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2020 | OriginalPaper | Chapter

Efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge Computing

Authors : Qing-Yan Lin, Guang-Shun Li, Jun-Hua Wu, Ying Zhang, JiaHe Yan

Published in: Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications

Publisher: Springer International Publishing

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Abstract

The Mobile Edge Computing (MEC) is a new paradigm that can meet the growing computing needs of mobile applications. Terminal devices can transfer tasks to MEC servers nearby to improve the quality of computing. In this paper, we investigate the multi-user computation offloading problem for mobile-edge computing. We study two different computation models, local computing and edge computing. First, we drive the expressions for time delay and energy consumption for local and edge computing. Then, we propose a server partitioning algorithm based on clustering. We propose a task scheduling and offloading algorithm in a multi-users MEC system. We formulate the tasks offloading decision problem as a multi-user game, which always has a Nash equilibrium. Our proposed algorithms are finally verified by numerical results, which show that the scheduling strategy based on clustering can significantly reduce the energy consumption and overhead.

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Metadata
Title
Efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge Computing
Authors
Qing-Yan Lin
Guang-Shun Li
Jun-Hua Wu
Ying Zhang
JiaHe Yan
Copyright Year
2020
Book
Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications

Print ISBN: 978-3-030-48512-2

Electronic ISBN: 978-3-030-48513-9

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-48513-9_22

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