Journal of Shandong University(Engineering Science) ›› 2020, Vol. 50 ›› Issue (4): 14-21.doi: 10.6040/j.issn.1672-3961.0.2018.210

• Machine Learning & Data Mining • Previous Articles     Next Articles

A scheduling algorithm based on multi-objective container cloud task

Xiaolan XIE(),Qi WANG*()   

  1. College of Information Science and Engineering, Guilin University of Technology, Guilin 541006, Guangxi, China
  • Received:2018-05-25 Online:2020-08-20 Published:2020-08-13
  • Contact: Qi WANG E-mail:237290696@qq.com;hanbingxzy@gmail.com

RichHTML

103

PDF (PC)

291

Abstract:

In order to solve the unrealistic, unfair, inefficient and unbalanced problems caused by container cloud scheduling model facing isomorphic tasks, isomorphic resources and single objectives, a tree scheduling objective model with constraint repair was proposed. Based on heterogeneous tasks and resources, constraint repair was adopted to avoid the impracticability of mapping scheme, and then priority to synthesize multiple sub-goals and attributed them to sub-spaces under different tree branches, and eventually achieved a fair, efficient, economical and balanced scheduling model among multiple upper application frameworks. The experimental results showed that the tree scheduling objective model with constrained repair was not inferior to other single-objective models in fairness, which could meet more tasks, and had higher resource utilization and load balancing under the preceding conditions. It was superior to the single-objective model in practicability, fairness, efficiency and balancing and ensured fair allocation of resources, which increased the benefits of container services, decreased the cost of physical resources, increased the stability and availability.

Key words: container cloud, scheduling, intelligent control, multi-object

CLC Number: 

  • TP391

Fig.1

Container cloud and related service hierarchy"

Fig.2

Resource allocation state migration"

Fig.3

Evaluation tree"

Fig.4

Fairness comparison"

Fig.5

Comparison of resource demand satisfaction"

Fig.6

Comparison of resource utilization"

Fig.7

Comparison of load balancing"

1 TOOSI A N , BUYYA R . Virtual networking with azure for hybrid cloud computing in aneka[J]. Research Advances in Cloud Computing, 2017, 93- 114.
2 KOZHIRBAYEV Z , SINNOTT R O . A performance comparison of container-based technologies for the cloud[J]. Future Generation Computer Systems, 2017, 68, 175- 182.
3 LI Y, ZHANG J, ZHANG W, et al. Cluster resource adjustment based on an improved artificial fish swarm algorithm in mesos[C]//IEEE International Conference on Signal Processing. Washington D C, USA: IEEE Computer Society, 2016: 1843-1847.
4 吴龙辉. Kubernetes实战[M]. 北京: 电子工业出版社, 2016: 2- 9.
5 崔广章, 朱志祥. 容器云资源调度策略的改进[J]. 计算机与数字工程, 2017, 45 (10): 1931- 1936.
CUI Guangzhang , ZHU Zhixiang . Improved container cloud resource scheduling policy[J]. Computer & Digital Engineering, 2017, 45 (10): 1931- 1936.
6 唐瑞.基于Kubernetes的容器云平台资源调度策略研究[D].成都:电子科技大学, 2017.
TANG Rui. Research on resources scheduling strategy of container cloud platform based on kubernetes[D]. Chengdu: University of Electronic Science and Technology of China, 2017.
7 杜威科.基于Kubemetes的大数据流式计算Spark平台设计与实现[D].南京:南京邮电大学, 2017.
DU Weike. Design and implementation of spark platformfor big data atreaming computing based on kubernetes[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2017.
8 柯尊旺, 于炯, 廖彬. 适应异构集群的Mesos多资源调度DRF增强算法[J]. 计算机应用, 2016, 36 (5): 1216- 1221.
KE Zunwang , YU Jiong , LIAO Bin . DRF enhanced algorithm for mesos multi resource scheduling adapted to heterogeneous clusters[J]. Computer Application, 2016, 36 (5): 1216- 1221.
9 冯兴杰, 贺阳. 基于节点性能的Hadoop作业调度算法改进[J]. 计算机应用与软件, 2017, (5): 223- 228.
FENG Xingjie , HE Yang . Improvement of scheduling algorithm on hadoop based on node performance[J]. Computer Applications and Software, 2017, (5): 223- 228.
10 杨晨.面向高性能计算的YARN平台关键技术与应用研究[D].南京:南京大学, 2016.
YANG Chen. Research on key technologies and application on yarn for high-performance computing[D]. Nanjing: Nanjin University, 2016.
11 魏赟, 陈元元. 基于改进蚁群算法的云计算任务调度模型[J]. 计算机工程, 2015, 41 (2): 12- 16.
WEI Yun , CHEN Yuanyuan . Cloud computing task scheduling model based on improved ant colony algorithm[J]. Computer Engineering, 2015, 41 (2): 12- 16.
12 CHO K M , TSAI P W , TSAI C W , et al. A hybrid meta-heuristic algorithm for vm scheduling with load balancing in cloud computing[J]. Neural Computing & Applications, 2015, 26 (6): 1- 13.
13 王永贵, 韩瑞莲. 基于改进蚁群算法的云环境任务调度研究[J]. 计算机测量与控制, 2011, 19 (5): 1203- 1205.
WANG Yonggui , HAN Ruilian . Study on cloud computing task schedule strategy based on maco algorithm[J]. Computer Measurement & Control, 2011, 19 (5): 1203- 1205.
14 张爱科, 谢翠兰. 基于公平性和负载均衡的云计算任务调度算法[J]. 计算机应用与软件, 2015, (2): 268- 271.
ZHANG Aike , XIE Cuilan . Task scheduling algorithm in cloud computing based on fairness and load balancing[J]. Computer Applications & Software, 2015, (2): 268- 271.
15 FANG Y, WANG F, GE J. A task scheduling algorithm based on load balancing in cloud computing[C]//International Conference on Web Information Systems and Mining. Berlin, Germany: Springer-Verlag, 2010: 271-277.
16 LIU Wanjuna , ZHANG Menghuab , GUO Wenyueb . Cloud computing resource schedule strategy based on mpsoalgorithm[J]. Computer Engineering, 2011, 37 (11): 42- 43.
17 YANG X, CHEN T, ZHANG Q. Research on cloud computing schedule based on improved hybrid PSO[C]//International Conference on Computer Science and Network Technology. Washington D C, USA: IEEE Computer Society, 2014: 388-391.
18 XIONG Y Y , WU Y Y . Cloud computing resource schedule strategy based on pso algorithm[J]. Applied Mechanics & Materials, 2014, 513-517, 1332- 1336.
19 LIU X , ZHANG X , LI W , et al. Swarm optimization algorithms applied to multi-resource fair allocation in heterogeneous cloud computing systems[J]. Computing, 2017, 99 (12): 1231- 1255.
20 WANG W , LIANG B , LI B . Multi-resource fair allocation in heterogeneous cloud computing systems[J]. IEEE Transactions on Parallel & Distributed Systems, 2015, 26 (10): 2822- 2835.
[1] Zhiyuan PAN,Chaonan LIU,Hongwei LI,Jing WANG,Wei WANG,Jing LIU,Xin ZHENG. Energy scheduling method of smart home integrated with photovoltaic units based on time-of-use pricing [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 111-116, 124.
[2] Dong YANG,Shiwen WANG,Yong WANG,Bo CHEN,Tianru ZHENG,Ning ZHOU,Tian XIAO,Yawen ZHAO. Optimal complementary photovoltaic capacity configuration for grid-connected wind farms expansion [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 44-51.
[3] Zhongwei ZHANG,Hongyan MEI,Jun ZHOU,Huiping JIA. A rule extraction method based on multi-objective co-evolutionarygenetic algorithm [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 122-130.
[4] Hongming LIU,Hongyan ZENG,Wei ZHOU,Tao WANG. Optimization of job shop scheduling based on improved particle swarm optimization algorithm [J]. Journal of Shandong University(Engineering Science), 2019, 49(1): 75-82.
[5] SONG Zhengqiang, YANG Huiling, XIAO Dan. Current and speed controllers driven by IPMSM based on online particle swarm optimization method [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(1): 112-116.
[6] WANG Fei, XU Jian, LI Wei, WANG Xinhao, SHI Xiaohan. Rolling optimal dispatch method of wind power based on distributed energy storage system [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 89-94.
[7] PEI Xiaobing, CHEN Huifen, ZHANG Baizhan, CHEN Menghui. Improved bi-variables estimation of distribution algorithms for multi-objective permutation flow shop scheduling problem [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(4): 25-30.
[8] DENG Guanlong, YANG Hongyong, ZHANG Shuning, GU Xingsheng. Multi-objective scheduling in no-wait flow shop using a hybridized differential evolution algorithm [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(5): 21-28.
[9] LIU Jinhui. Back analysis of parameters of a deep foundation pit based on multi-objective nonlinear function [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(4): 75-83.
[10] SHEN Xiaojing, CHEN Ming, CHI Tao. An novel information fusion algorithm of multi-Agent water quality monitoring system [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(4): 39-45.
[11] ZHANG Fei, GENG Hong-qin. Optimization of job-shop scheduling problem based on chaos particle swarm optimization algorithm [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2013, 43(3): 19-22.
[12] CHEN Ming-zhi1, 2, CHEN Jian3, XU Chun-yao3, YU Lun3, LIN Bo-gang1, 2. A new clustering algorithm for user access patterns based on network virtual environments [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(6): 43-49.
[13] ZHANG Qi-cong1, YANG Gong-ping2*. Study on Agent based simulation of banking queuing system [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(4): 68-72.
[14] LIU Chun-an. A dynamic multi-objective optimization evolutionary algorithm based on estimation of core distribution [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(1): 167-172.
[15] LI Jin-zhong1, XIA Jie-wu1, ZENG Jin-tao1, WANG Xiang2*. An optimization approach to grid workflow scheduling using improved SPEA2 algorithm [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(5): 12-16.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] WANG Su-yu,<\sup>,AI Xing<\sup>,ZHAO Jun<\sup>,LI Zuo-li<\sup>,LIU Zeng-wen<\sup> . Milling force prediction model for highspeed end milling 3Cr2Mo steel[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 1 -5 .
[2] ZHANG Yong-hua,WANG An-ling,LIU Fu-ping . The reflected phase angle of low frequent inhomogeneous[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 22 -25 .
[3] SHI Lai-shun,WAN Zhong-yi . Synthesis and performance evaluation of a novel betaine-type asphalt emulsifier[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 112 -115 .
[4] LAI Xiang . The global domain of attraction for a kind of MKdV equations[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 87 -92 .
[5] YU Jia yuan1, TIAN Jin ting1, ZHU Qiang zhong2. Computational intelligence and its application in psychology[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 1 -5 .
[6] LI Liang, LUO Qiming, CHEN Enhong. Graph-based ranking model for object-level search
[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 15 -21 .
[7] CHEN Rui, LI Hongwei, TIAN Jing. The relationship between the number of magnetic poles and the bearing capacity of radial magnetic bearing[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(2): 81 -85 .
[8] WANG Bo,WANG Ning-sheng . Automatic generation and combinatory optimization of disassembly sequence for mechanical-electric assembly[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 52 -57 .
[9] LI Ke,LIU Chang-chun,LI Tong-lei . Medical registration approach using improved maximization of mutual information[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 107 -110 .
[10] JI Tao,GAO Xu/sup>,SUN Tong-jing,XUE Yong-duan/sup>,XU Bing-yin/sup> . Characteristic analysis of fault generated traveling waves in 10 Kv automatic blocking and continuous power transmission lines[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 111 -116 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd