Adaptation of Sampling in Target Tracking Sensor Networks
Sampling is one of the most common and repeated tasks in a target tracking sensor network. However, tuning the sampling rate parameter can be a challenging issue considering all the sensor network restrictions. In this paper, we propose two adaptive sampling algorithms in a target tracking sensor network while considering a multi-objective fitness function. The restrictions used as objective functions are energy consumption and prediction error which provide a direct feedback to the sampling rate adaptation algorithms. We support our proposed methods with well structured experimental evaluations.
Sensor Networks Target Tracking Adaptive Sampling Evolutionary Strategy Reinforcement Learning
Mohammad Rahimi Reza Safabakhsh
Computer Engineering Department Amirkabir University of Technology Tehran, Iran
国际会议
北京
英文
1-5
2010-06-25（万方平台首次上网日期，不代表论文的发表时间）