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Trail-Using Ant Behavior Based Energy-Efficient Routing Protocol in Wireless Sensor Networks

Author

Listed:
  • Soon-gyo Jung
  • Byungseok Kang
  • Sanggil Yeoum
  • Hyunseung Choo

Abstract

Swarm Intelligence (SI) observes the collective behavior of social insects and other animal societies. Ant Colony Optimization (ACO) algorithm is one of the popular algorithms in SI. In the last decade, several routing protocols based on ACO algorithm have been developed for Wireless Sensor Networks (WSNs). Such routing protocols are very flexible in distributed system but generate a lot of additional traffic and thus increase communication overhead. This paper proposes a new routing protocol reducing the overhead to provide energy efficiency. The proposed protocol adopts not only the foraging behavior of ant colony but also the trail-using behavior which has never been adopted in routing. By employing the behaviors, the protocol establishes and manages the routing trails energy efficiently in the whole network. Simulation results show that the proposed protocol has low communication overhead and reduces up to 55% energy consumption compared to the existing ACO algorithm.

Suggested Citation

  • Soon-gyo Jung & Byungseok Kang & Sanggil Yeoum & Hyunseung Choo, 2016. "Trail-Using Ant Behavior Based Energy-Efficient Routing Protocol in Wireless Sensor Networks," International Journal of Distributed Sensor Networks, , vol. 12(4), pages 7350427-735, April.
    • Handle: RePEc:sae:intdis:v:12:y:2016:i:4:p:7350427
    DOI: 10.1155/2016/7350427
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    References listed on IDEAS

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    1. Yanwen Wang & Ivan G. Guardiola & Xiaoling Wu, 2014. "RSSI and LQI Data Clustering Techniques to Determine the Number of Nodes in Wireless Sensor Networks," International Journal of Distributed Sensor Networks, , vol. 10(5), pages 380526-3805, May.
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