Multipath data transmission in WSN using exponential cat swarm and fuzzy optimisation

Abstract

This study proposes a technique for multipath data transmission in Wireless Sensor Network (WSN) by proposing a novel optimisation algorithm, named exponential cat swarm optimisation (ECSO), by integrating the exponential weighted moving average and CSO. Initially, the CH is selected by the penguin fuzzy-based ant colony optimisation (PFuzzyACO) technique, which is the integration of fuzzy, ACO and penguin search optimisation algorithm (PeSOA). After the selection of the optimal CH, the multipath transmission is done by the proposed ECSO algorithm. Here, an optimal path is selected for transmitting the routeing information from source to destination based on various parameters such as trust, energy, distance, delay, traffic density and link lifetime (LLT). Thus, the CHs with maximum trust, energy and LLT, and minimum distance, delay and traffic density are adapted for multipath data transmission using the proposed ECSO algorithm. The proposed ECSO algorithm shows 18.75, 2.99 and 29.87% improvements in terms of number of alive nodes, throughput and network energy, respectively, than the existing PFuzzyACO, which has high performance than the other comparative methods such as artificial bee colony, ACO, fractional artificial bee colony, Low-Energy Adaptive Clustering Hierarchy (LEACH), FuzzyACO and PeSOA.