Dynamic Scheduling of Cloud Resource Based on Control Theory of Distributed Discrete Event Systems

LIU Fuchun; HU Qin

doi:10.13976/j.cnki.xk.2017.0558

Volume 46 Issue 5

Oct. 2017

Turn off MathJax

Article Contents

Abstract

References

INFORMATION AND CONTROL > 2017 > 46(5): 558-563. > DOI: 10.13976/j.cnki.xk.2017.0558 CSTR: 32166.14.xk.2017.0558

LIU Fuchun, HU Qin. Dynamic Scheduling of Cloud Resource Based on Control Theory of Distributed Discrete Event Systems[J]. INFORMATION AND CONTROL, 2017, 46(5): 558-563. DOI: 10.13976/j.cnki.xk.2017.0558

Citation:

PDF (1693 KB)

Dynamic Scheduling of Cloud Resource Based on Control Theory of Distributed Discrete Event Systems

LIU Fuchun^,,
HU Qin

School of Computers, Guangdong University of Technology, Guangzhou 510006, China

More Information

Received Date: August 29, 2016
Revised Date: February 21, 2017
Accepted Date: November 12, 2016
Available Online: December 01, 2022
Published Date: October 19, 2017

Graphical Abstract

Abstract

Abstract

Given the complex dynamic and distributed nature of the cloud environment together with the discrete characteristic of cloud data center entities, we propose a dynamic scheduling strategy of cloud resources based on the distributed discrete event systems (DES) theory. First, we construct the cloud environment as a distributed DES composed of numerous subsystems, which include the physical server subsystem, the virtual machine subsystem, and the cloud task subsystem. Then, we apply supervisory control theory of distributed DESs to deal with the dynamic scheduling of the cloud resources. Through the control from local controllers and the information exchange between the global and local controllers, the proposed strategy achieves the overall optimization of the cloud resources and guarantees the rational allocation of the subsystems' resources. Moreover, the scheduling of the resources' load balancing improves the overall utilization of the cloud resources and the quality of the cloud service and enhances the performance of the entire cloud platform. Experiments indicate that with the increase in tasks, the proposed control strategy has obvious advantages in the utilization rate and the execution time compared with the traditional strategies.
- discrete event system,
- distributed system,
- cloud resource allocation,
- dynamic scheduling strategy

FullText(HTML)

References (20)

References

[1]	Mell P, Grance T. The NIST definition of cloud computing[J]. Communications of the ACM, 2010, 53(6):50. http://www.researchgate.net/publication/271589473_The_NIST_definition_of_cloud_computing
[2]	刘鹏.云计算[M].北京:电子工业出版社, 2010. Liu P. Cloud computing[M]. Beijing:Publishing House of Electronics Industry, 2010.
[3]	于雷.一种基于协作博弈的虚拟网络嵌入策略[J].信息与控制, 2016, 45(4):449-455. http://ic.sia.cn/CN/abstract/abstract12441.shtml Yu L. Virtual network embedding strategy based on cooperative game theory[J]. Information and Control, 2016, 45(4):449-455. http://ic.sia.cn/CN/abstract/abstract12441.shtml
[4]	龚素文, 艾浩军, 袁远明.基于迁移技术的云资源动态调度策略研究[J].计算机工程与应用, 2014, 50(5):51-54, 78. http://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201405012.htm Gong S W, Ai H J, Yuan Y M. Research of cloud resource dynamic scheduling strategy on migration technology[J]. Computer Engineering and Applications, 2014, 50(5):51-54, 78. http://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201405012.htm
[5]	肖鹏, 胡志刚.云环境中基于混合博弈的虚拟资源定价模型[J].计算机集成制造系统, 2014, 20(1):198-206. http://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201401026.htm Xiao P, Hu Z G. Hybrid game based virtual resource pricing model in cloud environment[J]. Computer Integrated Manufacturing Systems, 2014, 20(1):198-206. http://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201401026.htm
[6]	孙佳佳, 王兴伟, 高程希, 等.云环境下基于神经网络和群搜索优化的资源分配机制[J].软件学报, 2014, 25(8):1858-1872. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=rjxb201408018&dbname=CJFD&dbcode=CJFQ Sun J J, Wang X W, Gao C X, Huang M. Resource allocation scheme based on neural network and group search optimization in cloud environment[J]. Journal of Software, 2014, 25(8):1858-1872. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=rjxb201408018&dbname=CJFD&dbcode=CJFQ
[7]	Li K, Liu C, Li K, et al. A framework of price bidding configurations for resource usage in cloud computing[J]. IEEE Transactions on Parallel and Distributed Systems, 2016, 27(8):2168-2181. doi: 10.1109/TPDS.2015.2495120
[8]	Xiao Z, Song W, Chen Q. Dynamic resource allocation using virtual machines for cloud computing environment[J]. IEEE Transactions on Parallel and Distributed Systems, 2013, 24(6):1107-1117. doi: 10.1109/TPDS.2012.283
[9]	匡桂娟, 曾国荪.一种基于时分复用的云资源管理方法[J].同济大学学报, 2014, 42(5):782-789. http://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201405020.htm Kuang G J, Zeng G S. Time-division multiplexing-based cloud resource management methods[J]. Journal of Tongji University, 2014, 42(5):782-789. http://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201405020.htm
[10]	师雪霖, 徐格.云虚拟机资源分配的效用最大化模型[J].计算机学报, 2013, 36(2):252-262. http://www.cnki.com.cn/Article/CJFDTOTAL-JSJX201302004.htm Shi X L, Xu G. Utility maximization model of virtual machine scheduling in cloud environment[J]. Chinese Journal of Computers, 2013, 36(2):252-262. http://www.cnki.com.cn/Article/CJFDTOTAL-JSJX201302004.htm
[11]	胡芹, 刘富春.基于离散事件系统的云资源分配优化控制[J].广东工业大学学报, 2016, 33(1):29-35. http://www.cnki.com.cn/Article/CJFDTOTAL-GDGX201601006.htm Hu Q, Liu F C. Optimization control of cloud resource allocation based on DES[J]. Journal of Guangdong University of Technology, 2016, 33(1):29-35. http://www.cnki.com.cn/Article/CJFDTOTAL-GDGX201601006.htm
[12]	Cassandras C, Lafortune S. Introduction to discrete event systems[M]. New York, USA:Springer Science+Business Media LLC, 2008:199-211.
[13]	Schmidt K, Breindl C. Maximally permissive hierarchical control of decentralized discrete event systems[J]. IEEE Transactions on Automatic Control, 2011, 56(4):723-737. doi: 10.1109/TAC.2010.2067250
[14]	Liu F, Lin H. Reliable supervisory control for general architecture of decentralized discrete event systems[J]. Automatica, 2010, 46(9):1510-1516. doi: 10.1016/j.automatica.2010.06.011
[15]	刘富春.非确定型离散事件系统双模拟控制的实现[J].控制理论与应用, 2015, 32(1):75-79. http://www.cnki.com.cn/Article/CJFDTOTAL-KZLY201501010.htm Liu F C. Realization of bisimilarity control of nondeterministic discrete event systems[J]. Control Theory & Applications, 2015, 32(1):75-79. http://www.cnki.com.cn/Article/CJFDTOTAL-KZLY201501010.htm
[16]	向洁, 丁恩杰.基于虚拟机调度的数据中心节能优化[J].计算机应用, 2013, 33(12):3331-3353. http://youxian.cnki.com.cn/yxdetail.aspx?filename=WJFZ20171018012&dbname=CAPJ2015 Xiang J, Ding E J. Energy-saving optimization in datacenter based on virtual machine scheduling[J]. Journal of Computer Applications, 2013, 33(12):3331-3353. http://youxian.cnki.com.cn/yxdetail.aspx?filename=WJFZ20171018012&dbname=CAPJ2015
[17]	马汉达, 郝晓宇, 马仁庆.基于Hadoop的并行PSO-kmeans算法实现Web日志挖掘[J].计算机科学, 2015, 42(6A):470-473. http://www.cnki.com.cn/Article/CJFDTOTAL-JSJA2015S1115.htm Ma H D, Hao X Y, Ma Y Q. Parallel PSO-kmeans algorithm implementing web log mining based on Hadoop[J]. Computer Science, 2015, 42(6A):470-473. http://www.cnki.com.cn/Article/CJFDTOTAL-JSJA2015S1115.htm
[18]	Humane P, Varshapriya J N. Simulation of cloud infrastructure using CloudSim simulator:A practical approach for researchers[C]//International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials. Piscataway, NJ, USA:IEEE, 2015:207-211.
[19]	Miriam D D H, Easwarakumar K S. A double Min-Min algorithm for task metascheduler on hypercubic P2P grid systems[J]. International Journal of Computer Science Issues, 2010, 7(4):8-18. https://www.researchgate.net/profile/K_Easwarakumar/publication/46093648_A_Double_Min_Min_Algorithm_for_Task_Metascheduler_on_Hypercubic_P2P_Grid_Systems/links/543272b40cf22395f29c1001.pdf?origin=publication_detail
[20]	Hsieh S Y, Chen C T, Chen C H, et al. Novel scheduling algorithms for efficient deployment of map reduce applications in heterogeneous computing environments[J]. IEEE Transactions on cloud Computing, 2016:DOI10.1109/TCC. 2016.2552518. http://ieeexplore.ieee.org/document/7450666/

[1]	XIA Yuanqing, WANG Chao, GAO Runze, ZHAN Yufeng, SUN Zhongqi, DAI Li, ZHAI Dihua. Progress and Challenges of Cloud-network-edge-end Collaborative Cloud Control[J]. INFORMATION AND CONTROL, 2024, 53(3): 273-286. DOI: 10.13976/j.cnki.xk.2024.4007
[2]	ZHANG Chenlu, PENG Dongliang, FANG Tao, GU Yu. Resource Scheduling Method for Space-Based Early Warning System Based on GA-PSO Algorithm[J]. INFORMATION AND CONTROL, 2016, 45(2): 199-203,210. DOI: 10.13976/j.cnki.xk.2016.0199
[3]	CHEN Shengfeng, WEI Chengjian. Decentralized Multi-Factory Resource Scheduling Under the Environment of General Cost[J]. INFORMATION AND CONTROL, 2010, 39(5): 640-645.
[4]	LI Zu-xin, WANG Wan-liang, CHENG Xin-min. Message Scheduling and Asymptotic Stability of System with Resource Constraints[J]. INFORMATION AND CONTROL, 2008, 37(5): 593-598.
[5]	WANG Yan, JI Zhi-cheng, XIE Lin-bo, HU Wei-li. A Dynamic-Scheduling-Based Design Approach for Networked Control Systems[J]. INFORMATION AND CONTROL, 2008, 37(1): 73-80,86.
[6]	CAI Hua, WANG Yan, CHEN Qing-wei, HU Wei-li. A Variable-period Dynamic Scheduling Strategy for Networked Control Systems[J]. INFORMATION AND CONTROL, 2007, 36(3): 345-351.
[7]	LIANG Wei, YU Hai-bin. RESEARCH ON AND IMPLEMENTATION OF DYNAMIC PRODUCTION SCHEDULING MANAGEMENT SYSTEM[J]. INFORMATION AND CONTROL, 2002, 31(6): 504-507.
[8]	WU Naiqi. SUFFICIENT AND NECESSARY CONDITIONS FOR DEADLOCK AVOIDANCE IN FLEXIBLE MANUFACTURING SYSTEMS PART Ⅱ:POLICY OF DYNAMIC RESOURCE ALLOCATION[J]. INFORMATION AND CONTROL, 1995, 24(6): 343-355.
[9]	CHEN Lin, HU Zexin, SHAO Huihe. MIXED SCHEDULING STRATEGY FOR MULTI-LEVEL MULTI-PRODUCT BATCH PRO CESS AND ITS APPLICATIONS[J]. INFORMATION AND CONTROL, 1992, 21(1): 6-12.
[10]	YANG Zihou, ZHANG Houqi. CONTROL OF THE RESOURCES STARTING-UP OF FMS[J]. INFORMATION AND CONTROL, 1989, 18(6): 24-30.