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基于竞争群体优化算法的信息物理系统中的网关部署算法

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

作者信息

Huang Shuqiang, Tao Ming

机构信息

Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, China.

College of Computer and Network Security, Dongguan University of Technology, Dongguan 523808, China.

出版信息

Sensors (Basel). 2017 Jan 22;17(1):209. doi: 10.3390/s17010209.

Abstract

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric -center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

摘要

无线传感器网络拓扑优化是一个非常重要的问题,通过节点选择进行拓扑控制可以提高数据转发效率,同时节省能量并延长网络寿命。为了解决在信息物理系统中将无线传感器网络连接到互联网的问题,在此我们提出一种基于竞争群体优化器算法的几何网关部署方法。粒子群优化(PSO)算法在解空间中具有连续搜索特性,这使其适合于寻找网关部署的几何中心;然而,其搜索机制局限于个体最优(pbest)和群体最优(gbest);因此,它很容易陷入局部最优。为了改进粒子搜索机制并提高算法的搜索效率,我们引入了一种新的竞争群体优化(CSO)算法。CSO搜索算法基于粒子间竞争机制,能够有效避免群体陷入局部最优。随着基于自适应反对搜索的改进及其动态参数调整能力,该算法可以保持整个群体的多样性以解决几何中心网关部署问题。仿真结果表明,这种CSO算法具有良好的全局探索能力以及收敛速度,并且通过获得最小网络覆盖半径可以提高信息物理系统的网络服务质量(QoS)水平。我们还发现,与PSO或Kmedoids算法相比,CSO算法在解决几何网关部署问题时更稳定、更健壮且更有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32f5/5298780/afd9e1de68f5/sensors-17-00209-g001.jpg

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