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Swarm intelligent compressive routing in wireless sensor networks

Mehrjoo, S ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1111/coin.12038
  3. Publisher: Blackwell Publishing Inc , 2015
  4. Abstract:
  5. 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
  6. Keywords:
  7. Artificial bee colony ; Compressive sensing theory ; Particle swarm optimization ; Wireless sensor network ; Artificial intelligence ; Compressed sensing ; Evolutionary algorithms ; Forestry ; Network routing ; Particle swarm optimization (PSO) ; Signal reconstruction ; Trees (mathematics) ; Artificial bee colonies ; Communication rate ; Compressive sensing ; Large-scale wireless sensor networks ; lifetime ; Network lifetime ; Swarm intelligence algorithms ; Swarm intelligent ; Wireless sensor networks ; Algorithms ; Optimization ; Problem Solving ; Telecommunications
  8. Source: Computational Intelligence ; Volume 31, Issue 3 , 2015 , Pages 513-531 ; 08247935 (ISSN)
  9. URL: http://onlinelibrary.wiley.com/doi/10.1111/coin.12038/abstract