Energy‐Aware Mobile Data Collection in Wireless Sensor Networks Using Heuristic Clustering and Path Optimization Techniques

Wireless sensor networks (WSNs) face critical energy constraints that directly affect network longevity, especially when scaled to large deployments. This paper uses a multi‐stage process to introduce an energy‐efficient data collection framework using mobile data collectors (MDCs). We employ a modified weighted set cover approach to identify a minimal set of strategically placed anchor points (APs), significantly reducing the number of required MDCs. After refining them with an optimized fuzzy C‐means clustering and a traffic load balancing technique, these APs ensure coverage for all areas and balance the load among each other. Using Euler graph analysis, the routing paths are determined through the minimum spanning tree and perfect matching approaches. Experimental results demonstrate that our suggested method reduces the amount of MDCs by 28%, the distance traveled by tours by 35%, the average delay in data collection by 10%, and increases data transmission efficiency by 16%. The reported results prove that our suggested method helps gather more data energy efficiently and prolong the lifetime of WSN nodes.