Multi-criteria Leader Selection in Ad Hoc Networks Using Fuzzy Analytical Hierarchy Process

Abstract

Clustering is one of the recent advancements in the implementation of modern ad hoc networks. Nodes in a large network form smaller groups, each guided by a cluster head also termed as leader node. The leader takes the major role of transmitting information across the network, thereby reducing the overhead incurred by other nodes in the network trying to forward information, thereby increasing the lifetime of the network. The selection of the most efficient leader is a challenging task and multi-criteria-based methods are implemented. Whenever the data for the multi-criterion are imprecise or unobtainable, it becomes difficult to predict the values to select the efficient leader. The proposed work uses fuzzy analytical hierarchical process (FAHP)-based multi criteria decision making (F-MCDM) model to overcome the drawbacks of the conventional methods that are ineffective in handling inherent fuzziness and uncertainty, in the selection of the leader. The analysis of results has been carried out based on the performance metrics to evaluate the stability of the network in terms of number of dominant set updates and number of reaffiliations and measuring and resolving inconsistencies in the computation of weighted coefficients for the leader selection criteria. The proposed approach shows marginally a better performance than the existing approach of combined-metrics method and also considerable improvement in the stability of the selected leader in terms of the studied metrics.