Khezri, S., Osmani, A., Eslamnour, B. (2015). Coverage Improvement Using GLA (Genetic Learning Automata) Algorithm in Wireless Sensor Networks. Journal of Advances in Computer Research, 6(3), 107-123.
Shirin Khezri; Amjad Osmani; Behdis Eslamnour. "Coverage Improvement Using GLA (Genetic Learning Automata) Algorithm in Wireless Sensor Networks". Journal of Advances in Computer Research, 6, 3, 2015, 107-123.
Khezri, S., Osmani, A., Eslamnour, B. (2015). 'Coverage Improvement Using GLA (Genetic Learning Automata) Algorithm in Wireless Sensor Networks', Journal of Advances in Computer Research, 6(3), pp. 107-123.
Khezri, S., Osmani, A., Eslamnour, B. Coverage Improvement Using GLA (Genetic Learning Automata) Algorithm in Wireless Sensor Networks. Journal of Advances in Computer Research, 2015; 6(3): 107-123.
Coverage Improvement Using GLA (Genetic Learning Automata) Algorithm in Wireless Sensor Networks
1Department of Computer Engineering, Payame Noor University, PO BOX 19395-3697, Tehran, i.r of Iran
2Department of Computer Engineering, Saghez Branch, Islamic Azad University, Saghez ,Iran
3Department of Electrical and Computer Engineering, Urmia University, Urmia, Iran
Abstract
Coverage improvement is one of the main problems in wireless sensor networks. Given a finite number of sensors, improvement of the sensor deployment will provide sufficient sensor coverage and save cost of sensors for locating in grid points. For achieving good coverage, the sensors should be placed in adequate places. This paper uses the genetic and learning automata as intelligent methods for solving the blanket sensor placement. In this paper an NP-complete problem for arbitrary sensor fields is described which is one of the most important issues in the research fields, so the proposed algorithm is going to solve this problem by considering two factors: first, the complete coverage and second, the minimum used sensors. The proposed method is examined in different areas using MATLAB. The results confirm the successes of using this new method in sensor placement; also they show that the new method is more efficient than other methods like FAPBIL and MDPSO in large areas
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