A new interpretation of schema notation that overturns the binary encoding constraint
Proceedings of the third international conference on Genetic algorithms
Applying tabu search to the job-shop scheduling problem
Annals of Operations Research - Special issue on Tabu search
Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Time synchronization in ad hoc networks
MobiHoc '01 Proceedings of the 2nd ACM international symposium on Mobile ad hoc networking & computing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Energy-Aware Routing in Cluster-Based Sensor Networks
MASCOTS '02 Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Medium access control with coordinated adaptive sleeping for wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Protocols and Architectures for Wireless Sensor Networks
Protocols and Architectures for Wireless Sensor Networks
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
| Hi-index | 0.00 |
The channel scheduling problem is to decide how to commit channels for transmitting data between nodes in wireless networks. This problem is one of the most important problems in wireless sensor networks. In this problem, we aim to obtain a near-optimal solution with the minimal energy consumption within a reasonable time. As the number of nodes increases in the network, however, the amount of calculation for finding the solution would be too high. It can be difficult to obtain an optimal solution in a reasonable execution time because this problem is NP-hard. Therefore, most of the recent studies for such problems seem to focus on heuristic algorithms. In this paper, we propose efficient channel scheduling algorithms to obtain a near-optimal solution on the basis of three meta-heuristic algorithms; the genetic algorithm, the Tabu search, and the simulated annealing. In order to make a search more efficient, we propose some neighborhood generating methods for the proposed algorithms. We evaluate the performance of the proposed algorithms through some experiments in terms of energy consumption and algorithm execution time. The experimental results show that the proposed algorithms are efficient for solving the channel scheduling problem in wireless sensor networks. Copyright © 2011 John Wiley & Sons, Ltd.