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Ant Colony Optimization Algorithm for Lifetime Maximization in Wireless Sensor Network with Mobile Sink

Authors
Zhong, Jing-huiZhang, Jun
Issue Date
Jul-2012
Publisher
ASSOC COMPUTING MACHINERY
Keywords
Ant colony optimization; Lifetime maximization; Mobile sink scheduling; Wireless sensor network
Citation
GECCO '12: Proceedings of the 14th annual conference on Genetic and evolutionary computation, pp 1199 - 1204
Pages
6
Indexed
SCIE
SCOPUS
Journal Title
GECCO '12: Proceedings of the 14th annual conference on Genetic and evolutionary computation
Start Page
1199
End Page
1204
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/116115
DOI
10.1145/2330163.2330328
Abstract
In wireless sensor networks (WSNs), sensors near the sink can be burdened with a large amount of traffic, because they have to transmit data generated by themselves and those far away from the sink. Hence the sensors near the sink would deplete their energy much faster than the others, which results in a short network lifetime. Using mobile sink is an effective way to tackle this issue. This paper explores the problem of determining the optimal movements of the mobile sink to maximize the network lifetime. A novel ant colony optimization algorithm (ACO), namely the ACO-MSS, is developed to solve the problem. The proposed ACO-MSS takes advantage of the global search ability of ACO and adopts effective heuristic information to find a near globally optimal solution. Multiple practical factors such as the forbidden regions and the maximum moving distance of the sink are taken into account to facilitate the real applications. The proposed ACO-MSS is validated by a series of simulations on WSNs with different characteristics. The simulation results demonstrate the effectiveness of the proposed algorithms.
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COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles

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ZHANG, Jun
ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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