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    Architecture, Protocols, and Applications of the Internet of Medical Things (IoMT)
    (Engineering and Technology Publishing, 2022) Askar, N.A.; Habbal, A.; Mohammed, A.H.; Sajat, M.S.; Yusupov, Z.; Kodirov, D.
    The Internet of Things (IoT) refers to the interconnected framework of web-connected objects that can collect and transfer information over a remote network without requiring any human intervention. The rapid progression in the development of IoT-based devices and their expansion towards making the medical care facility financially more savvy, proactive, and customized, has given rise to the development of the "Internet of Medical Things (IoMT)" that are assumed to function proactively in all domains of the healthcare industry. Within this framework, the IoMT-based healthcare system delivers various advantages, such as quick and unfailing treatment, enhanced communication, cost minimization, etc., through the exploitation of several new technologies. For instance, machine learning has significantly helped with the exploitation of various healthcare systems; fog computing not only minimises the cost of communication but also provides low latency; blockchain delivers its users a much better way of protecting sensitive and confidential information and data they possess. In this survey, a comprehensive elaboration of the IoMT-based healthcare systems based on modern technologies was conducted. This article describes various techniques and solutions of IoMT healthcare systems in the context of emerging technologies, and the related future trends and applications for a better understanding of how IoMT can enhance the healthcare industry now and in future. © 2022 Journal of Communications and 2022 by the authors.
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    RLEAFS: Reinforcement Learning based Energy Aware Forwarding Strategy for NDN based IoT Networks
    (Institute of Electrical and Electronics Engineers Inc., 2024) Askar, N.A.; Habbal, A.
    Internet of Things technology is seeing huge success in various fields. Smart objects combined with Internet connection have become an essential part of every aspect of human life. The way people interact with the things around them has inevitably changed. The IoT system presents many challenges. Devices are heterogeneous and limited in energy and memory. The applications used require a continuous and stable connection to transmit information effectively. This results in high energy consumption. Named Data Networking (NDN) is a promising networking concept. Unlike traditional networking, it's a data-driven model. It uses names to identify and retrieve data instead of device addresses. NDN provides a simple and efficient forwarding mechanism which makes it suitable for IOT communication. In this paper, we proposed forwarding strategy based on reinforcement learning for NDN-based IoT communications. The proposal integrates the reinforcement learning algorithm in the path selection strategy to optimize the overall energy consumption and extend the network lifetime. This research consists of two schemes firstly provide the complexities and dynamic nature of real-world IoT environments, finally, enhance the interest forward strategy. Our proposed research is implemented in ndnSIM and compared with state of the-art IOT-NDN forwarding strategies. The obtained results show clearly the effectiveness and robustness of our solution which outperforms the benchmarked methods in terms of energy consumption, network lifetime, retrieval time, and satisfactory rates. © 2013 IEEE.