Research on Offloading Strategy in Edge Computing of Internet of Things

Duan, Xiaoting; Xu, Fei; Sun, Yongyong

doi:10.1109/iccnea50255.2020.00050

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…Based on the Lyapunov optimization [39], we construct a virtual caching cost queue C(t) which represents the backlog of caching cost of the current slot [9], [40], [41]. We assume the initial state is C(0) = 0, and the state transition of the queue can be written as…”

Section: A Lyapunov-based Problem Transformationmentioning

confidence: 99%

When the User-Centric Network Meets Mobile Edge Computing: Challenges and Optimization

Qin

2023

IEEE Commun. Mag.

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In the traditional mobile edge computing (MEC) system, the availability of MEC services is greatly limited for the edge users of the cell due to serious signal attenuation and inter-cell interference. User-centric MEC (UC-MEC) can be seen as a promising solution to address this issue. In UC-MEC, each user is served by a dedicated access point (AP) cluster enabled with MEC capability instead of a single MEC server, however, at the expense of more energy consumption and greater privacy risks. To achieve efficient and reliable resource utilization with user-centric services, we propose an energy efficient blockchainenabled UC-MEC system where blockchain operations and resource optimization are jointly performed. Firstly, we design a resource-aware, reliable, replicated, redundant, and faulttolerant (R-RAFT) consensus mechanism to implement secure and reliable resource trading. Then, an optimization framework based on alternating direction method of multipliers (ADMM) is proposed to minimize the total energy consumed by wireless transmission, consensus and task computing, where APs clustering, computing resource allocation and bandwidth allocation are jointly considered. Simulation results show superiority of the proposed UC-MEC system over reference schemes, at most 33.96% reduction in the total delay and 48.77% reduction in the total energy consumption.

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