In wireless sensor networks (WSNs), energy management is a major problem because of the sensors' limited battery life, which reduces the network's longevity. The Green Multi-Mechanism-Low Energy Adaptive Clustering Hierarchy (GME-LEACH) routing protocol presented in this paper combines four complementary mechanisms into a single clustering framework: adaptive CH rotation, sleep-awake scheduling, hybrid multi-hop communication, and multi-criteria cluster-head (CH) selection. To find energy-efficient and strategically placed cluster heads, the suggested CH selection method takes into account residual energy, distance to the base station (BS), local node density, and node centrality. While the hybrid routing system chooses relay-based or direct communication based on communication distance and energy circumstances, sleep-awake scheduling minimizes needless energy usage by alternatively turning on paired nodes. The communication load is further distributed via adaptive CH rotation. Adaptive CH rotation further distributes the communication burden among eligible nodes and helps prevent premature energy depletion. Using a MATLAB-based simulation with a typical WSN configuration, the suggested methodology was evaluated and compared with four ablated GME-LEACH variations and conventional LEACH. The results showed that the complete GME-LEACH achieved first-node-death (FND) at round 1220, half-node-death (HND) at round 1439, and last-node-death (LND) at round 1696 with 25,288 successfully sent packets to the BS. By demonstrating how removing specific mechanisms changes packet delivery behavior and network longevity, the ablation findings demonstrate that the integrated processes contribute differently to the overall performance of the proposed protocol. In particular, the entire design provides a well-balanced combination of early-node survivability, continuous network operation, and data transmission. These results indicate that GME-LEACH provides an integrated energy-aware clustering and routing framework for improving the operational lifetime and communication efficiency of WSNs.
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Maha I. Raheem (2026) studied this question.
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