Mobility-Aware Offloading and Resource Allocation in MEC-Enabled IoT Networks
Han Hu, Weiwei Song, Qun Wang, Fuhui Zhou, Rose Qingyang Hu

TL;DR
This paper proposes a mobility-aware offloading and resource allocation scheme for MEC-enabled IoT networks, optimizing long-term service costs while considering device mobility, and demonstrates its effectiveness through simulations.
Contribution
It introduces an online algorithm that jointly optimizes offloading, resource allocation, and mobility considerations in MEC-IoT networks, which was not sufficiently addressed in prior work.
Findings
Outperforms benchmark methods in system service cost
Balances service cost and delay performance
Effective in mobility scenarios
Abstract
Mobile edge computing (MEC)-enabled Internet of Things (IoT) networks have been deemed a promising paradigm to support massive energy-constrained and computation-limited IoT devices. IoT with mobility has found tremendous new services in the 5G era and the forthcoming 6G eras such as autonomous driving and vehicular communications. However, mobility of IoT devices has not been studied in the sufficient level in the existing works. In this paper, the offloading decision and resource allocation problem is studied with mobility consideration. The long-term average sum service cost of all the mobile IoT devices (MIDs) is minimized by jointly optimizing the CPU-cycle frequencies, the transmit power, and the user association vector of MIDs. An online mobility-aware offloading and resource allocation (OMORA) algorithm is proposed based on Lyapunov optimization and Semi-Definite Programming…
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Taxonomy
Methodstravel james
