• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Learning Automata-based Algorithm for Area Coverage Problem in Directional Sensor Networks

Vol. 11, No.10, October 31, 2017
10.3837/tiis.2017.10.007, Download Paper (Free):

Abstract

Coverage problem is a research hot spot in directional sensor networks (DSNs). However, the major problem affecting the performance of the current coverage-enhancing strategies is that they just optimize the coverage of networks, but ignore the maximum number of sleep sensors to save more energy. Aiming to find an approximate optimal method that can cover maximum area with minimum number of active sensors, in this paper, a new scheduling algorithm based on learning automata is proposed to enhance area coverage, and shut off redundant sensors as many as possible. To evaluate the performance of the proposed algorithm, several experiments are conducted. Simulation results indicate that the proposed algorithm have effective performance in terms of coverage enhancement and sleeping sensors compared to the existing algorithms.


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Cite this article

[IEEE Style]
Zhimin Liu and Zhangdong Ouyang, "A Learning Automata-based Algorithm for Area Coverage Problem in Directional Sensor Networks," KSII Transactions on Internet and Information Systems, vol. 11, no. 10, pp. 4807-4822, 2017. DOI: 10.3837/tiis.2017.10.007

[ACM Style]
Liu, Z. and Ouyang, Z. 2017. A Learning Automata-based Algorithm for Area Coverage Problem in Directional Sensor Networks. KSII Transactions on Internet and Information Systems, 11, 10, (2017), 4807-4822. DOI: 10.3837/tiis.2017.10.007