移动群智网中基于粒子群寻优和距离协作判别的数据收集研究

摘要

This paper proposed a data collection mechanism based on the particle swarm optimization and distance cooperation for the real-time performance and reliability of data collection.Based on spatio-temporal sensing region,the mechanism de-fined with high accuracy and adaptation of particle swarm optimization model,combined with two-dimensional normal distribu-tion based on the time series method was used to determine the perception of data source distance collaborative decision mecha-nism,incentive user mobile nodes to actively participate in the cooperation communication,and put forward the applicable to mobile swarm intelligent network application data collection mechanism.The results of simulation experiments show that the proposed data collection system has advantages in the aspects of network survivability,transmission delay,and the survival a-bility of mobile nodes and energy consumption.%针对移动群智网应用对数据收集的实时性和可靠性要求，提出了一种基于粒子群寻优和距离协作判别的数据收集机制。该机制基于时空二维感知区域定义了具有高精度和适应度的粒子群寻优模型，结合二维正态分布基于时间序列给出了用于判断感知数据源的距离协作判别机制，激励用户移动节点积极加入到协作通信，从而提出了适用于移动群智网应用的数据收集机制。仿真实验结果表明，所提出的数据收集机制在网络生存能力、传输延迟、移动节点存活能力和能耗等方面表现优越。