Search Results

Search found 5 results on 1 pages for 'spaceowl'.

Page 1/1 | 1 

• Which game logic should run when doing prediction for PNP state updates

  - by spaceOwl

  We are writing a multiplayer game, where each game client (player) is responsible for sending state updates regarding its "owned" objects to other players. Each message that arrives to other (remote) clients is processed as such: Figure out when the message was sent. Create a diff between NOW and that time. Run game specific logic to bring the received state to "current" time. I am wondering which sort of logic should execute as part of step #3 ? Our game is composed of a physical update (position, speed, acceleration, etc) and many other components that can update an object's state and occur regularly (locally). There's a trade off here - Getting the new state quickly or remaining "faithful" to the true state representation and executing the whole thing to predict the "true" state when receiving state updates from remote clients. Which one is recommended to be used? and why?

  Read the article

• Mobile Multiplayer games and coping with high latency

  - by spaceOwl

  I'm currently researching regarding a design for an online (realtime) mobile multiplayer game. As such, i'm taking into consideration that latencies (lag) is going to be high (perhaps higher than PC/consoles). I'd like to know if there are ways to overcome this or minimize the issues of high latency? The model i'll be using is peer-to-peer (using Photon cloud to broadcast messages to all other players). How do i deal with a scenario where a message about a local object's state at time t will only get to other players at *t + HUGE_LAG* ?

  Read the article

• Sending state diffs (deltas) and unreliable connections

  - by spaceOwl

  We're building a realtime multiplayer game, in which each player is responsible for reporting its state on every iteration of the game loop. The state updates are broadcasted using unreliable UDP. To minimize state data sending, we've come up with a system that will send only deltas (whatever state data that was changed). This method however is flawed, since a lost packet will mean that other players will not receive the delta, making the game behave in an unexpected way. For example: Assume that state is comprised of: { positionX, positionY, health } Frame 1 - positionX changed --> send a packet with positionX only. Frame 2 - health changed // lost ! Frame 3 - positionY changed --> send a packet with positionY only. // Other players don't know about health change. How can one overcome this issue then? sending the entire data is not always feasible.

  Read the article

• Passing data between engine layers

  - by spaceOwl

  I am building a software system (game engine with networking support ) that is made up of (roughly) these layers: Game Layer Messaging Layer Networking Layer Game related data is passed to the messaging layer (this could be anything that is game specific), where they are to be converted to network specific messages (which are then serialized to byte arrays). I'm looking for a way to be able to convert "game" data into "network" data, such that no strong coupling between these layers will exist. As it looks now, the Messaging layer sits between both layers (game and network) and "knows" both of them (it contains Converter objects that know how to translate between data objects of both layers back and forth). I am not sure this is the best solution. Is there a good design for passing objects between layers? I'd like to learn more about the different options.

  Read the article

• How to perform game object smoothing in multiplayer games

  - by spaceOwl

  We're developing an infrastructure to support multiplayer games for our game engine. In simple terms, each client (player) engine sends some pieces of data regarding the relevant game objects at a given time interval. On the receiving end, we step the incoming data to current time (to compensate for latency), followed by a smoothing step (which is the subject of this question). I was wondering how smoothing should be performed ? Currently the algorithm is similar to this: Receive incoming state for an object (position, velocity, acceleration, rotation, custom data like visual properties, etc). Calculate a diff between local object position and the position we have after previous prediction steps. If diff doesn't exceed some threshold value, start a smoothing step: Mark the object's CURRENT POSITION and the TARGET POSITION. Linear interpolate between these values for 0.3 seconds. I wonder if this scheme is any good, or if there is any other common implementation or algorithm that should be used? (For example - should i only smooth out the position? or other values, such as speed, etc) any help will be appreciated.

  Read the article

1