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

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.