A Cutting-edge Metaheuristic Approach Based on ‎The Manifold Distance for Energy-efficient Clustering ‎in WSN

This paper presents the development of a new algorithm called F-MPSO, which aims to enhance energy efficiency and extend the lifetime of wireless sensor networks. The F-MPSO algorithm aims to optimize the selection of cluster heads, which is a problem that falls under the category of Non-Deterministic Polynomial (NP)-hard problems. To address this challenge, a hybrid metaheuristic approach has been implemented using manifold distance to cluster the sensor nodes. We recommend using a combination of the Firefly approach for local updates and the PSO approach for global updates to create a reliable cluster. Our strategy aims to improve the overall lifespan of the network. We use a metric that takes into account the different routes available and gives preference to paths that go through intermediate sensors with high residual energy, rather than simply selecting the shortest distance between a regular node and cluster heads with low residual energy. Based on the analysis conducted using Matlab, it has been determined that the F-MPSO algorithm proposed is highly efficient regarding energy consumption. Additionally, it has been deemed successful in extending the network lifetime. Results from round 1600 indicate that the proposed method had approximately 78 still operational nodes. On the other hand, Leach's algorithm had no live nodes, while enhanced-LEACH and ESO_LEACH had 25 and 53 live nodes, respectively. Furthermore, the author has compared the results with previous algorithms, and the outcome shows excellent promise.