EUDFC - Enhanced Unequal Distributed Type-2 Fuzzy Clustering Algorithm

Abstract

Wireless sensor networks are composed of nodes that monitor the environment and send their measurements to a base station. Due to the reduced computational and energetical resources of the sensor nodes, network organization must take into account those constraints to reduce energy consumption and, in turn, to prolong the lifetime of the network. Thus, collaborative management techniques, like clustering, are usually implemented. This paper proposes a novel unequal distributed clustering algorithm for wireless sensor networks that employs a new set of input variables. Compared with previous works, these variables help for a more accurate estimation of the convenience of a node to be a cluster head. The developed algorithm relies on local information of the sensors to diminish the data exchange, reduce the interference and the consumption of the transmission processes. Because of the underlying uncertainty of the local data, a type-2 fuzzy logic system constitutes the basis of the proposed clustering algorithm whose knowledge base is sampled to allow its feasible implementation in a node. In addition, it is used an unequal scheme for the cluster sizes because it has been demonstrated that those methods are more convenient in terms of energy consumption. The simulation results demonstrate the effectiveness of the algorithm to extend the network lifetime.