Improving the Network Lifetime in Wireless Sensor Network for Internet of Thing Applications

A. A. Salman, Zainab T. Alisa
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引用次数: 3

Abstract

Mobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kernel-based fuzzy C-means clustering algorithm (KFCM) is adopted to cluster sensor nodes, while a cluster head (CH) is selected for each cluster based on a fuzzy logic system. Results depicts that the new work performs better than the existing algorithms (as Low Energy Adaptive Cluster Hierarchy-Mobile (LEACH-M) and Low Energy Adaptive Cluster Hierarchy-Mobile Enhancement (LEACH-ME)) in terms of network lifetime, energy consumption, packet transmission and stability period.
面向物联网应用的无线传感器网络寿命改进
移动无线传感器网络由于能够在多个领域提供良好的解决方案和低廉的价格,最近引起了人们的极大兴趣。物联网(IoT)连接了不同的技术,如传感、通信、网络和云计算。它可用于监控、医疗保健和智慧城市。最适合物联网应用的基础设施是无线传感器网络。无线传感器网络的主要缺点之一是传感器节点的功率限制。聚类模型是一种消除被测数据在传输到中心点基站(Base Station, BS)过程中产生的激励功率的实际方法。本文提出了有效的集群协议来延长网络的生存期。采用基于核的模糊c均值聚类算法(KFCM)对传感器节点进行聚类,并基于模糊逻辑系统为每个聚类选择一个簇头(CH)。结果表明,新算法在网络寿命、能耗、数据包传输和稳定周期等方面优于现有的低能量自适应簇层次移动算法(LEACH-M)和低能量自适应簇层次移动增强算法(LEACH-ME)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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