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dc.contributor.authorChinnadurai U, Vinayagam A-
dc.date.accessioned2025-06-17T13:10:31Z-
dc.date.available2025-06-17T13:10:31Z-
dc.date.issued2025-06-16-
dc.identifier.issn0976 – 0997-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4384-
dc.description.abstractIn the pursuit of sustainable and energy-efficient communication in wireless networks, routing protocols play a crucial role in optimizing energy consumption while ensuring reliable data transmission. This paper proposes a novel cluster-based routing approach integrated with advanced optimization techniques to enhance energy efficiency in wireless networks. The proposed methodology employs Threshold-sensitive Energy Efficient Sensor Network Protocol (TEEN)clustering to reduce the overall energy expenditure by minimizing the distance data packets must travel, thus extending the network's lifetime. Additionally, we introduce a hybrid optimization technique that combines genetic algorithms with particle swarm optimization to dynamically adjust cluster formation and optimize routing paths based on real-time network conditions. Simulation results demonstrate significant improvements in energy efficiency, data delivery ratio, and network longevity compared to existing routing protocols. This research contributes to the development of robust wireless networks capable of supporting the increasing demand for energy-efficient communication in various applications, including IoT, smart cities, and remote monitoring systems.en_US
dc.language.isoenen_US
dc.subjectWireless Networks, Threshold-sensitive Energy Efficient Sensor Network Protocol (TEEN)en_US
dc.subjectOptimization techniques, Genetic Algorithm, Particle Swarm Optimizationen_US
dc.titleOptimizations Cluster Based Energy Efficient Routing Protocol (OCEERP) for Wireless Networksen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Applications

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