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Swarm Intelligent Compressive Routing in Wireless Sensor Networks
Authors:Saeed Mehrjoo  Abdolhossein Sarrafzadeh  Mehrdad Mehrjoo
Affiliation:1. Department of Computer Engineering, Dariun Branch, Islamic Azad University, Dariun, Iran;2. Unitec Institute of Technology, Auckland, New Zealand;3. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
Abstract:This article proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs swarm intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate. The main contribution of this article is to extend swarm intelligence algorithms to build a routing tree in such a way that it can be utilized to maximize efficiency, thereby rectifying the delay problem of compressive sensing theory and improving the network lifetime. In addition, our approach offers accurate data recovery from small amounts of compressed data. Simulation results show that our approach can effectively extend the network lifetime of a large‐scale wireless sensor network.
Keywords:wireless sensor network  lifetime  compressive sensing theory  particle swarm optimization  artificial bee colony
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