An energy-efficient stable clustering approach using fuzzy-enhanced flower pollination algorithm for WSNs

Due to advancement in the technology and need for machine-to-machine connectivity, wireless sensor network (WSN) overplays the role compared to other wireless networks. In this context, different applications based on WSNs need to be executed efficiently in terms of energy and communication. To achieve this, there is a need to collaborate among various devices at various levels. This can be achieved by the grouping of these devices, that is, through the clustering. Clustering-based routing is the most suitable approach to support for load balancing, fault tolerance and reliable communication to prolong performance parameters of WSN. These performance parameters are achieved at the cost of reduced lifetime of cluster head (CH). To overcome such limitations in clustering-based hierarchical approach, efficient CH selection algorithm and optimized routing algorithm are essential to design efficient solution for larger scale networks. In this paper, fuzzy-enhanced flower pollination algorithm-based threshold-sensitive energy-efficient clustering protocol is proposed to prolong the stability period of the network. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in the context of energy consumption, stability period and system lifetime.