A Novel Clustering Approach in Wireless Sensor Network Using Genetic Algorithm and Fuzzy Logic

Fatemehzahra Gholami Tirkolaei, Faramarz E. Seraji
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Abstract

Wireless sensor network consists of hundred or thousand sensor nodes that are connected together and work simultaneously to perform some special tasks. The restricted energy of sensor nodes is the main challenge in wireless sensor network as node energy depletion causes node death. Therefore, some techniques should be exerted to reduce energy consumption in these networks. One of the techniques to reduce energy consumptions most effectively is the use of clustering in wireless sensor networks.There are various methods for clustering process, among which LEACH is the most common and popular one. In this method, clusters are formed in a probabilistic manner. Among clustering strategies, applying evolutional algorithm and fuzzy logic simultaneously are rarely taken into account. The main attention of previous works was energy consumption and less attention was paid to delay.In the present proposed method, clusters are constructed by an evolutional algorithm and a fuzzy system such that in addition to a reduction of energy consumption, considerable reduction of delay is also obtained. The simulation results clearly reveal the superiority of the proposed method over other reported approaches.
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基于遗传算法和模糊逻辑的无线传感器网络聚类方法
无线传感器网络由数百或数千个传感器节点组成,这些节点连接在一起,同时工作以执行一些特殊任务。传感器节点能量有限是无线传感器网络面临的主要挑战,节点能量耗尽会导致节点死亡。因此,应该运用一些技术来降低这些网络的能耗。在无线传感器网络中使用聚类技术是最有效地降低能耗的技术之一。聚类的方法有很多种,其中LEACH是最常用的聚类方法。在这种方法中,聚类以概率方式形成。在聚类策略中,进化算法和模糊逻辑同时应用的策略很少。以往的工作主要关注的是能耗,对延迟的关注较少。在本方法中,采用进化算法和模糊系统构建聚类,在降低能耗的同时,也大大降低了延迟。仿真结果清楚地显示了该方法相对于其他已报道的方法的优越性。
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