Research Article
A Multi-objective Computation Offloading Method for Hybrid Workflow Applications in Mobile Edge Computing
@INPROCEEDINGS{10.1007/978-3-030-48513-9_4, author={Kai Peng and Bohai Zhao and Xingda Qian and Xiaolong Xu and Lixin Zheng and Victor Leung}, title={A Multi-objective Computation Offloading Method for Hybrid Workflow Applications in 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 Hybrid workflow applications Multi-objective Time consumption Energy consumption}, doi={10.1007/978-3-030-48513-9_4} }- Kai Peng
Bohai Zhao
Xingda Qian
Xiaolong Xu
Lixin Zheng
Victor Leung
Year: 2020
A Multi-objective Computation Offloading Method for Hybrid Workflow Applications in Mobile Edge Computing
CLOUDCOMP
Springer
DOI: 10.1007/978-3-030-48513-9_4
Abstract
Computation offloading has become a promising method to overcome intrinsic defects of portable smart devices, such as low operating speed and low battery capacity. However, it is a challenge to design an optimized strategy as the edge server is resource-constrained and the workflow application has timing constraints. In this paper, we investigated the hybrid workflow application computation offloading issue, which further increases the difficulty. According to the analysis of theory and consideration of time consumption and energy consumption, we establish a multi-objective optimization model to solve the issue. Furthermore, we propose a method based on particle swarm optimization algorithm for multi-objective computation offloading to get the optimal strategy for tasks offloading, which is suitable for all the hybrid workflow applications. Finally, extensive experiments have verified the effectiveness and efficiency of our proposed method.
