A novel approach for particle swarm optimization‐based clustering with dual sink mobility in wireless sensor network,International Journal of Communication Systems

当前位置： X-MOL 学术 › Int. J. Commun. Syst. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

A novel approach for particle swarm optimization‐based clustering with dual sink mobility in wireless sensor network
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2020-08-23 , DOI: 10.1002/dac.4553
Supreet Kaur ₁ , Vinit Grewal ₁

Affiliation

The proliferation in the sensing technology in wireless sensor network has left an everlasting impact to revolutionize every sector of human's lives. The limited battery of sensor nodes (SNs) has generated a tremendous challenge for the researchers to ameliorate the network's life span. To pacify this concern, in this paper, we have proposed a particle swarm optimization (PSO)‐based dual sink mobility (PSODSM) technique to reduce the energy expenditure of the SNs. PSODSM has the paramount focus on the cluster head (CH) selection based on integration of crucial factors: “ratio of remaining energy to the initial energy,” node degree, node centrality, separation factor between the SN and the sink, CH number, and energy consumption rate. As soon as the CHs are selected, two sinks placed opposite to each other are made to move towards the selected CHs for data collection. The most prominent fact is the movement of sinks which is done outside the periphery of the network to collect data rather than the reported conventional research works that employ sink mobility inside the network. Extensive simulations are performed to examine the empirical evaluation of PSODSM based on the benchmark of different performance metrics. The performance validation of PSODSM is done against the other meta‐heuristic algorithms, and findings show that the PSODSM outperforms the competitive algorithms and is also found to be scalable pertaining to real time implementation.

中文翻译：

无线传感器网络中具有双接收器移动性的基于粒子群优化的新型聚类方法

无线传感器网络中传感技术的迅猛发展给人类生活的各个领域带来了深远的影响。有限的传感器节点（SN）电池为研究人员改善网络寿命提供了巨大的挑战。为了解决这一问题，在本文中，我们提出了一种基于粒子群优化（PSO）的双池迁移率（PSODSM）技术，以减少SN的能量消耗。PSODSM最重要的是基于以下关键因素的集成来选择簇头（CH）：“剩余能量与初始能量之比”，节点度，节点中心度，SN与汇之间的分离因子，CH数量和能源消耗率。一旦选择了CH，使两个彼此相对放置的接收器向选定的CH移动，以进行数据收集。最突出的事实是汇的移动是在网络外围进行的，以收集数据，而不是报道的采用网络内部汇移动性的传统研究工作。基于不同性能指标的基准，进行了广泛的仿真以检查PSODSM的经验评估。PSODSM的性能验证是针对其他元启发式算法进行的，结果表明PSODSM优于竞争算法，并且在实时实施方面具有可扩展性。最突出的事实是汇的移动是在网络外围进行以收集数据，而不是已报道的采用网络内部汇移动的传统研究工作。基于不同性能指标的基准，进行了广泛的仿真以检查PSODSM的经验评估。PSODSM的性能验证是针对其他元启发式算法进行的，结果表明PSODSM优于竞争算法，并且在实时实施方面具有可扩展性。最突出的事实是汇的移动是在网络外围进行的，以收集数据，而不是报道的采用网络内部汇移动性的传统研究工作。基于不同性能指标的基准，进行了广泛的仿真以检查PSODSM的经验评估。PSODSM的性能验证是针对其他元启发式算法进行的，结果表明PSODSM优于竞争算法，并且在实时实施方面具有可扩展性。

更新日期：2020-10-05

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11