Solving Target Coverage Problem Using Cover Sets in Wireless Sensor Networks Based on Learning Automata

Authors:
Hosein Mohamadi;Abdul Samad Ismail;Shaharuddin Salleh
Affiliations:
Computer Department, Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia 81310;Computer Department, Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia 81310;Mathematics Department, Faculty of Science, Universiti Teknologi Malaysia, Johor Bahru, Malaysia 81310
Venue:
Wireless Personal Communications: An International Journal
Year:
2014

Citing 17
Cited 1

Learning automata with changing number of actions

IEEE Transactions on Systems, Man and Cybernetics
Learning automata: theory and applications

Learning automata: theory and applications
Improving wireless sensor network lifetime through power aware organization

Wireless Networks
An effective genetic algorithm for improving wireless sensor network lifetime

Proceedings of the 9th annual conference on Genetic and evolutionary computation
Review: Coverage and connectivity issues in wireless sensor networks: A survey

Pervasive and Mobile Computing
Wireless sensor network survey

Computer Networks: The International Journal of Computer and Telecommunications Networking
Priority-based target coverage in directional sensor networks using a genetic algorithm

Computers & Mathematics with Applications
Solving coverage problems in wireless sensor networks using cover sets

Ad Hoc Networks
A learning automata based scheduling solution to the dynamic point coverage problem in wireless sensor networks

Computer Networks: The International Journal of Computer and Telecommunications Networking
A memetic algorithm for extending wireless sensor network lifetime

Information Sciences: an International Journal
Coverage problems in sensor networks: A survey

ACM Computing Surveys (CSUR)
Learning automata-based algorithms for solving stochastic minimum spanning tree problem

Applied Soft Computing
Weighted Steiner Connected Dominating Set and its Application to Multicast Routing in Wireless MANETs

Wireless Personal Communications: An International Journal
A learning automata-based algorithm for solving coverage problem in directional sensor networks

Computing
LAAP: A Learning Automata-based Adaptive Polling Scheme for Clustered Wireless Ad-Hoc Networks

Wireless Personal Communications: An International Journal
Maximizing Lifetime of Target Coverage in Wireless Sensor Networks Using Learning Automata

Wireless Personal Communications: An International Journal
Learning Automata-Based Algorithms for Solving the Target Coverage Problem in Directional Sensor Networks

Wireless Personal Communications: An International Journal

A learning automata-based solution to the target coverage problem in wireless sensor networks

Proceedings of International Conference on Advances in Mobile Computing & Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recent years have witnessed a significant increase in employing wireless sensor networks (WSNs) for a variety of applications. Monitoring a set of discrete targets and, at the same time, extending the network lifetime is a critical issue in WSNs. One method to solve this problem is designing an efficient scheduling algorithm that is able to organize sensor nodes into several cover sets in such a way that each cover set could monitor all the targets. This study presents three learning automata-based scheduling algorithms to solve the problem. Moreover, several pruning rules are devised to avoid the selection of redundant sensors and manage critical sensors for extending the network lifetime. To evaluate the performance of proposed algorithms, we conducted several experiments, and the obtained results indicated that Algorithm 3 was more successful in terms of extending the network lifetime.