Market-based Adaptive Task Scheduling for Sensor Networks
This paper designs a microeconomic system for task scheduling in wireless sensor networks by virtue of the migration of mobile agents. Further, it proposes a market-based adaptive task scheduling algorithm, named MATS, which schedules tasks to the set of optimal nodes by adjusting the energy price of nodes and modifying the nodes’ roles. The simulation in the scenario of target tracking demonstrates that MATS is adaptable to the changing network conditions and realizes an efficient allocation of energy resources by regulating the energy consumption of nodes. Compared with the static scheduling algorithm, MATS impressively promotes the energy efficiency at the trivial cost of tracking accuracy.
Sensor networks task scheduling market mechanism mobile agent
Wang Zhe Yan Yujie Jia Peng Wang Shu
Department of Electronics and Information Engineering,Huazhong University of Science and Technology
国际会议
武汉
英文
2006-09-01（万方平台首次上网日期，不代表论文的发表时间）