TY - GEN
T1 - Mobility profiling using Markov chains for tree-based object tracking in wireless sensor networks
AU - Yen, Li-Hsing
AU - Yang, Chia Cheng
PY - 2006/12/15
Y1 - 2006/12/15
N2 - Object tracking in wireless sensor networks is to track moving objects by scattered sensors. These sensors are typically organized into a tree to deliver report messages upon detecting object's move. Existing tree construction algorithms all require a mobility profile that is obtained based on historical statistics. In this paper, we propose an analytic estimate of such mobility profile based on Markov-chain model. This estimate replaces otherwise experimental process that collects statistical data. Simulation results confirm the effectiveness of the proposed approach.
AB - Object tracking in wireless sensor networks is to track moving objects by scattered sensors. These sensors are typically organized into a tree to deliver report messages upon detecting object's move. Existing tree construction algorithms all require a mobility profile that is obtained based on historical statistics. In this paper, we propose an analytic estimate of such mobility profile based on Markov-chain model. This estimate replaces otherwise experimental process that collects statistical data. Simulation results confirm the effectiveness of the proposed approach.
UR - http://www.scopus.com/inward/record.url?scp=33845439008&partnerID=8YFLogxK
U2 - 10.1109/SUTC.2006.92
DO - 10.1109/SUTC.2006.92
M3 - Conference contribution
AN - SCOPUS:33845439008
SN - 0769525539
SN - 9780769525532
T3 - Proceedings - IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing
SP - 220
EP - 225
BT - Proceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006
T2 - IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing
Y2 - 5 June 2006 through 7 June 2006
ER -