Home > Archive > 2012 > Volume 2 Number 5 (Oct. 2012) >
IJMLC 2012 Vol.2(5): 626-632 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.203

An Adaptive Scheduling Algorithm for Set Cover Problem in Wireless Sensor Networks: A Cellular Learning Automata Approach

Reza Ghaderi, Mehdi Esnaashari, and Mohammad Reza Meybodi

Abstract—Redundant node deployment is a common strategy in wireless sensor networks. This redundancy can be due to various reasons such as high probability of failures, long lifetime expectation, etc. One major problem in wireless sensor networks is to use this redundancy in order to extend the network lifetime while keeping the entire area under the coverage of the network. In this problem, which is known as set cover problem, the main objective is to select a subset of sensor nodes as active nodes so that the set of active nodes covers the entire area of the network. In this paper, an scheduling algorithm is presented for solving the set cover problem using cellular learning automata. In this algorithm, each node is equipped with a learning automaton which locally decides for the node to be active or not based on the situations of its neighbors. Simulation results in J-sim simulator environment specify the efficiency of the proposed scheduling algorithm over existing algorithms such as PEAS and PECAS.

Index Terms—Area coverage, cellular learning automata, learning automata, scheduling algorithm, wireless sensor networks.

R. Ghaderi is with the Computer Engineering Department, Islamic Azad University, Arak 38135 Iran (e-mail: Ghaderi.re@gmail.com).
M. Esnaashari and M. R. Meybodi are with the Computer Engineering and Information Technology Department, Amirkabir University of Technology, Tehran 15914 Iran (e-mail: Esnaashari@aut.ac.ir; mmeybodi@aut.ac.ir).

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Cite: Reza Ghaderi, Mehdi Esnaashari, and Mohammad Reza Meybodi, "An Adaptive Scheduling Algorithm for Set Cover Problem in Wireless Sensor Networks: A Cellular Learning Automata Approach," International Journal of Machine Learning and Computing vol. 2, no. 5, pp. 626-632, 2012.

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net


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