An auto-adaptive dead reckoning algorithm for distributed interactive simulation
PADS '99 Proceedings of the thirteenth workshop on Parallel and distributed simulation
Consistency in replicated continuous interactive media
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Design and Evaluation of MiMaze, a Multi-Player Game on the Internet
ICMCS '98 Proceedings of the IEEE International Conference on Multimedia Computing and Systems
Accuracy in dead-reckoning based distributed multi-player games
Proceedings of 3rd ACM SIGCOMM workshop on Network and system support for games
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Conventional GRID service is static (no mobility), and it has many drawbacks such as continuous connection, waste of bandwidth, and service overloading. Wireless GRID supports mobility, however it should consider geographic position to support efficient resource sharing and routing. When the devices in the GRID are highly mobile, there will be much traffic to exchange the geographic position information of each mobile node, and this makes adverse effect on efficient battery usage. To minimize the network traffic between mobile users, we use dead reckoning algorithm for each mobile nodes, where each node uses the algorithm to estimates its own movement (also other node's movement), and when the estimation error is over threshold, the node sends the UPDATE (including position, velocity, etc) packet to other devices. As the estimation accuracy is increased, each node can minimize the number of UPDATE packet transmission. To improve the prediction accuracy of dead reckoning algorithm, we propose Kalman filter based dead reckoning approach. To experiment our scheme, we implement a popular network game (BZFlag) with our scheme added on each mobile node, and the results show that we can achieve better prediction accuracy and reduction of network traffic by 12 percents