Optimization Techniques and Performance Assessment of IoT-Enabled WBANs in Healthcare Systems
Keywords:
Wireless Body Area Networks, IoT Healthcare, Energy Optimization, Quality of Service, Performance MetricsAbstract
Wireless Body Area Networks (WBANs) integrated with Internet of Things (IoT) technology have emerged as transformative solutions for continuous healthcare monitoring systems. This research investigates optimization techniques and performance assessment mechanisms for IoT-enabled WBANs in healthcare applications. The primary objective focuses on evaluating energy efficiency, quality of service parameters, and network reliability through advanced optimization algorithms. The methodology encompasses systematic analysis of IEEE 802.15.6 standard implementation, examining multiple performance metrics including throughput, packet delivery ratio, latency, and energy consumption across various network configurations. Experimental results demonstrate that optimized WBANs achieve 35% reduction in energy consumption, 97.5% packet delivery ratio, and latency below 92 milliseconds. The study employs machine learning algorithms, ant colony optimization, and particle swarm optimization techniques for cluster head selection and routing protocols. Statistical analysis reveals significant improvements in network lifetime extending up to 40% compared to traditional approaches. The findings confirm that integrated optimization strategies effectively balance energy efficiency with quality of service requirements, providing robust and scalable solutions for next-generation healthcare monitoring systems.
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