TY - GEN
T1 - Kalman filter based dead reckoning algorithm for minimizing network traffic between mobile game users in wireless GRID
AU - Kim, Seong Whan
AU - Ko, Ki Hong
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
KW - Dead reckoning
KW - Kalman filter
KW - Wireless GRID
UR - http://www.scopus.com/inward/record.url?scp=33749572526&partnerID=8YFLogxK
U2 - 10.1007/11801603_9
DO - 10.1007/11801603_9
M3 - Conference contribution
AN - SCOPUS:33749572526
SN - 3540366679
SN - 9783540366676
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 61
EP - 70
BT - PRICAI 2006
PB - Springer Verlag
T2 - 9th Pacific Rim International Conference on Artificial Intelligence
Y2 - 7 August 2006 through 11 August 2006
ER -