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

• Zhimin Liu,
• Zhangdong Ouyang,

Vol. 11, No. 10, October 30, 2017
10.3837/tiis.2017.10.007, Download Paper (Free):

• Coverage enhancement
• energy consumption
• directional sensor networks
• Learning automata

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.

Statistics

Cite this article