Research Article
Efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge Computing
@INPROCEEDINGS{10.1007/978-3-030-48513-9_22, author={Qing-Yan Lin and Guang-Shun Li and Jun-Hua Wu and Ying Zhang and JiaHe Yan}, title={Efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge Computing}, proceedings={Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. 9th EAI International Conference, CloudComp 2019, and 4th EAI International Conference, SmartGIFT 2019, Beijing, China, December 4-5, 2019, and December 21-22, 2019}, proceedings_a={CLOUDCOMP}, year={2020}, month={6}, keywords={Mobile edge computing Offloading decision Node clustering Optimal strategy Nash equilibrium}, doi={10.1007/978-3-030-48513-9_22} }- Qing-Yan Lin
Guang-Shun Li
Jun-Hua Wu
Ying Zhang
JiaHe Yan
Year: 2020
Efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge Computing
CLOUDCOMP
Springer
DOI: 10.1007/978-3-030-48513-9_22
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.
