Intelligent clustering protocol design and optimisation in wireless sensor networks. (2018) - Tamene, Melaku; Nageswara, Kuda
Communication overhead is one of the big troubles in distributed clustering for which protocols that are able to guarantee limited flow of control packets shall be introduced. Considering that most of fuzzy based protocols are vulnerable to overhead of control packets in cluster setup phase, new approach has been introduced in this paper to reduce communication overhead and consequently optimising distributed cluster formation. Clusters are formed using fuzzy logic and optimal routes towards the base station are established based on ant colony optimisation (ACO) algorithm. The optimisation problem consists of finding routes towards the base station such that the tour length is minimised and the balance of energy consumption is maintained among routes in the path. The fuzzy logic and ACO toolboxes are developed in C++ and integrated with OMNeT++ simulation platform to implement the protocol. The experimental results prove that the proposed protocol extends the network lifetime compared to LEACH and CHEF protocols.