A grid-based sectoring for energy-efficient wireless sensor networks

Extending the network lifetime of Wireless Sensor Networks (WSNs) while meeting user needs is crucial, given the limited energy capacity and rapid depletion of nodes. Clustering is an effective strategy for prolonging network lifetime by reducing energy overhead in data transmission. The Sector-Low Energy Adaptive Clustering Hierarchy (S-LEACH) method mitigates energy depletion by grouping nodes into sectors and selecting Cluster Heads (CHs) based on either the highest residual energy or a random number. However, its CH selection process remains suboptimal, leading to energy imbalance and inefficiencies due to fixed sector boundaries. This research improves CH selection by organizing sensor nodes into square grid clusters and employing a routing algorithm for randomized CH selection. Game theory (GT) and Ad hoc on Demand Vectors (AODV) were used to choose the optimal routing path, while Grey Wolf Optimization (GWO) was used to determine the optimal CHs. MATLAB 2023a was utilized for network design and algorithm implementation. After 1,000 transmission rounds, the proposed method extended the network lifetime to 582 seconds, compared to 565 seconds in S-LEACH, representing a 3% improvement. Results indicate that the proposed approach enhances network longevity and balances energy consumption across clusters, ultimately improving overall performance.