摘要
针对任务在各执行器的协作问题,提出一种动态调度策略,根据执行器节点的剩余能量和工作状态,利用混合模拟退火的微粒群算法,在任务时效期内,统一安排各任务在执行器上的执行周期,最小化最大完成时间.仿真结果表明,算法具有良好的收敛性能,各执行器的任务完成响应时间和能耗均衡情况均得到改善.
A dynamic task scheduling approach based on particle swarm optimization（PSO） and simulated annealing（SA） technique for wireless sensor and actuator networks is proposed to solve the execution problem of tasks collaboratively among actuators.The purpose of approach is minimizing the maximum response time in the actuators subject to residual energy constraints and schedule execution period of each task operation within given time.Simulation results have shown that the proposed hybrid approach is of high convergence speed and good performance between task response time and balancing the energy dissipation among actuators.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2010年第6期1239-1244,共6页
Acta Electronica Sinica
基金
国家863计划项目(No.2006AA780201-2)
科技部国际科技合作项目资助(No.2007DFR10420)
关键词
无线传感器/执行器网络
任务调度
微粒群算法
模拟退火算法
wireless sensor and actuator network
task scheduling
particle swarm optimization
simulated annealing
