一种改进的LEACH-MF协议延长无线传感器网络的生存期

Sweety Sharma, N. Mittal
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引用次数: 6

摘要

无线传感器网络(WSN)通信以其无线数据传输能力强等特点受到了研究学者的广泛关注。为了实现高效节能的网络,迄今为止已经开发了大量的技术。聚类和簇头选择是网络中最主要也是最困难的任务。LEACH是其他节能聚类协议的基础。本研究将leach -移动模糊(LEACH-MF)作为开展所提出工作的基础。本文开发了基于LEACH的模糊推理系统(FIS)和基于阈值的数据传输概念。本工作的主要目的是有效地利用分配给传感器节点的能量。该模型分为两种形式,即修改参数-浸出- mf (MP-LEACH-MF)和有限通信-浸出- mf (LC-LEACH-MF)。LC-LEACH-MF是一种反应性协议,而LC-LEACH-MF是一种周期性协议。为了保证所提工作的性能效率,评估了网络的包传送率(PDR)、最后节点死亡(LND)、半节点死亡(HND)、第一节点死亡(FND)、网络能耗等参数,并与传统LEACH、LEACH- mobile (LEACH- m)、LEACH- mf进行了比较分析。通过对所得结果的分析,得出了LC-LEACH-MF优于其他传统的节能聚类技术的结论。
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An Improved LEACH-MF Protocol to Prolong Lifetime of Wireless Sensor Networks
Wireless sensor network (WSN) communication has gathered a lot of attention of research scholars due to its various features such as high wireless data transmission. A large number of techniques have been developed till now in order to achieve an energy efficient network. The clustering and cluster head selection is the major and difficult task to perform in a network. LEACH serves as a basic for rest of the energy efficient clustering protocols. This study considers the LEACH-Mobile Fuzzy (LEACH-MF) as base for developing the proposed work. Fuzzy Inference System (FIS) with LEACH along with threshold based data transmission concept is developed in this work. The major objective of this work is to utilize the allotted energy to sensor nodes in an effective way. The proposed model is parted in two forms i.e. Modified Parameter-LEACH-MF (MP-LEACH-MF) and Limited Communication-LEACH-MF (LC-LEACH-MF). LC-LEACH-MF is a reactive protocol whereas the former one is periodic. In order to assure the performance efficiency of the proposed work, the parameters such as Packet Delivery Ratio (PDR), Last Node Dead (LND), Half Node Dead (HND), First Node Dead (FND), Energy Consumption of the network are evaluated and along with this a comparison analysis has been done with traditional LEACH, LEACH–Mobile (LEACH-M), LEACH-MF. After analyzing the obtained results it is concluded that the LC-LEACH-MF outnumbers the rest of the traditional energy efficient clustering techniques.
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