Energy Efficient Routing in Wireless Sensor Network Using Ant Colony Optimization and Firefly

Abstract

Energy conservation in Wireless Sensor Networks(WSN) is a crucial venture as their miniaturize nature limits their power capabilities. An effective way of energy conservation is the adoption of efficient routing of data from source to sink. This work investigates the performance of two meta-heuristic algorithms, Ant Colony Optimization (ACO) and Firefly Algorithm (FA) on optimal route detection in a WSN routing management system. An adapted ACO was used to search for optimal routes between selected source and sink nodes, after which a developed Discrete FA ran same search. Performance of both were tested on sensor networks deployed randomly, in a clustered pattern and finally randomly-clustered. Evaluators used were energy budget of reported routes. Results show that FA was able detect routes with less cost than those detected by ACO for short routes while ACO performed better with longer routes. Considering the enhanced speed of performance of ACO in comparison to FA and the local search nature of FA, it would be beneficial for future work to explore a hybridized FA-ACO algorithm.