Research Challenges of Improved Cluster Chain Power-Efficient Routing Using Natural Computing Methods for Wireless Sensor Network
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Abstract
Wireless Sensor Networks (WSNs) primarily operate on batteries, making energy conservation crucial, especially in routing processes. Efficient routing in WSNs is challenging due to the network's distinct attributes. Among various routing protocols, CCPAR is noteworthy as it utilizes a chain between cluster heads to relay data to the base station. This research delves into nature-inspired techniques for energy-efficient routing in WSNs. It introduces the Moth-Dolphin Optimization Algorithm, capitalizing on the communication between moths to enhance routing performance. This innovative method combines the navigational skills of moths and the communicative attributes of dolphins. When benchmarked against other optimization methods, the Moth-Dolphin algorithm offers favorable results. The study then applies this algorithm to improve CCPAR routing, aiming for reduced energy consumption. The modified routing's effectiveness is evaluated against other top-tier algorithms, considering factors like energy consumption, throughput, network longevity, and delay.