Research Article
Distributed Task Splitting and Offloading in Mobile Edge Computing
@INPROCEEDINGS{10.1007/978-3-030-41114-5_3, author={Yanling Ren and Zhihui Weng and Yuanjiang Li and Zhibin Xie and Kening Song and Xiaolei Sun}, title={Distributed Task Splitting and Offloading in Mobile Edge Computing}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part I}, proceedings_a={CHINACOM}, year={2020}, month={2}, keywords={Mobile edge computing Offload strategy Game theory}, doi={10.1007/978-3-030-41114-5_3} }- Yanling Ren
Zhihui Weng
Yuanjiang Li
Zhibin Xie
Kening Song
Xiaolei Sun
Year: 2020
Distributed Task Splitting and Offloading in Mobile Edge Computing
CHINACOM
Springer
DOI: 10.1007/978-3-030-41114-5_3
Abstract
With the rapid development of the mobile internet, many emerging compute-intensive and data-intensive tasks are extremely sensitive to latency and cannot be implemented on mobile devices (MDs). To solve this problem, mobile edge computing (MEC) appears to be a promising solution. In this paper, we propose a distributed task splitting and offloading algorithm (DSOA) for the scenario of multi-device and multi-MEC servers in ultra-dense networks (UDN). In the proposed scheme, the MDs can perform their tasks locally or offload suitable percentage of tasks to the MEC server. The optimization goal is to minimize the overall task computation time. Since the MDs are selfish, we propose a game theory approach to achieve optimal global computation time. Finally, the numerical simulation results verify that the algorithm can effectively reduce global computation time.
