Marouane Myyara, Oussama Lagnfdi, Anouar Darif, and Abderrazak Farchane 

Ehancing QoS for IoT Devices through Heuristics-based Computation Offloading in Multi-access Edge Computing

Multi-access Edge Computing (MEC) networks, particularly with the advent of 5G, aim to reduce latency and increase speed to meet the demands of resource-intensive applications in the Internet of Things (IoT), such as private wireless networks, online gaming, industry, and remote healthcare. These applications require guaranteed performance. However, while Quality of Service (QoS) management is well established in the Cloud, improving it remains a challenge in MEC environments. This study addresses this challenge by proposing heuristic computation offloading algorithms for IoT-intensive devices in MEC networks. These algorithms aim to minimize service time while maximizing the QoS, taking into account tasks and resource characteristics to determine the optimal execution location for IoT device applications. We evaluated our approach using the EdgeCloudSim simulator, and the results demonstrate its superiority over existing solutions. Our approach significantly improves QoS by reducing the service time of IoT application tasks. This research fills a gap in efficient QoS improvement and contributes to advances in computation offloading strategies in MEC environments. It paves the way for enhanced performance of IoT applications in these networks.

DOI: 10.36244/ICJ.2024.4.2

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Please cite this paper the following way:

Marouane Myyara, Oussama Lagnfdi, Anouar Darif, and Abderrazak Farchane, "Ehancing QoS for IoT Devices through Heuristics-based Computation Offloading in Multi-access Edge Computing", Infocommunications Journal, Vol. XVI, No 4, December 2024, pp. 10-17., https://doi.org/10.36244/ICJ.2024.4.2