Kalman Filter Based Dead Reckoning Algorithm for Minimizing Network Traffic Between Mobile Game Users in Wireless GRID

Abstract

Whereas conventional GRID service is static, wireless GRID supports mobility, and it should maintain geographic position to support efficient resource sharing and routing. When the devices 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 and network congestion. To minimize the network traffic between mobile users, we can use dead reckoning (DR) 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 DR algorithm, we propose Kalman filter based DR approach, and we also propose the adaptive Kalman gain control to minimize the number of UPDATE packet to distant device. 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.