计算机应用 ›› 2012, Vol. 32 ›› Issue (04): 913-916.

• 网络与通信 • 上一篇    下一篇

基于0-1规划的异构传感器网络任务分配策略

蒋志强1,廖晓峰2,刘群1   

  1. 1. 重庆邮电大学 计算机科学与技术学院,重庆 400065
    2. 重庆大学 计算机学院,重庆 401331
  • 收稿日期:2011-09-21 修回日期:2011-12-02 发布日期:2012-04-20 出版日期:2012-04-01
  • 通讯作者: 蒋志强
  • 作者简介:蒋志强(1984-),男,江西景德镇人,硕士研究生,主要研究方向:无线传感器网络资源优化;廖晓峰(1964-),男,四川成都人,教授,博士生导师,博士,主要研究方向:人工神经网络、混沌控制与同步;刘群(1969-),女,江西南昌人,教授,博士,主要研究方向:计算机仿真、多媒体信息处理、人工智能。
  • 基金资助:
    国家自然科学基金资助项目;重庆市自然科学基金资助项目;博士启动资金资助项目

Task allocation strategy in heterogeneous wireless sensor networks based on 0-1 programming

JIANG Zhi-qiang1,LIAO Xiao-feng2,LIU Qun1   

  1. 1. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    2. College of Computer Science, Chongqing University, Chongqing 401331, China
  • Received:2011-09-21 Revised:2011-12-02 Online:2012-04-20 Published:2012-04-01
  • Contact: JIANG Zhi-qiang

摘要: 为了减少无线传感器网络节点处理任务的总体能耗、均衡网络节点的剩余能量以及减少网络中任务的调度时间,提出一种三目标任务分配算法。利用0-1非线性规划理论建立问题的代价函数,用能量方差表征节点处理任务后的剩余能量均衡度,并结合离散粒子群优化算法(DPSO),以最小化代价函数为优化目的,从而得出经优化的任务分配策略。仿真实验表明基于0-1规划的任务分配策略能有效地减少网络总体能耗,均衡网络节点剩余能量(延长网络寿命)以及减少任务调度时间。

关键词: 无线传感器网络, 0-1规划, 任务分配, 任务图, 离散粒子群算法

Abstract: In order to reduce total energy consumption for processing task in Wireless Sensor Network (WSN), balance the residual energy of nodes and decrease the time of task scheduling, a task allocation algorithm for three targets was proposed. Cost function was built with the theory of 0-1 nonlinear programming and energy variance was utilized to show equilibrium degree of residual energy of nodes. Discrete Particle Swarm Optimization (DPSO) was used to solve cost function to obtain minimum and get optimized task allocation strategy. The simulation results verify that the task allocation strategy based on 0-1 programming with DPSO could decrease the energy consumption efficiently, balance the residual energy of nodes and reduce the time of task scheduling.

Key words: Wireless Sensor Network (WSN), 0-1 programming, task allocation, task graph, Discrete Particle Swarm Optimization (DPSO) algorithm