FUCA: Fuzzy‐based unequal clustering algorithm to prolong the lifetime of wireless sensor networks

Wireless sensor network comprises billions of nodes that work collaboratively, gather data, and transmit to the sink. “Energy hole” or “hotspot” problem is a phenomenon in which nodes near to the sink die prematurely, which causes the network partition. This is because of the imbalance of the consumption of energy by the nodes in wireless sensor networks. This decreases the network's lifetime. Unequal clustering is a technique to cope up with this issue. In this paper, an algorithm, “fuzzy‐based unequal clustering algorithm,” is proposed to prolong the lifetime of the network. This protocol forms unequal clusters. This is to balance the energy consumption. Cluster head selection is done through fuzzy logic approach. Input variables are the distance to base station, residual energy, and density. Competition radius and rank are the two output fuzzy variables. Mamdani method is employed for fuzzy inference. The protocol is compared with well‐known algorithms, like low‐energy adaptive clustering hierarchy, energy‐aware unequal clustering fuzzy, multi‐objective fuzzy clustering algorithm, and fuzzy‐based unequal clustering under different network scenarios. In all the scenarios, the proposed protocol performs better. It extends the lifetime of the network as compared with its counterparts.