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Research and improvement of cluster algorithm in wireless sensor network

Author: WuWei
Tutor: FanChunLi
School: Nanjing University of Technology and Engineering
Course: Applied Computer Technology
Keywords: Wireless Sensor Networks Clustering Nodes LEACH Energy Location
CLC: TN929.5
Type: Master's thesis
Year: 2013
Downloads: 83
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Abstract


WSN is short for Wireless Sensor Networks. It is the self-organization and distributed network system. It is constituted by a micro-sensor. The micro-sensor has wireless communication capacity and computing capacity. It can autonomously complete tasks depending on the specific environment in unmanned cases. In recent years, wireless technology and portable computers have rapidly developed and the consequent WSN has become a focus for researchers. WSN has bright application prospects.WSN does not need a fixed network support. It has some characteristics different from the traditional networks, such as limited energy of the node, less computing power and finite communication bandwidth. Many routing algorithms are not suitable for WSN. The routing problem is the research focus in WSN. In all the routing problems, the clustering algorithm came in the first place.This paper studies the clustering algorithm based on node residual energy and location information and other related issues, including the following aspects:First, this paper studies the topology control of WSN including power control and sleep scheduling, analyses the existing hierarchical topology control and leads to the most basic clustering algorithm-LEACH. This paper studies the work process of LEACH, simulates the performance, and analyses the characteristics and shortcomings of the algorithm. Then, this paper presents the improved clustering algorithm based on node residual energy and location. The improved clustering algorithm is LEACH-EL, short for Leach based on Energy and Location. LEACH-EL changes the cluster head election algorithm to reduce the energy consumption of network and to extend the lifetime of network. Finally, the simulation compares the performance of two algorithms. This paper verifies the feasibility of the improved algorithm.

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