arrow
Return

Distributed Task Offloading in Mobile-Edge Computing With Virtual Machines

delete2024-07-01
delete0
PRE
AI
H
Hongju Lee
C
Choi, Sung Il
S
Sang Hyun Lee
M
Mérouane Debbah
I
Inkyu Lee *
DOI:10.1109/JIOT.2024.3388452delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Mobile-edge computing (MEC) offloads computation intensive tasks of individual users to computing clouds to alleviate the computing loads. Virtual machines (VMs), in practice, are often adopted to realize the parallel computing feature of MEC clouds. A careful local interaction among VMs further reduces the overall computing latency. However, their management turns out quite challenging in practical wireless MEC networks. This article aims at minimizing the latency of the overall MEC task with the min-max criterion. To this end, a novel distributed strategy is developed for the joint management of the task allocation and the offloading balance among VMs. This task offloading protocol is carried out through a message-passing framework that enables a simultaneous consideration of the min-max criterion about multiple MEC tasks. The numerical results demonstrate that the proposed scheduling for distributed MEC operations achieves a 40% improvement in network utility performance over existing optimization techniques.
Keywords:
Computing latency
distributed task offloading
min-max criterion
mobile-edge computing (MEC)
virtual machines (VMs)

Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

K
Korea University
Scholars:
3.6W
Papers: 3.8W
Citations: 4.4W