Ant Colony Optimization-Based Location-Aware Routing for Wireless Sensor Networks

  • Authors:

  • Xiaoming Wang;Qiaoliang Li;Naixue Xiong;Yi Pan

  • Affiliations:

  • School of Computer Science, Shaanxi Normal University, Xi'an, China 710062 and Department of Computer Science, Georgia State University, Atlanta, USA 30319;School of Computer Science and Communication, Hunan University, Changsha, China 410082 and Department of Computer Science, Georgia State University, Atlanta, USA 30319;Department of Computer Science, Georgia State University, Atlanta, USA 30319;Department of Computer Science, Georgia State University, Atlanta, USA 30319

  • Venue:
  • WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
  • Year:
  • 2008

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Abstract

The routing for Wireless Sensor Networks (WSNs) is a key and hard problem, and it is a research topic in the field of WSN applications. Based on Ant Colony Optimization (ACO), this paper proposes a novel adaptive intelligent routing scheme for WSNs. Following the proposed scheme, a high performance routing algorithm for WSNs is designed. The proposed routing scheme is very different from the existing ACO based routing schema for WSNs. On one hand, in the proposed scheme, the search range for an ant to select its next-hop node is limited to a subset of the set of the neighbors of the current node. On the other hand, by fusing the residual energy and the global and local location information of nodes, the new probability transition rules for an ant to select its next-hop node are defined. Compared with other ACO based routing algorithms for WSNs, the proposed routing algorithm has a better network performance on aspects of energy consumption, energy efficiency, and packet delivery latency.