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PSO Based Clustering for the Optimization of Energy Consumption in Wireless Sensor Network
Emerging Materials Research ( IF 2.2 ) Pub Date : 2020-07-06 , DOI: 20.00107
Naim Karasekreter, Mahmet Akif Şahman, Fatih Başçiftçi, Uğur Fidan

Wireless sensors (Node) are devices with a built-in battery, sensor and communication unit. Wireless sensor network (WSN) are structures that are formed by multiple nodes coming together to transmit the data they collect to each other to the base station. Significant work has been done on WSN in recent years. One of the important issues that these studies focus on is increasing the energy efficiency of the nodes forming the network and ensure their survival for longer. In this study, two-dimensional PSO (TDPSO) has been proposed to solve the problem of clustering in wireless sensor networks by inspiring from Particle Swarm Optimization (PSO) modified by Huilian FAN to solve discrete problems such as traveling salesman problem. The proposed algorithm was analyzed comparatively with the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. As a result, an improvement of 4% compared to LEACH was achieved in terms of the amount of energy left in the network. The data packet sent in 20 rounds was increased by 2000 packets according to LEACH and 27% improvement was achieved. In addition, the number of surviving nodes was increased by 22%.

中文翻译:

基于PSO的聚类优化无线传感器网络能耗。

无线传感器(节点)是具有内置电池,传感器和通信单元的设备。无线传感器网络(WSN)是由多个节点组成的结构,这些节点汇聚在一起将彼此收集的数据传输到基站。近年来,在WSN方面已进行了大量工作。这些研究关注的重要问题之一是提高形成网络的节点的能源效率,并确保其生存期更长。在这项研究中,提出了二维PSO(TDPSO),以范慧莲(Fillian FAN)修改的粒子群优化(PSO)为灵感来解决无线传感器网络中的聚类问题,以解决离散问题,例如旅行商问题。通过低能耗自适应聚类层次结构(LEACH)协议对提出的算法进行了比较分析。结果,就网络中剩余的能量而言,与LEACH相比提高了4%。根据LEACH,在20个回合中发送的数据包增加了2000个数据包,并且实现了27%的改进。此外,存活节点的数量增加了22%。
更新日期:2020-07-06
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