An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks

Lin, Y., Zhang, J., Chung, H.S.-H., Ip, W.H., Li, Y. and Shi, Y.-H. (2011) An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 42(3), pp. 408-420. (doi: 10.1109/TSMCC.2011.2129570)

Abstract

Maximizing the lifetime of wireless sensor networks (WSNs) is a challenging problem. Although some methods exist to address the problem in homogeneous WSNs, research on this problem in heterogeneous WSNs have progressed at a slow pace. Inspired by the promising performance of ant colony optimization (ACO) to solve combinatorial problems, this paper proposes an ACO-based approach that can maximize the lifetime of heterogeneous WSNs. The methodology is based on finding the maximum number of disjoint connected covers that satisfy both sensing coverage and network connectivity. A construction graph is designed with each vertex denoting the assignment of a device in a subset. Based on pheromone and heuristic information, the ants seek an optimal path on the construction graph to maximize the number of connected covers. The pheromone serves as a metaphor for the search experiences in building connected covers. The heuristic information is used to reflect the desirability of device assignments. A local search procedure is designed to further improve the search efficiency. The proposed approach has been applied to a variety of heterogeneous WSNs. The results show that the approach is effective and efficient in finding high-quality solutions for maximizing the lifetime of heterogeneous WSNs.

• Item Type: Articles
• Keywords: Ant colony optimization (ACO), connectivity, coverage, network lifetime, wireless sensor networks (WSNs)
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Li, Professor Yun
• Authors: Lin, Y., Zhang, J., Chung, H.S.-H., Ip, W.H., Li, Y., and Shi, Y.-H.
• Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering; Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Research Group: Intelligent Systems
• Journal Name: IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
• Publisher: Institute of Electrical and Electronics Engineers
• ISSN: 1094-6977
• ISSN (Online): 1094-6977
• Published Online: 25 April 2011
• Copyright Holders: Copyright © 2011 IEEE
• First Published: First published in IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 42(3):408-420
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher