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基于 PSO 算法的改进分簇路由协议在异构无线传感器网络中的应用。

An Improved Routing Schema with Special Clustering Using PSO Algorithm for Heterogeneous Wireless Sensor Network.

机构信息

Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, School of Computer & Communication Engineering, Changsha University of Science & Technology, Changsha 410000, China.

College of Information Engineering, Yangzhou University, Yangzhou 225000, China.

出版信息

Sensors (Basel). 2019 Feb 7;19(3):671. doi: 10.3390/s19030671.

Abstract

Energy efficiency and energy balancing are crucial research issues as per routing protocol designing for self-organized wireless sensor networks (WSNs). Many literatures used the clustering algorithm to achieve energy efficiency and energy balancing, however, there are usually energy holes near the cluster heads (CHs) because of the heavy burden of forwarding. As the clustering problem in lossy WSNs is proved to be a NP-hard problem, many metaheuristic algorithms are utilized to solve the problem. In this paper, a special clustering method called Energy Centers Searching using Particle Swarm Optimization (EC-PSO) is presented to avoid these energy holes and search energy centers for CHs selection. During the first period, the CHs are elected using geometric method. After the energy of the network is heterogeneous, EC-PSO is adopted for clustering. Energy centers are searched using an improved PSO algorithm and nodes close to the energy center are elected as CHs. Additionally, a protection mechanism is also used to prevent low energy nodes from being the forwarder and a mobile data collector is introduced to gather the data. We conduct numerous simulations to illustrate that our presented EC-PSO outperforms than some similar works in terms of network lifetime enhancement and energy utilization ratio.

摘要

能源效率和能量平衡是自组织无线传感器网络(WSNs)路由协议设计的关键研究问题。许多文献使用聚类算法来实现能量效率和能量平衡,但是由于转发的负担较重,通常在簇头(CH)附近会出现能量空洞。由于有损 WSN 中的聚类问题被证明是 NP 难问题,因此许多元启发式算法被用于解决该问题。在本文中,提出了一种特殊的聚类方法,称为使用粒子群优化的能量中心搜索(EC-PSO),以避免这些能量空洞并搜索 CH 选择的能量中心。在第一个阶段,使用几何方法选举 CH。在网络能量异质后,采用 EC-PSO 进行聚类。使用改进的 PSO 算法搜索能量中心,并选择靠近能量中心的节点作为 CH。此外,还使用了一种保护机制来防止低能量节点成为转发器,并引入了移动数据收集器来收集数据。我们进行了大量的模拟实验,结果表明,与一些类似的工作相比,我们提出的 EC-PSO 在网络寿命延长和能量利用率方面表现更好。

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