Modified Clustering Algorithm for Energy Efficiency Utilizing Fuzzy Logic in WSN (MCF)

Q4 Computer Science
Tuba Firdaus, Meenakshi Yadav
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引用次数: 1

Abstract

A number of research have taken place in the field of Wireless Sensor Networks (WSN) as there is continuous need of advancement in the field of wireless communication, digital technology and micro-electro-mechanical systems(MEMS) . So the need of growth of low cost, low power, multifunctional sensor nodes have been required. A Wireless Sensor Network is a collection of sensor nodes that have the capability of sensing any environmental phenomenon, processing that information and then sending that data to the base station. A single sensor node is not capable of capturing desired information from a particular region so a collection of nodes are arranged to get accurate and sufficient result. This collection of sensor nodes along with a base station will collaboratively form a network that is known as Wireless Sensor Network. As limited energy is one of the most important constraint of WSN so it must be assured that it is utilized in most efficient way. Clustering is best approach to remove redundant data transmission to base station. Each cluster has a cluster head that is responsible for transmitting data to base station for that cluster members. Cluster head (CH) collect the data from all members of its cluster and perform aggregation on these data to remove redundancy then send it to base station. So appropriate CH election is very important for improving efficiency. In this thesis we have presented a clustering approach that has taken a heterogeneous environment and uses fuzzy logic to elect CHs more efficiently. We have combined two parameters Distance and Residual Energy and apply fuzzy rules on that to find the priority of a node for being a CH. Simulation shows that using fuzzy logic in SEP (Stability Election Protocol) will improve the energy efficiency by providing better load distribution and utilizing the benefits of heterogeneity of network. We have shown our analysis on two parameters- Number of dead nodes and average energy of nodes
基于模糊逻辑的WSN能效改进聚类算法(MCF)
随着无线通信、数字技术和微机电系统(MEMS)领域的不断发展,无线传感器网络(WSN)领域的研究也越来越多。因此,低成本、低功耗、多功能传感器节点的发展需求已经被提出。无线传感器网络是一组传感器节点的集合,这些节点具有感知任何环境现象的能力,处理这些信息,然后将这些数据发送到基站。单个传感器节点无法从特定区域捕获所需信息,因此需要安排节点集合以获得准确和充分的结果。这些传感器节点的集合与基站将协同形成一个网络,称为无线传感器网络。有限的能量是无线传感器网络最重要的制约因素之一,因此必须保证其得到最有效的利用。集群是消除基站冗余数据传输的最佳方法。每个集群都有一个集群头,负责将数据传输到该集群成员的基站。集群头(CH)从其集群的所有成员中收集数据,并对这些数据进行聚合以消除冗余,然后将其发送到基站。因此,适当的CH选择对于提高效率非常重要。在本文中,我们提出了一种采用异构环境并使用模糊逻辑更有效地选择CHs的聚类方法。我们结合了距离和剩余能量两个参数,并对其应用模糊规则来确定节点作为CH的优先级。仿真表明,在SEP (Stability Election Protocol)中使用模糊逻辑可以通过提供更好的负载分配和利用网络异构性的好处来提高能量效率。我们对两个参数——死节点数和节点平均能量进行了分析
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来源期刊
International Journal of Computer Science and Applications
International Journal of Computer Science and Applications Computer Science-Computer Science Applications
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期刊介绍: IJCSA is an international forum for scientists and engineers involved in computer science and its applications to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the IJCSA are selected through rigorous peer review to ensure originality, timeliness, relevance, and readability.
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