Water Cycle Algorithm Tuned Fuzzy Expert System for Trusted Routing in Smart Grid Communication Network

Abstract

Finding an optimal route for reliable data delivery in the smart grid communication network (SGCN) is a challenging task due to its dynamic nature. Even though the rule set (RS) and membership function (MF) framed intuitively in our previous fuzzy logic (FL) approach performs the trusted routing satisfactorily, it consumes computational memory and reduces the energy efficiency of the node. To address this issue, in this article, we proposed a novel trust evaluation framework that employs water cycle algorithm (WCA) for automatic tuning of the rule set and membership function for the decision variable to route the packet in an adaptable manner. Variables like distance, link stability, and node honesty are considered for evaluation using WCA in three iterative processes, namely, exploitation, evaporation, and raining to find the near optimal if–then rules and points for the membership functions. An experimental setup is created using Network Simulator-2 (NS2) to evaluate the performance of the proposed trusted routing algorithm in SGCN. Extensive experiments are conducted for three cases, namely, 1) evaluating RS with fixed MF; 2) evaluating MF with fixed RS; and 3) combined evaluation of MF and RS to evaluate the performance of the proposed model. From the simulation results, it is clear that the RS and MF generated by the proposed model is small and compact enough to provide reliable routing in SGCN.