Amirhossein Barzin - PhD Student of Industrial Engineering, Azadi Pardis, Azadi Square, Yazd University, Yazd, IRAN
Ahmad Sadegheih - Professor of Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd.,
Hassan Khademi Zare - Professor of Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd.,
Mahboobeh Honarvar - Assistant Professor of Industrial Engineering, Faculty of Industrial Engineering, Yazd University, Daneshgah Blvd.,

In this paper, a Multi-Objective swarm intelligence algorithm based on Firefly and Shuffled frog-leaping algorithms (named SFFA) is presented as an energy aware clustering protocol for Wireless Sensor Networks. The multi-objective fitness function of SFFA consider different criteria such as cluster heads’ distances from the sink, residual energy of nodes, inter- and intra-cluster distances, overlap and load of clusters, to select proper cluster heads at each round. The parameters of SFFA in clustering phase can be adaptively tuned to achieve the best performance based on the network requirements. Simulation outcomes demonstrate average lifetime improvements of up to 49.1% compared with LEACH, 38.3% compared with ERA, 7.1% compared with SIF and 11.3% compared with FSFLA in different network scenarios.

Wireless Sensor Networks, Clustering, Swarm Intelligence Algorithm, Firefly Algorithm, Shuffled Frog Leaping Algorithm