Energy-efficient Positioning of Cluster Heads in Wireless Sensor Networks
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
As one of the most important requirements for wireless sensor networks, prolonging network lifetime can be realized by minimizing energy consumption in cluster heads as well as sensor nodes. While most of the previous researches have focused on the energy of sensor nodes, we devote our attention to cluster heads because they are most dominant source of power consumption in the cluster-based sensor networks. Therefore, we seek to minimize energy consumption by minimizing the maximum(MINMAX) energy dissipation at each cluster heads. This work requires energy-efficient clustering of the sensor nodes while satisfying given energy constraints. In this paper, we present a constraint satisfaction modeling of cluster-based routing in a heterogeneous sensor networks because mixed integer programming cannot provide solutions to this MINMAX problem. Computational experiments show that substantial energy savings can be obtained with the MINMAX algorithm in comparison with a minimum total energy(MTE) strategy.
Abstract
As one of the most important requirements for wireless sensor networks, prolonging network lifetime can be realized by minimizing energy consumption in cluster heads as well as sensor nodes. While most of the previous researches have focused on the energy of sensor nodes, we devote our attention to cluster heads because they are most dominant source of power consumption in the cluster-based sensor networks. Therefore, we seek to minimize energy consumption by minimizing the maximum(MINMAX) energy dissipation at each cluster heads. This work requires energy-efficient clustering of the sensor nodes while satisfying given energy constraints. In this paper, we present a constraint satisfaction modeling of cluster-based routing in a heterogeneous sensor networks because mixed integer programming cannot provide solutions to this MINMAX problem. Computational experiments show that substantial energy savings can be obtained with the MINMAX algorithm in comparison with a minimum total energy(MTE) strategy.
참고문헌 (18)
- W.B. Heinzelman, "An Application-Specific Protocol Architecture for Wireless Microsensor Networks", IEEE Trans. on Wireless Communications, 1(4), pp.660~670 (2002)
- O. Younis, "Distributed Clustering in Ad-hoc Sensor Networks: A Hybrid, Energy-Efficient Approach", INFOCOM 2004 (2004)
- A. Manjeshwar, "TEEN: A Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks", IPDPS 2001 (2001)
- S. Lindsey, "Data Gathering Algorithms in Sensor Networks Using Energy Metrics", IEEE Trans. Parallel and Distributed Systems, 13(9), pp.924~935 (2002)
- D. Culler, "Introduction: Overview of Sensor Networks", IEEE Computer, pp.41~49 (2004)
- P.K. Agarwal, "Exact and Approximation Algorithms for Clustering", Symposium on Discrete Algorithms (1997)
- J.H. Chang, "Maximum Lifetime Routing in Wireless Sensor Networks", IEEE, 2004, pp.12(4), 609~619
- S. Ghiasi, "Optimal Energy Aware Clustering in Sensor Networks", Sensors 2002-2, pp.258~269 (2002)
- C. Chiasserini, "An Energy-Efficient Method for Nodes Assignment in Cluster-Based Ad Hoc Networks", pp.223~231 (2004), Wireless Networks 10
- J. Ai, "A Cluster-based Energy Balancing Scheme in Heterogeneous Wireless Sensor Networks", ICN2005 (2005), Lecture Notes in Computer Science 3420
- M. Younis, "Optimization of Task Allocation in a Cluster-Based Sensor Network", IEEE Int'l Symposium on Computers and Communication (2003)
- I. Kang, "Maximizing Network Lifetime of Broadcasting Over Wireless Stationary Ad Hoc Networks", Mobile Networks and Applications 10, pp.879~896 (2005), Springer Science
- T. Rappaport, "Wireless Communications: Principles & Practice" (1996), Prentice-Hall
- S. Sohn, "Optimization of Base Stations Positioning in Mobile Networks", ICCSA2006 (2006), Lecture Notes in Computer Science 3981
- S.C. Brailsford, "Constraint Satisfaction Problems: Algorithms and Applications", Europian Journal of Operational Research, 119, pp.557~581 (1999)
- R. Bejar, "Sensor Networks and Distributed CSP: Communication, Computation and Complexity", Artificial Intelligence, 161, pp.117~147 (2005)
- M. Sun, "Solving the Uncapacitated Facility Location Problem Using Tabu Search", Computers & Operations Research, 33, pp.2563~2589 (2006)
- P.V. Hentenryck, "Search and Strategies in OPL", ACM Transactions on Computational Logic, 1(2), pp.285~320 (2000)