we will never get access to those environments. - WebLogic Server 12c has industry performance benchmarks with submissions across platforms and configurations leading SPECJ. Oracle WebLogic leads SPECJAppServer performance in multiple categories, fitting all customer topologies like: dual-node, single-node, multi-node and multi-node with RAC. JBoss... again, does not provide any SPECJAppServer performance benchmarks. - WebLogic Server 12c has a feature called work manager which allows your application to embrace new performance levels based on critical resource utilization of the CPUs usage. Work managers prioritizes work and allocates threads based on an execution model that takes into account administrator-defined parameters and actual run-time performance and throughput. JBoss EAP 6 on the other hand has no compared feature and probably they never will. Not supporting such feature like work managers, JBoss EAP 6 forces admin people and specially developers to uncover performance gains in a intrusive way, rewriting the code and doing performance refactorings. 11) Professional Services Support - WebLogic Server 12c and any other technology sold by Oracle give customers the possibility of hire OCS ("Oracle Consulting Services") to manage critical scenarios, deployment assistance of new applications, high skilled consultancy of architecture, best practices and people allocation together with customer teams. All OCS services are available without any restrictions, having the customer bought software from Oracle or just starting their implementation before any acquisition. JBoss EAP 6 or Red Hat to be more specifically, only offers professional services if you buy subscriptions from them. If you are developing a new critical application for your business and need the help of Red Hat for a serious issue or architecture decision, they will probably say: "OK... I can help you but after you buy subscriptions from me". Red Hat also does not allows their professional services consultants to manage environments that uses community based software. They will probably force you to first buy a subscription, download their "enterprise" version and them, optionally hire their consultants. - Oracle provides you our university to educate your team into our technologies, including of course specialized trainings of WebLogic application server. At any time and location, you can hire Oracle to train your team so you get trustful knowledge according to your specific needs. Certifications for the products are also available if your technical people desire to differentiate themselves as professionals. Red Hat on the other hand have a limited pool of resources to train your team in their technologies. Basically they are selling training and certification for RHEL ("Red Hat Enterprise Linux") but if you demand more specialized training in JBoss middleware, they will probably connect you to some "certified" partner localized training since they are apparently discontinuing their education center, at least here in Brazil. They were not able to reproduce their success with RHEL education to their middleware division since they need first sell the subscriptions to after gives you specialized training. And again, they only offer you specialized training based on their enterprise version (EAP in the case of JBoss) which means that the courses will be a quite outdated. There are reports of developers that took official training's from Red Hat at this year (2012) and in a certain JBoss advanced course, Red Hat supposedly covered JBossMQ as the messaging subsystem, and even the printed material provided was based on JBossMQ since the training was created for JBoss EAP 4.3. 12) Encouraging Transparency without Ulterior Motives - WebLogic Server 12c like any other software from Oracle can be downloaded any time from anywhere, you should only possess an OTN ("Oracle Technology Network") credential and you can download any enterprise software how many times you want. And is not some kind of "trial" version. It is the official binaries that will be running for ever in your data center. Oracle does not encourages the usage of "specific versions" of our software. The binaries you buy from Oracle are the same binaries anyone in the world could download and use for testing and personal education. JBoss EAP 6 on the other hand are not available for download unless you buy a subscription and get access to the Red Hat enterprise repositories. If you need to test, learn or just start creating your application using Red Hat's middleware software, you should download it from the community website. You are not allowed to download the enterprise version that, according to Red Hat are more secure, reliable and robust. But no one of us want to start the development of a software with an unsecured, unreliable and not scalable middleware right? So what you do? You are "invited" by Red Hat to buy subscriptions from them to get access to the "cool" version of the software. - WebLogic Server 12c prices are publicly available in the Oracle website. If you want to know right now how much WebLogic will cost to your organization, just click here and get access to our price list. In the case of WebLogic, check out the "US Oracle Technology Commercial Price List". Oracle also encourages you to get in touch with a sales representative to discuss discounts that would make possible the investment into our technology. But you are not required to do this, only if you are interested in buying our technology or maybe you want to discuss some discount scenarios. JBoss EAP 6 on the other hand does not have its cost publicly available in Red Hat's website or in any other media, at least is not so easy to get such information. The only link you will possibly find in their website is a "Contact a Sales Representative" link. This is not a very good relationship between an customer and an vendor. This is not an example of transparency, mainly when the software are sold as open. In this situations, customers expects to see the software prices publicly available, so they can have the chance to decide, based on the existing features of the software, if the cost is fair or not. Conclusion Oracle WebLogic is the most mature, secure, reliable and scalable Java EE application server of the market, and have a proven record of success around the globe to prove it's majority. Don't lose the chance to discover today how WebLogic could fit your needs and sustain your global IT middleware strategy, no matter if your strategy are completely based on the Cloud or not.

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• understanding evaluation function

  - by mish

  I am developing a chess program. And have made use of an alpha beta algorithm and a static evaluation function. I have successfully implemented both but I want to improve the evaluation function by automatically tuning the weights assigned to its features. At this point am totally confused about the policy suitable for updating the weights of the function. One policy I have in mind is to check whether a move is good or bad before updating weights but I really know how to implement it. Thus I need ideas and pseudo code please.

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• Parallelism in .NET – Part 12, More on Task Decomposition

  - by Reed

  Many tasks can be decomposed using a Data Decomposition approach, but often, this is not appropriate.  Frequently, decomposing the problem into distinctive tasks that must be performed is a more natural abstraction. However, as I mentioned in Part 1, Task Decomposition tends to be a bit more difficult than data decomposition, and can require a bit more effort.  Before we being parallelizing our algorithm based on the tasks being performed, we need to decompose our problem, and take special care of certain considerations such as ordering and grouping of tasks. Up to this point in this series, I’ve focused on parallelization techniques which are most appropriate when a problem space can be decomposed by data.  Using PLINQ and the Parallel class, I’ve shown how problem spaces where there is a collection of data, and each element needs to be processed, can potentially be parallelized. However, there are many other routines where this is not appropriate.  Often, instead of working on a collection of data, there is a single piece of data which must be processed using an algorithm or series of algorithms.  Here, there is no collection of data, but there may still be opportunities for parallelism. As I mentioned before, in cases like this, the approach is to look at your overall routine, and decompose your problem space based on tasks.  The idea here is to look for discrete “tasks,” individual pieces of work which can be conceptually thought of as a single operation. Let’s revisit the example I used in Part 1, an application startup path.  Say we want our program, at startup, to do a bunch of individual actions, or “tasks”.  The following is our list of duties we must perform right at startup: Display a splash screen Request a license from our license manager Check for an update to the software from our web server If an update is available, download it Setup our menu structure based on our current license Open and display our main, welcome Window Hide the splash screen The first step in Task Decomposition is breaking up the problem space into discrete tasks. This, naturally, can be abstracted as seven discrete tasks.  In the serial version of our program, if we were to diagram this, the general process would appear as: These tasks, obviously, provide some opportunities for parallelism.  Before we can parallelize this routine, we need to analyze these tasks, and find any dependencies between tasks.  In this case, our dependencies include: The splash screen must be displayed first, and as quickly as possible. We can’t download an update before we see whether one exists. Our menu structure depends on our license, so we must check for the license before setting up the menus. Since our welcome screen will notify the user of an update, we can’t show it until we’ve downloaded the update. Since our welcome screen includes menus that are customized based off the licensing, we can’t display it until we’ve received a license. We can’t hide the splash until our welcome screen is displayed. By listing our dependencies, we start to see the natural ordering that must occur for the tasks to be processed correctly. The second step in Task Decomposition is determining the dependencies between tasks, and ordering tasks based on their dependencies. Looking at these tasks, and looking at all the dependencies, we quickly see that even a simple decomposition such as this one can get quite complicated.  In order to simplify the problem of defining the dependencies, it’s often a useful practice to group our tasks into larger, discrete tasks.  The goal when grouping tasks is that you want to make each task “group” have as few dependencies as possible to other tasks or groups, and then work out the dependencies within that group.  Typically, this works best when any external dependency is based on the “last” task within the group when it’s ordered, although that is not a firm requirement.  This process is often called Grouping Tasks.  In our case, we can easily group together tasks, effectively turning this into four discrete task groups: 1. Show our splash screen – This needs to be left as its own task.  First, multiple things depend on this task, mainly because we want this to start before any other action, and start as quickly as possible. 2. Check for Update and Download the Update if it Exists - These two tasks logically group together.  We know we only download an update if the update exists, so that naturally follows.  This task has one dependency as an input, and other tasks only rely on the final task within this group. 3. Request a License, and then Setup the Menus – Here, we can group these two tasks together.  Although we mentioned that our welcome screen depends on the license returned, it also depends on setting up the menu, which is the final task here.  Setting up our menus cannot happen until after our license is requested.  By grouping these together, we further reduce our problem space. 4. Display welcome and hide splash - Finally, we can display our welcome window and hide our splash screen.  This task group depends on all three previous task groups – it cannot happen until all three of the previous groups have completed. By grouping the tasks together, we reduce our problem space, and can naturally see a pattern for how this process can be parallelized.  The diagram below shows one approach: The orange boxes show each task group, with each task represented within.  We can, now, effectively take these tasks, and run a large portion of this process in parallel, including the portions which may be the most time consuming.  We’ve now created two parallel paths which our process execution can follow, hopefully speeding up the application startup time dramatically. The main point to remember here is that, when decomposing your problem space by tasks, you need to: Define each discrete action as an individual Task Discover dependencies between your tasks Group tasks based on their dependencies Order the tasks and groups of tasks

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• A Taxonomy of Numerical Methods v1

  - by JoshReuben

  Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

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• Computer Networks UNISA - Chap 12 &ndash; Networking Security

  - by MarkPearl

  After reading this section you should be able to Identify security risks in LANs and WANs and design security policies that minimize risks Explain how physical security contributes to network security Discuss hardware and design based security techniques Understand methods of encryption such as SSL and IPSec, that can secure data in storage and in transit Describe how popular authentication protocols such as RADIUS< TACACS,Kerberos, PAP, CHAP, and MS-CHAP function Use network operating system techniques to provide basic security Understand wireless security protocols such as WEP, WPA and 802.11i Security Audits Before spending time and money on network security, examine your networks security risks – rate and prioritize risks. Different organizations have different levels of network security requirements. Security Risks Not all security breaches result from a manipulation of network technology – there are human factors that can play a role as well. The following categories are areas of considerations… Risks associated with People Risks associated with Transmission and Hardware Risks associated with Protocols and Software Risks associated with Internet Access An effective security policy A security policy identifies your security goals, risks, levels of authority, designated security coordinator and team members, responsibilities for each team member, and responsibilities for each employee. In addition it specifies how to address security breaches. It should not state exactly which hardware, software, architecture, or protocols will be used to ensure security, nor how hardware or software will be installed and configured. A security policy must address an organizations specific risks. to understand your risks, you should conduct a security audit that identifies vulnerabilities and rates both the severity of each threat and its likelihood of occurring. Security Policy Content Security policy content should… Policies for each category of security Explain to users what they can and cannot do and how these measures protect the networks security Should define what confidential means to the organization Response Policy A security policy should provide for a planned response in the event of a security breach. The response policy should identify the members of a response team, all of whom should clearly understand the the security policy, risks, and measures in place. Some of the roles concerned could include… Dispatcher – the person on call who first notices the breach Manager – the person who coordinates the resources necessary to solve the problem Technical Support Specialist – the person who focuses on solving the problem Public relations specialist – the person who acts as the official spokesperson for the organization Physical Security An important element in network security is restricting physical access to its components. There are various techniques for this including locking doors, security people at access points etc. You should identify the following… Which rooms contain critical systems or data and must be secured Through what means might intruders gain access to these rooms How and to what extent are authorized personnel granted access to these rooms Are authentication methods such as ID cards easy to forge etc. Security in Network Design The optimal way to prevent external security breaches from affecting you LAN is not to connect your LAN to the outside world at all. The next best protection is to restrict access at every point where your LAN connects to the rest of the world. Router Access List – can be used to filter or decline access to a portion of a network for certain devices. Intrusion Detection and Prevention While denying someone access to a section of the network is good, it is better to be able to detect when an attempt has been made and notify security personnel. This can be done using IDS (intrusion detection system) software. One drawback of IDS software is it can detect false positives – i.e. an authorized person who has forgotten his password attempts to logon. Firewalls A firewall is a specialized device, or a computer installed with specialized software, that selectively filters or blocks traffic between networks. A firewall typically involves a combination of hardware and software and may reside between two interconnected private networks. The simplest form of a firewall is a packet filtering firewall, which is a router that examines the header of every packet of data it receives to determine whether that type of packet is authorized to continue to its destination or not. Firewalls can block traffic in and out of a LAN. NOS (Network Operating System) Security Regardless of the operating system, generally every network administrator can implement basic security by restricting what users are authorized to do on a network. Some of the restrictions include things related to Logons – place, time of day, total time logged in, etc Passwords – length, characters used, etc Encryption Encryption is the use of an algorithm to scramble data into a format that can be read only by reversing the algorithm. The purpose of encryption is to keep information private. Many forms of encryption exist and new ways of cracking encryption are continually being invented. The following are some categories of encryption… Key Encryption PGP (Pretty Good Privacy) SSL (Secure Sockets Layer) SSH (Secure Shell) SCP (Secure CoPy) SFTP (Secure File Transfer Protocol) IPSec (Internet Protocol Security) For a detailed explanation on each section refer to pages 596 to 604 of textbook Authentication Protocols Authentication protocols are the rules that computers follow to accomplish authentication. Several types exist and the following are some of the common authentication protocols… RADIUS and TACACS PAP (Password Authentication Protocol) CHAP and MS-CHAP EAP (Extensible Authentication Protocol) 802.1x (EAPoL) Kerberos Wireless Network Security Wireless transmissions are particularly susceptible to eavesdropping. The following are two wireless network security protocols WEP WPA

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• CodePlex Daily Summary for Sunday, March 07, 2010

  CodePlex Daily Summary for Sunday, March 07, 2010New ProjectsAlgorithminator: Universal .NET algorithm visualizer, which helps you to illustrate any algorithm, written in any .NET language. Still in development.ALToolkit: Contains a set of handy .NET components/classes. Currently it contains: * A Numeric Text Box (an Extended NumericUpDown) * A Splash Screen base fo...Automaton Home: Automaton is a home automation software built with a n-Tier, MVVM pattern utilzing WCF, EF, WPF, Silverlight and XBAP.Developer Controls: Developer Controls contains various controls to help build applications that can script/write code.Dynamic Reference Manager: Dynamic Reference Manager is a set (more like a small group) of classes and attributes written in C# that allows any .NET program to reference othe...indiologic: Utilities of an IndioNeural Cryptography in F#: This project is my magistracy resulting work. It is intended to be an example of using neural networks in cryptography. Hashing functions are chose...Particle Filter Visualization: Particle Filter Visualization Program for the Intel Science and Engineering FairPólya: Efficient, immutable, polymorphic collections. .Net lacks them, we provide them*. * By we, we mean I; and by efficient, I mean hopefully so.project euler solutions from mhinze: mhinze project euler solutionsSilverlight 4 and WCF multi layer: Silverlight 4 and WCF multi layersqwarea: Project for a browser-based, minimalistic, massively multiplayer strategy game. Part of the "Génie logiciel et Cloud Computing" course of the ENS (...SuperSocket: SuperSocket, a socket application framework can build FTP/SMTP/POP server easilyToast (for ASP.NET MVC): Dynamic, developer & designer friendly content injection, compression and optimization for ASP.NET MVCNew ReleasesALToolkit: ALToolkit 1.0: Binary release of the libraries containing: NumericTextBox SplashScreen Based on the VB.NET code, but that doesn't really matter.Blacklist of Providers: 1.0-Milestone 1: Blacklist of Providers.Milestone 1In this development release implemented - Main interface (Work Item #5453) - Database (Work Item #5523)C# Linear Hash Table: Linear Hash Table b2: Now includes a default constructor, and will throw an exception if capacity is not set to a power of 2 or loadToMaintain is below 1.Composure: CassiniDev-Trunk-40745-VS2010.rc1.NET4: A simple port of the CassiniDev portable web server project for Visual Studio 2010 RC1 built against .NET 4.0. The WCF tests currently fail unless...Developer Controls: DevControls: These are the version 1.0 releases of these controls. Download the individually or all together (in a .zip file). More releases coming soon!Dynamic Reference Manager: DRM Alpha1: This is the first release. I'm calling it Alpha because I intend implementing other functions, but I do not intend changing the way current functio...ESB Toolkit Extensions: Tellago SOA ESB Extenstions v0.3: Windows Installer file that installs Library on a BizTalk ESB 2.0 system. This Install automatically configures the esb.config to use the new compo...GKO Libraries: GKO Libraries 0.1 Alpha: 0.1 AlphaHome Access Plus+: v3.0.3.0: Version 3.0.3.0 Release Change Log: Added Announcement Box Removed script files that aren't needed Fixed & issue in directory path Stylesheet...Icarus Scene Engine: Icarus Scene Engine 1.10.306.840: Icarus Professional, Icarus Player, the supporting software for Icarus Scene Engine, with some included samples, and the start of a tutorial (with ...mavjuz WndLpt: wndlpt-0.2.5: New: Response to 5 LPT inputs "test i 1" New: Reaction to 12 LPT outputs "test q 8" New: Reaction to all LPT pins "test pin 15" New: Syntax: ...Neural Cryptography in F#: Neural Cryptography 0.0.1: The most simple version of this project. It has a neural network that works just like logical AND and a possibility to recreate neural network from...Password Provider: 1.0.3: This release fixes a bug which caused the program to crash when double clicking on a generic item.RoTwee: RoTwee 6.2.0.0: New feature is as next. 16649 Add hashtag for tweet of tune.Now you can tweet your playing tune with hashtag.Visual Studio DSite: Picture Viewer (Visual C++ 2008): This example source code allows you to view any picture you want in the click of a button. All you got to do is click the button and browser via th...WatchersNET CKEditor™ Provider for DotNetNuke: CKEditor Provider 1.8.00: Whats New File Browser: Folders & Files View reworked File Browser: Folders & Files View reworked File Browser: Folders are displayed as TreeVi...WSDLGenerator: WSDLGenerator 0.0.0.4: - replaced CommonLibrary.dll by CommandLineParser.dll - added better support for custom complex typesMost Popular ProjectsMetaSharpSilverlight ToolkitASP.NET Ajax LibraryAll-In-One Code FrameworkWindows 7 USB/DVD Download Toolニコ生アラートWindows Double ExplorerVirtual Router - Wifi Hot Spot for Windows 7 / 2008 R2Caliburn: An Application Framework for WPF and SilverlightArkSwitchMost Active ProjectsUmbraco CMSRawrSDS: Scientific DataSet library and toolsBlogEngine.NETjQuery Library for SharePoint Web Servicespatterns & practices – Enterprise LibraryIonics Isapi Rewrite FilterFarseer Physics EngineFasterflect - A Fast and Simple Reflection APIFluent Assertions

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• Big Data&rsquo;s Killer App&hellip;

  - by jean-pierre.dijcks

  Recently Keith spent  some time talking about the cloud on this blog and I will spare you my thoughts on the whole thing. What I do want to write down is something about the Big Data movement and what I think is the killer app for Big Data... Where is this coming from, ok, I confess... I spent 3 days in cloud land at the Cloud Connect conference in Santa Clara and it was quite a lot of fun. One of the nice things at Cloud Connect was that there was a track dedicated to Big Data, which prompted me to some extend to write this post. What is Big Data anyways? The most valuable point made in the Big Data track was that Big Data in itself is not very cool. Doing something with Big Data is what makes all of this cool and interesting to a business user! The other good insight I got was that a lot of people think Big Data means a single gigantic monolithic system holding gazillions of bytes or documents or log files. Well turns out that most people in the Big Data track are talking about a lot of collections of smaller data sets. So rather than thinking "big = monolithic" you should be thinking "big = many data sets". This is more than just theoretical, it is actually relevant when thinking about big data and how to process it. It is important because it means that the platform that stores data will most likely consist out of multiple solutions. You may be storing logs on something like HDFS, you may store your customer information in Oracle and you may store distilled clickstream information in some distilled form in MySQL. The big question you will need to solve is not what lives where, but how to get it all together and get some value out of all that data. NoSQL and MapReduce Nope, sorry, this is not the killer app... and no I'm not saying this because my business card says Oracle and I'm therefore biased. I think language is important, but as with storage I think pragmatic is better. In other words, some questions can be answered with SQL very efficiently, others can be answered with PERL or TCL others with MR. History should teach us that anyone trying to solve a problem will use any and all tools around. For example, most data warehouses (Big Data 1.0?) get a lot of data in flat files. Everyone then runs a bunch of shell scripts to massage or verify those files and then shoves those files into the database. We've even built shell script support into external tables to allow for this. I think the Big Data projects will do the same. Some people will use MapReduce, although I would argue that things like Cascading are more interesting, some people will use Java. Some data is stored on HDFS making Cascading the way to go, some data is stored in Oracle and SQL does do a good job there. As with storage and with history, be pragmatic and use what fits and neither NoSQL nor MR will be the one and only. Also, a language, while important, does in itself not deliver business value. So while cool it is not a killer app... Vertical Behavioral Analytics This is the killer app! And you are now thinking: "what does that mean?" Let's decompose that heading. First of all, analytics. I would think you had guessed by now that this is really what I'm after, and of course you are right. But not just analytics, which has a very large scope and means many things to many people. I'm not just after Business Intelligence (analytics 1.0?) or data mining (analytics 2.0?) but I'm after something more interesting that you can only do after collecting large volumes of specific data. That all important data is about behavior. What do my customers do? More importantly why do they behave like that? If you can figure that out, you can tailor web sites, stores, products etc. to that behavior and figure out how to be successful. Today's behavior that is somewhat easily tracked is web site clicks, search patterns and all of those things that a web site or web server tracks. that is where the Big Data lives and where these patters are now emerging. Other examples however are emerging, and one of the examples used at the conference was about prediction churn for a telco based on the social network its members are a part of. That social network is not about LinkedIn or Facebook, but about who calls whom. I call you a lot, you switch provider, and I might/will switch too. And that just naturally brings me to the next word, vertical. Vertical in this context means per industry, e.g. communications or retail or government or any other vertical. The reason for being more specific than just behavioral analytics is that each industry has its own data sources, has its own quirky logic and has its own demands and priorities. Of course, the methods and some of the software will be common and some will have both retail and service industry analytics in place (your corner coffee store for example). But the gist of it all is that analytics that can predict customer behavior for a specific focused group of people in a specific industry is what makes Big Data interesting. Building a Vertical Behavioral Analysis System Well, that is going to be interesting. I have not seen much going on in that space and if I had to have some criticism on the cloud connect conference it would be the lack of concrete user cases on big data. The telco example, while a step into the vertical behavioral part is not really on big data. It used a sample of data from the customers' data warehouse. One thing I do think, and this is where I think parts of the NoSQL stuff come from, is that we will be doing this analysis where the data is. Over the past 10 years we at Oracle have called this in-database analytics. I guess we were (too) early? Now the entire market is going there including companies like SAS. In-place btw does not mean "no data movement at all", what it means that you will do this on data's permanent home. For SAS that is kind of the current problem. Most of the inputs live in a data warehouse. So why move it into SAS and back? That all worked with 1 TB data warehouses, but when we are looking at 100TB to 500 TB of distilled data... Comments? As it is still early days with these systems, I'm very interested in seeing reactions and thoughts to some of these thoughts...

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• Real Life Pixar Lamp Can’t Get Enough Of Human Interaction

  - by Jason Fitzpatrick

  This curious lamp, powered by an Arduino board and servo motors, is just as playful as the on-screen counterpart that inspired its creation. The New Zealand Herald reports on the creation of the lamp, seen in action in the video above: The project is a collaborative effort by Victoria University students Shanshan Zhou, Adam Ben-Gur and Joss Doggett, who met in a Physical Computing class. The lamp’s movements are informed by a webcam with an algorithm working behind it. Robotics and facial recognition technology enable the lamp to search for faces in the images from its webcam. When it spots a face, it follows as if trying to maintain eye contact. How to Access Your Router If You Forget the Password Secure Yourself by Using Two-Step Verification on These 16 Web Services How to Fix a Stuck Pixel on an LCD Monitor

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• How Oracle Data Integration Customers Differentiate Their Business in Competitive Markets

  - by Irem Radzik

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 With data being a central force in driving innovation and competing effectively, data integration has become a key IT approach to remove silos and ensure working with consistent and trusted data. Especially with the release of 12c version, Oracle Data Integrator and Oracle GoldenGate offer easy-to-use and high-performance solutions that help companies with their critical data initiatives, including big data analytics, moving to cloud architectures, modernizing and connecting transactional systems and more. In a recent press release we announced the great momentum and analyst recognition Oracle Data Integration products have achieved in the data integration and replication market. In this press release we described some of the key new features of Oracle Data Integrator 12c and Oracle GoldenGate 12c. In addition, a few from our 4500+ customers explained how Oracle’s data integration platform helped them achieve their business goals. In this blog post I would like to go over what these customers shared about their experience. Land O’Lakes is one of America’s premier member-owned cooperatives, and offers an extensive line of agricultural supplies, as well as production and business services. Rich Bellefeuille, manager, ETL & data warehouse for Land O’Lakes told us how GoldenGate helped them modernize their critical ERP system without impacting service and how they are moving to new projects with Oracle Data Integrator 12c: “With Oracle GoldenGate 11g, we've been able to migrate our enterprise-wide implementation of Oracle’s JD Edwards EnterpriseOne, ERP system, to a new database and application server platform with minimal downtime to our business. Using Oracle GoldenGate 11g we reduced database migration time from nearly 30 hours to less than 30 minutes. Given our quick success, we are considering expansion of our Oracle GoldenGate 12c footprint. We are also in the midst of deploying a solution leveraging Oracle Data Integrator 12c to manage our pricing data to handle orders more effectively and provide a better relationship with our clients. We feel we are gaining higher productivity and flexibility with Oracle's data integration products." ICON, a global provider of outsourced development services to the pharmaceutical, biotechnology and medical device industries, highlighted the competitive advantage that a solid data integration foundation brings. Diarmaid O’Reilly, enterprise data warehouse manager, ICON plc said “Oracle Data Integrator enables us to align clinical trials intelligence with the information needs of our sponsors. It helps differentiate ICON’s services in an increasingly competitive drug-development industry."  You can find more info on ICON's implementation here. A popular use case for Oracle GoldenGate’s real-time data integration is offloading operational reporting from critical transaction processing systems. SolarWorld, one of the world’s largest solar-technology producers and the largest U.S. solar panel manufacturer, implemented Oracle GoldenGate for real-time data integration of manufacturing data for fast analysis. Russ Toyama, U.S. senior database administrator for SolarWorld told us real-time data helps their operations and GoldenGate’s solution supports high performance of their manufacturing systems: “We use Oracle GoldenGate for real-time data integration into our decision support system, which performs real-time analysis for manufacturing operations to continuously improve product quality, yield and efficiency. With reliable and low-impact data movement capabilities, Oracle GoldenGate also helps ensure that our critical manufacturing systems are stable and operate with high performance."  You can watch the full interview with SolarWorld's Russ Toyama here. Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Starwood Hotels and Resorts is one of the many customers that found out how well Oracle Data Integration products work with Oracle Exadata. Gordon Light, senior director of information technology for StarWood Hotels, says they had notable performance gain in loading Oracle Exadata reporting environment: “We leverage Oracle GoldenGate to replicate data from our central reservations systems and other OLTP databases – significantly decreasing the overall ETL duration. Moving forward, we plan to use Oracle GoldenGate to help the company achieve near-real-time reporting.”You can listen about Starwood Hotels' implementation here. Many companies combine the power of Oracle GoldenGate with Oracle Data Integrator to have a single, integrated data integration platform for variety of use cases across the enterprise. Ufone is another good example of that. The leading mobile communications service provider of Pakistan has improved customer service using timely customer data in its data warehouse. Atif Aslam, head of management information systems for Ufone says: “Oracle Data Integrator and Oracle GoldenGate help us integrate information from various systems and provide up-to-date and real-time CRM data updates hourly, rather than daily. The applications have simplified data warehouse operations and allowed business users to make faster and better informed decisions to protect revenue in the fast-moving Pakistani telecommunications market.” You can read more about Ufone's use case here. In our Oracle Data Integration 12c launch webcast back in November we also heard from BT’s CTO Surren Parthab about their use of GoldenGate for moving to private cloud architecture. Surren also shared his perspectives on Oracle Data Integrator 12c and Oracle GoldenGate 12c releases. You can watch the video here. These are only a few examples of leading companies that have made data integration and real-time data access a key part of their data governance and IT modernization initiatives. They have seen real improvements in how their businesses operate and differentiate in today’s competitive markets. You can read about other customer examples in our Ebook: The Path to the Future and access resources including white papers, data sheets, podcasts and more via our Oracle Data Integration resource kit. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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• JMX Based Monitoring - Part Four - Business App Server Monitoring

  - by Anthony Shorten

  In the last blog entry I talked about the Oracle Utilities Application Framework V4 feature for monitoring and managing aspects of the Web Application Server using JMX. In this blog entry I am going to discuss a similar new feature that allows JMX to be used for management and monitoring the Oracle Utilities business application server component. This feature is primarily focussed on performance tracking of the product. In first release of Oracle Utilities Customer Care And Billing (V1.x I am talking about), we used to use Oracle Tuxedo as part of the architecture. In Oracle Utilities Application Framework V2.0 and above, we removed Tuxedo from the architecture. One of the features that some customers used within Tuxedo was the performance tracking ability. The idea was that you enabled performance logging on the individual Tuxedo servers and then used a utility named txrpt to produce a performance report. This report would list every service called, the number of times it was called and the average response time. When I worked a performance consultant, I used this report to identify badly performing services and also gauge the overall performance characteristics of a site. When Tuxedo was removed from the architecture this information was also lost. While you can get some information from access.log and some Mbeans supplied by the Web Application Server it was not at the same granularity as txrpt or as useful. I am happy to say we have not only reintroduced this facility in Oracle Utilities Application Framework but it is now accessible via JMX and also we have added more detail into the performance tracking. Most of this new design was working with customers around the world to make sure we introduced a new feature that not only satisfied their performance tracking needs but allowed for finer grained performance analysis. As with the Web Application Server, the Business Application Server JMX monitoring is enabled by specifying a JMX port number in RMI Port number for JMX Business and initial credentials in the JMX Enablement System User ID and JMX Enablement System Password configuration options. These options are available using the configureEnv[.sh] -a utility. These credentials are shared across the Web Application Server and Business Application Server for authorization purposes. Once this is information is supplied a number of configuration files are built (by the initialSetup[.sh] utility) to configure the facility: spl.properties - contains the JMX URL, the security configuration and the mbeans that are enabled. For example, on my demonstration machine: spl.runtime.management.rmi.port=6750 spl.runtime.management.connector.url.default=service:jmx:rmi:///jndi/rmi://localhost:6750/oracle/ouaf/ejbAppConnector jmx.remote.x.password.file=scripts/ouaf.jmx.password.file jmx.remote.x.access.file=scripts/ouaf.jmx.access.file ouaf.jmx.com.splwg.ejb.service.management.PerformanceStatistics=enabled ouaf.jmx.* files - contain the userid and password. The default configuration uses the JMX default configuration. You can use additional security features by altering the spl.properties file manually or using a custom template. For more security options see JMX Security for more details. Once it has been configured and the changes reflected in the product using the initialSetup[.sh] utility the JMX facility can be used. For illustrative purposes I will use jconsole but any JSR160 complaint browser or client can be used (with the appropriate configuration). Once you start jconsole (ensure that splenviron[.sh] is executed prior to execution to set the environment variables or for remote connection, ensure java is in your path and jconsole.jar in your classpath) you specify the URL in the spl.runtime.management.connnector.url.default entry. For example: You are then able to track performance of the product using the PerformanceStatistics Mbean. The attributes of the PerformanceStatistics Mbean are counts of each object type. This is where this facility differs from txrpt. The information that is collected includes the following: The Service Type is captured so you can filter the results in terms of the type of service. For maintenance type services you can even see the transaction type (ADD, CHANGE etc) so you can see the performance of updates against read transactions. The Minimum and Maximum are also collected to give you an idea of the spread of performance. The last call is recorded. The date, time and user of the last call are recorded to give you an idea of the timeliness of the data. The Mbean maintains a set of counters per Service Type to give you a summary of the types of transactions being executed. This gives you an overall picture of the types of transactions and volumes at your site. There are a number of interesting operations that can also be performed: reset - This resets the statistics back to zero. This is an important operation. For example, txrpt is restricted to collecting statistics per hour, which is ok for most people. But what if you wanted to be more granular? This operation allows to set the collection period to anything you wish. The statistics collected will represent values since the last restart or last reset. completeExecutionDump - This is the operation that produces a CSV in memory to allow extraction of the data. All the statistics are extracted (see the Server Administration Guide for a full list). This can be then loaded into a database, a tool or simply into your favourite spreadsheet for analysis. Here is an extract of an execution dump from my demonstration environment to give you an idea of the format: ServiceName, ServiceType, MinTime, MaxTime, Avg Time, # of Calls, Latest Time, Latest Date, Latest User ... CFLZLOUL, EXECUTE_LIST, 15.0, 64.0, 22.2, 10, 16.0, 2009-12-16::11-25-36-932, ASHORTEN CILBBLLP, READ, 106.0, 1184.0, 466.3333333333333, 6, 106.0, 2009-12-16::11-39-01-645, BOBAMA CILBBLLP, DELETE, 70.0, 146.0, 108.0, 2, 70.0, 2009-12-15::12-53-58-280, BPAYS CILBBLLP, ADD, 860.0, 4903.0, 2243.5, 8, 860.0, 2009-12-16::17-54-23-862, LELLISON CILBBLLP, CHANGE, 112.0, 3410.0, 815.1666666666666, 12, 112.0, 2009-12-16::11-40-01-103, ASHORTEN CILBCBAL, EXECUTE_LIST, 8.0, 84.0, 26.0, 22, 23.0, 2009-12-16::17-54-01-643, LJACKMAN InitializeUserInfoService, READ_SYSTEM, 49.0, 962.0, 70.83777777777777, 450, 63.0, 2010-02-25::11-21-21-667, ASHORTEN InitializeUserService, READ_SYSTEM, 130.0, 2835.0, 234.85777777777778, 450, 216.0, 2010-02-25::11-21-21-446, ASHORTEN MenuLoginService, READ_SYSTEM, 530.0, 1186.0, 703.3333333333334, 9, 530.0, 2009-12-16::16-39-31-172, ASHORTEN NavigationOptionDescriptionService, READ_SYSTEM, 2.0, 7.0, 4.0, 8, 2.0, 2009-12-21::09-46-46-892, ASHORTEN ... There are other operations and attributes available. Refer to the Server Administration Guide provided with your product to understand the full et of operations and attributes. This is one of the many features I am proud that we implemented as it allows flexible monitoring of the performance of the product.

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• How can Swift be so much faster than Objective-C in these comparisons?

  - by Yellow

  Apple launched its new programming language Swift at WWDC14. In the presentation, they made some performance comparisons between Objective-C and Python. The following is a picture of one of their slides, of a comparison of those three languages performing some complex object sort: There was an even more incredible graph about a performance comparison using the RC4 encryption algorithm. Obviously this is a marketing talk, and they didn't go into detail on how this was implemented in each. I leaves me wondering though: How can a new programming language be so much faster? Are the Objective-C results caused by a bad compiler or is there something less efficient in Objective-C than Swift? How would you explain a 40% performance increase? I understand that garbage collection/automated reference control might produce some additional overhead, but this much?

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• Algorithmia Source Code released on CodePlex

  - by FransBouma

  Following the release of our BCL Extensions Library on CodePlex, we have now released the source-code of Algorithmia on CodePlex! Algorithmia is an algorithm and data-structures library for .NET 3.5 or higher and is one of the pillars LLBLGen Pro v3's designer is built on. The library contains many data-structures and algorithms, and the source-code is well documented and commented, often with links to official descriptions and papers of the algorithms and data-structures implemented. The source-code is shared using Mercurial on CodePlex and is licensed under the friendly BSD2 license. User documentation is not available at the moment but will be added soon. One of the main design goals of Algorithmia was to create a library which contains implementations of well-known algorithms which weren't already implemented in .NET itself. This way, more developers out there can enjoy the results of many years of what the field of Computer Science research has delivered. Some algorithms and datastructures are known in .NET but are re-implemented because the implementation in .NET isn't efficient for many situations or lacks features. An example is the linked list in .NET: it doesn't have an O(1) concat operation, as every node refers to the containing LinkedList object it's stored in. This is bad for algorithms which rely on O(1) concat operations, like the Fibonacci heap implementation in Algorithmia. Algorithmia therefore contains a linked list with an O(1) concat feature. The following functionality is available in Algorithmia: Command, Command management. This system is usable to build a fully undo/redo aware system by building your object graph using command-aware classes. The Command pattern is implemented using a system which allows transparent undo-redo and command grouping so you can use it to make a class undo/redo aware and set properties, use its contents without using commands at all. The Commands namespace is the namespace to start. Classes you'd want to look at are CommandifiedMember, CommandifiedList and KeyedCommandifiedList. See the CommandQueueTests in the test project for examples. Graphs, Graph algorithms. Algorithmia contains a sophisticated graph class hierarchy and algorithms implemented onto them: non-directed and directed graphs, as well as a subgraph view class, which can be used to create a view onto an existing graph class which can be self-maintaining. Algorithms include transitive closure, topological sorting and others. A feature rich depth-first search (DFS) crawler is available so DFS based algorithms can be implemented quickly. All graph classes are undo/redo aware, as they can be set to be 'commandified'. When a graph is 'commandified' it will do its housekeeping through commands, which makes it fully undo-redo aware, so you can remove, add and manipulate the graph and undo/redo the activity automatically without any extra code. If you define the properties of the class you set as the vertex type using CommandifiedMember, you can manipulate the properties of vertices and the graph contents with full undo/redo functionality without any extra code. Heaps. Heaps are data-structures which have the largest or smallest item stored in them always as the 'root'. Extracting the root from the heap makes the heap determine the next in line to be the 'maximum' or 'minimum' (max-heap vs. min-heap, all heaps in Algorithmia can do both). Algorithmia contains various heaps, among them an implementation of the Fibonacci heap, one of the most efficient heap datastructures known today, especially when you want to merge different instances into one. Priority queues. Priority queues are specializations of heaps. Algorithmia contains a couple of them. Sorting. What's an algorithm library without sort algorithms? Algorithmia implements a couple of sort algorithms which sort the data in-place. This aspect is important in situations where you want to sort the elements in a buffer/list/ICollection in-place, so all data stays in the data-structure it already is stored in. PropertyBag. It re-implements Tony Allowatt's original idea in .NET 3.5 specific syntax, which is to have a generic property bag and to be able to build an object in code at runtime which can be bound to a property grid for editing. This is handy for when you have data / settings stored in XML or other format, and want to create an editable form of it without creating many editors. IEditableObject/IDataErrorInfo implementations. It contains default implementations for IEditableObject and IDataErrorInfo (EditableObjectDataContainer for IEditableObject and ErrorContainer for IDataErrorInfo), which make it very easy to implement these interfaces (just a few lines of code) without having to worry about bookkeeping during databinding. They work seamlessly with CommandifiedMember as well, so your undo/redo aware code can use them out of the box. EventThrottler. It contains an event throttler, which can be used to filter out duplicate events in an event stream coming into an observer from an event. This can greatly enhance performance in your UI without needing to do anything other than hooking it up so it's placed between the event source and your real handler. If your UI is flooded with events from data-structures observed by your UI or a middle tier, you can use this class to filter out duplicates to avoid redundant updates to UI elements or to avoid having observers choke on many redundant events. Small, handy stuff. A MultiValueDictionary, which can store multiple unique values per key, instead of one with the default Dictionary, and is also merge-aware so you can merge two into one. A Pair class, to quickly group two elements together. Multiple interfaces for helping with building a de-coupled, observer based system, and some utility extension methods for the defined data-structures. We regularly update the library with new code. If you have ideas for new algorithms or want to share your contribution, feel free to discuss it on the project's Discussions page or send us a pull request. Enjoy!

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• Improving the Industry’s Best Cloud Project Portfolio Management (PPM) Solution – New Release of Instantis EnterpriseTrack

  - by Melissa Centurio Lopes

  Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} By Yasser Mahmud, Vice President of Product Strategy & Industry Marketing, Oracle Primavera We know that in today’s rapidly changing world, organizations and leaders must adapt to fierce competition, business climate change and customers consistently demanding more for less. And project portfolio management (PPM) initiatives are a key component to help organizations thrive and stand out among competitors. That’s why I’m excited to announce Instantis EnterpriseTrack 8.5. Since Oracle’s acquisition of Instantis late last year, we’ve been busy working to enhance the leading cloud PPM solution. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Here’s what’s new: Perform more precise resource planning and management  Gain more precise capacity visibility for resource planning and project execution with resource calendars that capture vacation, LOA and part-time resource availability Ensure compliance and governance processes  with activity labor cost capitalization Improve project labor cost estimation, tracking and administration with variable resource rates Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Optimize Project Demand Management And Execution Enhance productivity and analysis with project request flexible staffing plan and simplified finance estimation Improve project status communication and execution with estimated time to complete (ETC) in timesheets and projects Achieve audit compliance and governance with field change history for key project and project request fields Enforce proper financial accounting processes with the new strict finance lock/close period option Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Improve Reporting and the User Experience Enhance user productivity and analysis with improved listing pages Improve program reporting with new program filters in listing pages and reports Run large data volume user defined Excel reports with MS Excel 2010 support Accelerate user productivity and satisfaction with an improved user interface for project issues, risks, and scope changes Enjoy faster system response and improved user experience with  optimized listing pages, resource planning, and application cache Deliver user self-service training on demand with UPK support And if that wasn’t enough, we’ve also made additional improvements to timesheets, field change history and finance lock/close period. Learn more about Instantis EnterpriseTrack 8.5.

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• SQL SERVER – Guest Post – Architecting Data Warehouse – Niraj Bhatt

  - by pinaldave

  Niraj Bhatt works as an Enterprise Architect for a Fortune 500 company and has an innate passion for building / studying software systems. He is a top rated speaker at various technical forums including Tech·Ed, MCT Summit, Developer Summit, and Virtual Tech Days, among others. Having run a successful startup for four years Niraj enjoys working on – IT innovations that can impact an enterprise bottom line, streamlining IT budgets through IT consolidation, architecture and integration of systems, performance tuning, and review of enterprise applications. He has received Microsoft MVP award for ASP.NET, Connected Systems and most recently on Windows Azure. When he is away from his laptop, you will find him taking deep dives in automobiles, pottery, rafting, photography, cooking and financial statements though not necessarily in that order. He is also a manager/speaker at BDOTNET, Asia’s largest .NET user group. Here is the guest post by Niraj Bhatt. As data in your applications grows it’s the database that usually becomes a bottleneck. It’s hard to scale a relational DB and the preferred approach for large scale applications is to create separate databases for writes and reads. These databases are referred as transactional database and reporting database. Though there are tools / techniques which can allow you to create snapshot of your transactional database for reporting purpose, sometimes they don’t quite fit the reporting requirements of an enterprise. These requirements typically are data analytics, effective schema (for an Information worker to self-service herself), historical data, better performance (flat data, no joins) etc. This is where a need for data warehouse or an OLAP system arises. A Key point to remember is a data warehouse is mostly a relational database. It’s built on top of same concepts like Tables, Rows, Columns, Primary keys, Foreign Keys, etc. Before we talk about how data warehouses are typically structured let’s understand key components that can create a data flow between OLTP systems and OLAP systems. There are 3 major areas to it: a) OLTP system should be capable of tracking its changes as all these changes should go back to data warehouse for historical recording. For e.g. if an OLTP transaction moves a customer from silver to gold category, OLTP system needs to ensure that this change is tracked and send to data warehouse for reporting purpose. A report in context could be how many customers divided by geographies moved from sliver to gold category. In data warehouse terminology this process is called Change Data Capture. There are quite a few systems that leverage database triggers to move these changes to corresponding tracking tables. There are also out of box features provided by some databases e.g. SQL Server 2008 offers Change Data Capture and Change Tracking for addressing such requirements. b) After we make the OLTP system capable of tracking its changes we need to provision a batch process that can run periodically and takes these changes from OLTP system and dump them into data warehouse. There are many tools out there that can help you fill this gap – SQL Server Integration Services happens to be one of them. c) So we have an OLTP system that knows how to track its changes, we have jobs that run periodically to move these changes to warehouse. The question though remains is how warehouse will record these changes? This structural change in data warehouse arena is often covered under something called Slowly Changing Dimension (SCD). While we will talk about dimensions in a while, SCD can be applied to pure relational tables too. SCD enables a database structure to capture historical data. This would create multiple records for a given entity in relational database and data warehouses prefer having their own primary key, often known as surrogate key. As I mentioned a data warehouse is just a relational database but industry often attributes a specific schema style to data warehouses. These styles are Star Schema or Snowflake Schema. The motivation behind these styles is to create a flat database structure (as opposed to normalized one), which is easy to understand / use, easy to query and easy to slice / dice. Star schema is a database structure made up of dimensions and facts. Facts are generally the numbers (sales, quantity, etc.) that you want to slice and dice. Fact tables have these numbers and have references (foreign keys) to set of tables that provide context around those facts. E.g. if you have recorded 10,000 USD as sales that number would go in a sales fact table and could have foreign keys attached to it that refers to the sales agent responsible for sale and to time table which contains the dates between which that sale was made. These agent and time tables are called dimensions which provide context to the numbers stored in fact tables. This schema structure of fact being at center surrounded by dimensions is called Star schema. A similar structure with difference of dimension tables being normalized is called a Snowflake schema. This relational structure of facts and dimensions serves as an input for another analysis structure called Cube. Though physically Cube is a special structure supported by commercial databases like SQL Server Analysis Services, logically it’s a multidimensional structure where dimensions define the sides of cube and facts define the content. Facts are often called as Measures inside a cube. Dimensions often tend to form a hierarchy. E.g. Product may be broken into categories and categories in turn to individual items. Category and Items are often referred as Levels and their constituents as Members with their overall structure called as Hierarchy. Measures are rolled up as per dimensional hierarchy. These rolled up measures are called Aggregates. Now this may seem like an overwhelming vocabulary to deal with but don’t worry it will sink in as you start working with Cubes and others. Let’s see few other terms that we would run into while talking about data warehouses. ODS or an Operational Data Store is a frequently misused term. There would be few users in your organization that want to report on most current data and can’t afford to miss a single transaction for their report. Then there is another set of users that typically don’t care how current the data is. Mostly senior level executives who are interesting in trending, mining, forecasting, strategizing, etc. don’t care for that one specific transaction. This is where an ODS can come in handy. ODS can use the same star schema and the OLAP cubes we saw earlier. The only difference is that the data inside an ODS would be short lived, i.e. for few months and ODS would sync with OLTP system every few minutes. Data warehouse can periodically sync with ODS either daily or weekly depending on business drivers. Data marts are another frequently talked about topic in data warehousing. They are subject-specific data warehouse. Data warehouses that try to span over an enterprise are normally too big to scope, build, manage, track, etc. Hence they are often scaled down to something called Data mart that supports a specific segment of business like sales, marketing, or support. Data marts too, are often designed using star schema model discussed earlier. Industry is divided when it comes to use of data marts. Some experts prefer having data marts along with a central data warehouse. Data warehouse here acts as information staging and distribution hub with spokes being data marts connected via data feeds serving summarized data. Others eliminate the need for a centralized data warehouse citing that most users want to report on detailed data. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Business Intelligence, Data Warehousing, Database, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Difference Procedural Generation and Random Generation

  - by U-No-Poo

  Today, I got into an argument about the term "procedural generation". My point was that its different from "classic" random generation in the way that procedural is based on a more mathematical, fractal based, algorithm leading to a more "realistic" distribution and the usual randomness of most languages are based on a pseudo-random-number generator, leading to an "unrealistic", in a way, ugly, distribution. This discussion was made with a heightmap in mind. The discussion left me somehow unconvinced about my own arguments though, so, is there more to it? Or am I the one who is, in fact, simply wrong?

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• Implementing algorithms via compute shaders vs. pipeline shaders

  - by TravisG

  With the availability of compute shaders for both DirectX and OpenGL it's now possible to implement many algorithms without going through the rasterization pipeline and instead use general purpose computing on the GPU to solve the problem. For some algorithms this seems to become the intuitive canonical solution because they're inherently not rasterization based, and rasterization-based shaders seemed to be a workaround to harness GPU power (simple example: creating a noise texture. No quad needs to be rasterized here). Given an algorithm that can be implemented both ways, are there general (potential) performance benefits over using compute shaders vs. going the normal route? Are there drawbacks that we should watch out for (for example, is there some kind of unusual overhead to switching from/to compute shaders at runtime)? Are there perhaps other benefits or drawbacks to consider when choosing between the two?

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• SQL SERVER When are Statistics Updated What triggers Statistics to Update

  If you are an SQL Server Consultant/Trainer involved with Performance Tuning and Query Optimization, I am sure you have faced the following questions many times.When is statistics updated? What is the interval of Statistics update? What is the algorithm behind update statistics? These are the puzzling questions and more.I searched the Internet as well many [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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• How to detect 2D line on line collision?

  - by Vish

  I'm a flash actionscript game developer who is a bit backward with mathematics, though I find physics both interesting and cool. For reference this is a similar game to the one I'm making: Untangled flash game I have made an untangled game almost to full completion of logic. But, when two lines intersect, I need those intersected or 'tangled' lines to show a different color; red. It would be really kind of you people if you could suggest an algorithm with/without math for detecting line segment collisions. I'm basically a person who likes to think 'visually' than 'arithmetically' :) P.S I'm trying to make a function as private function isIntersecting(A:Point, B:Point, C:Point, D:Point):Boolean Thanks in advance.

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