| Abstrakt: |
Named Data Networking (NDN) has emerged as a promising communication paradigm, emphasizing content-centric access rather than location-based access. This model offers several advantages for Internet of Healthcare Things (IoHT) environments, including efficient content distribution, built-in security, and natural support for mobility and scalability. However, existing NDN-based IoHT systems face inefficiencies in their forwarding strategy, where identical Interest packets are forwarded across multiple nodes, causing broadcast storms, increased collisions, higher energy consumption, and delays. These issues negatively impact healthcare system performance, particularly for individuals with disabilities and chronic diseases requiring continuous monitoring. To address these challenges, we propose a Smart and Energy-Aware Forwarding (SEF) strategy based on reinforcement learning for NDN-based IoHT. The SEF strategy leverages the geographical distance and energy levels of neighboring nodes, enabling devices to make more informed forwarding decisions and optimize next-hop selection. This approach reduces broadcast storms, optimizes overall energy consumption, and extends network lifetime. The system model, which targets smart hospitals and monitoring systems for individuals with disabilities, was examined in relation to the proposed strategy. The SEF strategy was then implemented in the NS-3 simulation environment to assess its performance in healthcare scenarios. Results demonstrated that SEF significantly enhanced NDN-based IoHT performance. Specifically, it reduced energy consumption by up to 27.11%, 82.23%, and 84.44%, decreased retrieval time by 20.23%, 48.12%, and 51.65%, and achieved satisfaction rates that were approximately 0.69 higher than those of other strategies, even in more densely populated areas. This forwarding strategy is anticipated to substantially improve the quality and efficiency of NDN-based IoHT systems. [ABSTRACT FROM AUTHOR] |
