Fault-tolerant scheduling algorithm for service workflow in MEC environment

被引：0
|
作者：
Yuan Y. [1 ,2 ]
Huang X. [1 ,2 ]
Yu D. [1 ]
Li Z. [1 ]
机构：
[1] School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou
[2] Key Laboratory of Complex Systems Modeling and Simulation, Ministry of Education, Hangzhou
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2021年 / 27卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Delay optimization; Fault-tolerant strategy; Immune algorithm; Mobile edge computing; Particle swarm optimization algorithm; Service workflow;
D O I：
10.13196/j.cims.2021.06.015
中图分类号：
学科分类号：
摘要：
To address the problem of service workflow delay optimization and workflow task execution failure in Mobile Edge Computing (MEC) environment, a Fault Tolerant Immune Particle Swarm Optimization Scheduling Algorithm (FT-IPSO) for service workflow was proposed. The Heterogeneous Earliest Finish Time (HEFT) algorithm was used to calculate the weight of task and generate the ready queue. The mixed fault-tolerant strategy was added to the service workflow scheduling process to ensure the workflow continue to execute after the task fails. The particle swarm optimization algorithm was used to quickly find the optimal scheduling scheme and incorporates an immune algorithm to ensure the global optimization of the particle. To map out the scheduling position of the prime and backup version of task, the encoding scheme had been redesigned using integer. The task was scheduled according to the optimal scheduling scheme obtained by the algorithm. The simulation result showed that FT-IPSO algorithm reduced the service task failure rate and optimizes the service delay about 4.1%, 6.3% and 9.1% compared with the RFTA, CRCH and C-HEFT algorithms respectively. © 2021, Editorial Department of CIMS. All right reserved.
引用
收藏
页码：1683 / 1702
页数：19
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