Volume 9 Number 10 (Oct. 2014)
Home > Archive > 2014 > Volume 9 Number 10 (Oct. 2014) >
JSW 2014 Vol.9(10): 2758-2763 ISSN: 1796-217X
doi: 10.4304/jsw.9.10.2758-2763

An Energy Efficient Routing Based on Swarm Intelligence for Wireless Sensor Networks

Yong Lv

College of Mechanical and Electrical Engineering Jiaxing University, Zhejiang Province, China

Abstract—Wireless Sensor Networks are characterized by having specific requirements such as limited power, memory and functionality to support communications. In sensor networks, minimization of energy consumption is considered a major performance criterion to provide maximum network lifetime. Traditional routing protocols do not take into account that a node contains only a limited energy supply. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the Ant colony based meta heuristic, with a novel variation of Reinforcement learning for Wireless Sensor Networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence based optimization. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that ARNet can obviously improve adaptability and effectively reduce the average energy consumption compared with the traditional EEABR algorithm.

Index Terms—wireless sensor networks, routing, swarm intelligence

[PDF]

Cite: Yong Lv, "An Energy Efficient Routing Based on Swarm Intelligence for Wireless Sensor Networks," Journal of Software vol. 9, no. 10, pp. 2758-2763, 2014.

General Information

  • ISSN: 1796-217X (Online)

  • Abbreviated Title: J. Softw.

  • Frequency:  Quarterly

  • APC: 500USD

  • DOI: 10.17706/JSW

  • Editor-in-Chief: Prof. Antanas Verikas

  • Executive Editor: Ms. Cecilia Xie

  • Abstracting/ Indexing: DBLP, EBSCO,
           CNKIGoogle Scholar, ProQuest,
           INSPEC(IET), ULRICH's Periodicals
           Directory, WorldCat, etc

  • E-mail: jsweditorialoffice@gmail.com

  • Jun 12, 2024 News!

    Vol 19, No 2 has been published with online version   [Click]

  • Jan 04, 2024 News!

    JSW will adopt Article-by-Article Work Flow

  • Apr 01, 2024 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Apr 01, 2024 News!

    Papers published in JSW Vol 18, No 1- Vol 18, No 6 have been indexed by DBLP   [Click]

  • Mar 01, 2024 News!

    Vol 19, No 1 has been published with online version    [Click]