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<p>Wireless Sensor Networks (WSNs) find applications across numerous industries, including disaster response, traffic management, smart home systems, agriculture, healthcare, environmental monitoring, and military surveillance. For applications such as military surveillance, network endurance is one of the most important requirements. WSN nodes use a limited amount of battery power, therefore maximizing energy use is crucial to enhancing network performance. This study presents a novel algorithm called Fuzzy Hybrid Zone-Based Arbitrary Clustering (FHZBAC), which aims to enhance efficiency and fault tolerance of network. This method chooses zone and cluster heads dynamically to find the best paths, which lowers energy consumption and guarantees effective data transfer. FHZBAC guarantees loop-free routing and successfully tackles the node hotspot issue. When selecting cluster heads during the CHIP phase, several factors are considered, such as node energy left, buffer size, latency, hop count, neighbor density, and connection quality. The optimal zone hotspot node is chosen from among the cluster heads during the FZIP phase using a fuzzy inference technique. FHZBAC outperforms other well-known protocols, such as FLPSOC, EAFTC-RIS, CSO-UCRA, and HYBRID GSO-ACO, in relation to the network's lifespan extension, energy efficiency, latency reduction, alive nodes, and the ratio of packets successfully delivered.</p>

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A Fuzzy Hybrid Zone Head Selection and Arbitrary Cluster Based Routing Algorithm for Border Surveillance in WSN

  • 期刊论文

  • 发表日期：

    2025年1月1日

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  • J. Jayachandran,
  • K. Vimaladevi

摘要

Wireless Sensor Networks (WSNs) find applications across numerous industries, including disaster response, traffic management, smart home systems, agriculture, healthcare, environmental monitoring, and military surveillance. For applications such as military surveillance, network endurance is one of the most important requirements. WSN nodes use a limited amount of battery power, therefore maximizing energy use is crucial to enhancing network performance. This study presents a novel algorithm called Fuzzy Hybrid Zone-Based Arbitrary Clustering (FHZBAC), which aims to enhance efficiency and fault tolerance of network. This method chooses zone and cluster heads dynamically to find the best paths, which lowers energy consumption and guarantees effective data transfer. FHZBAC guarantees loop-free routing and successfully tackles the node hotspot issue. When selecting cluster heads during the CHIP phase, several factors are considered, such as node energy left, buffer size, latency, hop count, neighbor density, and connection quality. The optimal zone hotspot node is chosen from among the cluster heads during the FZIP phase using a fuzzy inference technique. FHZBAC outperforms other well-known protocols, such as FLPSOC, EAFTC-RIS, CSO-UCRA, and HYBRID GSO-ACO, in relation to the network's lifespan extension, energy efficiency, latency reduction, alive nodes, and the ratio of packets successfully delivered.