Hyper-Heuristic Task Scheduling Algorithm Based on Reinforcement Learning in Cloud Computing

作     者：Lei Yin Chang Sun Ming Gao Yadong Fang Ming Li Fengyu Zhou 

作者机构：School of Control Science and EngineeringShandong UniversityJinan250061ShandongChina School of SoftwareShandong UniversityJinan250101ShandongChina Academy of Intelligent InnovationShandong UniversityShunhua RoadJinan250101ShandongChina Inspur Cloud Information Technology Co.Ltd.Inspur GroupJinan250101ShandongChina 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第37卷第8期

页      面：1587-1608页

核心收录：

学科分类：08[工学] 081104[工学-模式识别与智能系统] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the National Key R&D Program of China under Grant 2017YFB1302400 the Jinan“20 New Colleges and Universities”Funded Scientific Research Leader Studio under Grant 2021GXRC079 the Major Agricultural Applied Technological Innovation Projects of Shandong Province underGrant SD2019NJ014 the Shandong Natural Science Foundation under Grant ZR2019MF064 the Beijing Advanced Innovation Center for Intelligent Robots and Systems under Grant 2019IRS19. 

主　　题：Task scheduling cloud computing hyper-heuristic algorithm makespan optimization 

摘      要：The solution strategy of the heuristic algorithm is pre-set and has good performance in the conventional cloud resource scheduling process.However,for complex and dynamic cloud service scheduling tasks,due to the difference in service attributes,the solution efficiency of a single strategy is low for such problems.In this paper,we presents a hyper-heuristic algorithm based on reinforcement learning(HHRL)to optimize the completion time of the task sequence.Firstly,In the reward table setting stage of HHRL,we introduce population diversity and integrate maximum time to comprehensively deter-mine the task scheduling and the selection of low-level heuristic strategies.Secondly,a task computational complexity estimation method integrated with linear regression is proposed to influence task scheduling priorities.Besides,we propose a high-quality candidate solution migration method to ensure the continuity and diversity of the solving process.Compared with HHSA,ACO,GA,F-PSO,etc,HHRL can quickly obtain task complexity,select appropriate heuristic strategies for task scheduling,search for the the best makspan and have stronger disturbance detection ability for population diversity.