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Title Onem2M-Basedadaptive Loss Recovery Mechanisms For Enhancing Scalability And Quality Of Service In Iot Networks
ID_Doc 40024
Authors Abourriche S.; Et-Tousy J.; Zyane A.; Ghammaz A.
Year 2025
Published 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2025
DOI http://dx.doi.org/10.1109/IRASET64571.2025.11007947
Abstract The technological world has known major advancements, leading to the creation of new paradigms like the Internet of Things (IoT). IoT is a combination between two concepts , the "Internet"and "Things".This innovative notion connects billions of devices, enabling automation and smarter systems across industries like healthcare, smart cities, and manufacturing. By integrating concepts such as M2M, Big Data, and AI, IoT has transformed communication and innovation. However, as IoT networks expand, they face challenges like scalability, increased latency, limited bandwidth, and higher error rates, which impact Quality of Service (QoS).This paper proposes implementing Simple Automatic Repeat reQuest loss recovery mechanisms within IoT architecture to enhance QoS and address scalability challenges, ensuring reliable performance even as the network grows. © 2025 IEEE.
Author Keywords AI; Big Data; error rates; IoT; Latency; M2M; QoS; Scalability; SimpleARQ


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