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Quality of Service (QoS) Enhancement in Healthcare Mobile Wireless Sensor Networks Using Adaptable Hummingbird Optimization Based Dynamic Source Routing (AHODSR)


Affiliations
1 Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India
2 Department of Computer Science, Rathinam College of Arts and Science, Coimbatore, Tamil Nadu, India

The research introduces MC-DSR-AHO a routing protocol integrating Markov Chain-based Dynamic Source Routing (MC-DSR) with Adaptable Hummingbird Optimization (AHO) for Mobile Wireless Sensor Networks (MWSNs). MWSNs face challenges such as packet loss, latency, limited throughput, and energy inefficiency in dynamic and resource-constrained environments. MC-DSR-AHO addresses these issues by combining the probabilistic modeling of MC-DSR with the adaptive optimization of AHO. This integration results in improved packet delivery reliability, reduced packet drops, efficient data transmission, optimized delays, and energy conservation. Simulations demonstrate the protocol’s scalability and consistent performance across varying node counts. This research highlights the effectiveness of utilizing probability modeling and bio-inspired optimization to enhance the adaptability and efficiency of routing protocols in MWSNs. MC-DSR-AHO represents a significant advancement, providing practical benefits and guiding future research in dynamic network environments.

Keywords

Dynamic Source Routing, Hummingbird Optimization, MWSNs, Routing ProtocolBio-inspired Optimization, QoS, Healthcare
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  • Quality of Service (QoS) Enhancement in Healthcare Mobile Wireless Sensor Networks Using Adaptable Hummingbird Optimization Based Dynamic Source Routing (AHODSR)

Abstract Views: 115  | 

Authors

S. Kawsalya
Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India
D. Vimal Kumar
Department of Computer Science, Rathinam College of Arts and Science, Coimbatore, Tamil Nadu, India

Abstract


The research introduces MC-DSR-AHO a routing protocol integrating Markov Chain-based Dynamic Source Routing (MC-DSR) with Adaptable Hummingbird Optimization (AHO) for Mobile Wireless Sensor Networks (MWSNs). MWSNs face challenges such as packet loss, latency, limited throughput, and energy inefficiency in dynamic and resource-constrained environments. MC-DSR-AHO addresses these issues by combining the probabilistic modeling of MC-DSR with the adaptive optimization of AHO. This integration results in improved packet delivery reliability, reduced packet drops, efficient data transmission, optimized delays, and energy conservation. Simulations demonstrate the protocol’s scalability and consistent performance across varying node counts. This research highlights the effectiveness of utilizing probability modeling and bio-inspired optimization to enhance the adaptability and efficiency of routing protocols in MWSNs. MC-DSR-AHO represents a significant advancement, providing practical benefits and guiding future research in dynamic network environments.

Keywords


Dynamic Source Routing, Hummingbird Optimization, MWSNs, Routing ProtocolBio-inspired Optimization, QoS, Healthcare



DOI: https://doi.org/10.22247/ijcna%2F2024%2F20