Enhanced Multiple Mobile-Sink Energy Efficient Clustering Algorithm in Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) are employed in a variety of applications, including healthcare, home automation, and military security. To address MMECA's drawbacks, we propose Enhanced Multiple Mobile-sink Energy Efficient Clustering Algorithm (EMMCA) for WSNs. To improve energy efficiency, sink mobility management, and network performance, EMMECA employs manifold-based clustering and energy-aware algorithms. To remedy the shortcomings of MMCA, EMMCA adds a slew of key features. To begin, E-MMECA enhances sensor-sink communication and coordination in order to decrease network overhead. With effective sink position update algorithms, it reduces traffic and energy consumption. Second, E-MMECA employs network architecture and intelligent sink mobility control based on energy dynamics. This optimizes sink movement while also lowering computational complexity. E-MMECA also offers optimization algorithms for mobile sink number and location in order to manage sink deployment and cost. By taking into account network coverage, energy consumption, and communication efficiency, E-MMECA optimizes sink position to increase network performance while minimizing resource requirements. To boost fault tolerance, E-MMECA employs powerful sink and communication failure mechanisms. E-MMECA analyzes sink movement energy use by adopting energy-efficient routing and movement patterns. It blends sink mobility with energy economy to increase network life and data collection. In large-scale networks, distributed coordination and data aggregation reduce computational costs and communication delay, making E-MMECA scalable. Comprehensive simulations and evaluations validate MOSEC's effectiveness. In terms of network longevity, energy utilization, communication delay, and load balancing, E-MMECA outperforms MMECA, MMSR, LEACH, and PEGASIS.