Optimizing cluster head selection in wireless sensor networks using firefly and genetics algorithm

Document Type : Original Article

Authors

1 PhD Student, Department of Electrical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran. Email: navid.moshtaghi@alumni.ut.ac.ir

2 Master of Electrical Control Engineering, Sajjad University of Technology, Mashhad, Iran. Email: mh.olyaei123@sadjad

Abstract

Sensor networks are a new generation of networks. In this paper, an algorithm has been proposed to improve the performance of the EAMMH algorithm. For this purpose, the evolutionary firefly algorithm and genetic algorithm that itself has been modeled after natural biological evolution modeling have been used, and instead of randomly choosing cluster heads, it works on the possible answers that have superior attributes and also have a higher survival rate. The results of comparing LEACH and EAMMH protocols and the proposed method in terms of the number of dead nodes compared to the number of execution times based on 50, 100, and 200 nodes indicates that the number of dead nodes for the simulation of LEACH protocol is almost equal to the number of dead nodes for the EAMMH protocol, but the proposed algorithm has approximately 10 percent less dead nodes, but by an increase in the number of nodes (200 nodes) the number of dead nodes have decreased 35 percent and 22 percent compared to LEACH and EAMMH algorithms respectively.

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