Wireless Sensor Network (WSN) Routing Optimization via the Implementation of Fuzzy Ant Colony (FACO) Algorithm: Towards Enhanced Energy Conservation

Abstract

To realize efficient performance in industrial applications, wireless sensor networks (WSNs) have witnessed routes developed. In WSN operations, it is important to note that they rely upon and operate on battery, which implies that there is energy restriction. In the current study, the aim was to design a routing protocol through which improved WSN energy conservation could be achieved, hence preserving the battery life. In the study, three variables were on the focus and aided in making informed decisions about routes that would be deemed appropriate. These parameters included the distance needed for the successful sending of packets to the destination node (from the source and in meters), the traffic amount in Erlang, and the sensor energy in joules. In the proposed routing protocol, it is important to note that it was based on FACO (fuzzy logic and ant colony optimization). Indeed, the role of employing fuzzy logic lay in the calculation of the total cost of the node–gateway intersection relative to the node’s energy, as well as its traffic load. Similarly, the implementation of ACO was informed by the need for searching and establishing distances that would prove the shortest between the sources to the destination sensor nodes, with the shortest distances aiding in system performance evaluation and inference-making. With MATLAB simulation adopted, findings demonstrated significant improvements in system performance, especially in terms of energy conservation. Particularly, results from FACO implementation, relative to the energy conservation parameter, suggested its superiority, as it outperformed ACO, having implemented the two algorithms under the same experimental conditions and with the same experimental parameters. The future implication for industrial applications is that the routing algorithm associated with system improvements via more energy conservation could be implemented via the use of WSN.