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.
| Language | English |
|---|---|
| Pages | 408-420 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews |
| Volume | 42 |
| Issue number | 3 |
| Early online date | 25 Apr 2011 |
| DOIs | |
| Publication status | Published - 31 May 2012 |
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Keywords
- ant colony optimization (ACO)
- connectivity
- coverage
- network lifetime
- wireless sensor networks (WSNs)
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An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks. / Lin, Ying; Zhang, Jun; Chung, Henry Shu-Hung; Ip, Wai Hung; Li, Yun; Shi, Yu Hui.
In: IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, Vol. 42, No. 3, 31.05.2012, p. 408-420.Research output: Contribution to journal › Article
TY - JOUR
T1 - An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks
AU - Lin, Ying
AU - Zhang, Jun
AU - Chung, Henry Shu-Hung
AU - Ip, Wai Hung
AU - Li, Yun
AU - Shi, Yu Hui
PY - 2012/5/31
Y1 - 2012/5/31
N2 - 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.
AB - 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.
KW - ant colony optimization (ACO)
KW - connectivity
KW - coverage
KW - network lifetime
KW - wireless sensor networks (WSNs)
UR - http://www.scopus.com/inward/record.url?scp=84860214713&partnerID=8YFLogxK
UR - https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5326
UR - http://eprints.gla.ac.uk/51335/
U2 - 10.1109/TSMCC.2011.2129570
DO - 10.1109/TSMCC.2011.2129570
M3 - Article
VL - 42
SP - 408
EP - 420
JO - IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
T2 - IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
JF - IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
SN - 1094-6977
IS - 3
ER -