移动感知器网络中基于随机游走和协作关系的任务分发算法

Task Distribution Algorithm Based on Random Walk and Cooperative Relationship in Mobile Sensor Networks

关于移动感知器网络中感知任务的分发问题,目前学术界已经有了诸多相关研究.然而,这些研究很少涉及到多个智能体协作完成复杂感知任务问题.针对这种情况,首先,通过分析移动感知器网络的结构特征、智能体相互之间、以及智能体和感知任务之间的关系,本文提出了智能体之间协作关系强度和智能体对感知任务适应度两个概念,并讨论了二者对于移动感知器网络中感知任务动态分发的作用.其次,在上述概念的基础上,将二者融合为偏好因子,提出了基于随机游走和协作关系的任务分发算法(TDCR,Task Distribution With Cooperative Relationship),通过该算法达到提高任务分发效率的目的.最后,将TDCR与Personal Rank算法(PR)、HITS算法对比分析,表明所提出的算法TDCR在任务分发效率和准确度等性能指标上有较好的提升.

There have been many studies on the distribution of sensing tasks in mobile sensor networks.However,these studies rarely involve the problem that many agents in a mobile sensor network cooperate to perform complex sensing tasks.In order to address this challenge,first,we combined the structural characteristics of mobile sensor networks,the relationship between agents,and the relationship between agents and sensing tasks.Then we proposed the strength of cooperation between agents and the fitness of agents to sensing tasks,and discussed their roles in the dynamic distribution of sensing tasks in mobile sensor networks.Second,based on the above concepts,the two were unified as preference factors.In order to achieve the goal of improving task distribution efficiency,a task distribution algorithm based on random walk and cooperative relationship was proposed.At last,the comparison with the Personal Rank(PR)algorithm and HITS algorithm shows that the proposed algorithm has superiority in task distribution efficiency and accuracy.