云计算环境下虚拟机服务质量保证和评估方法:研究综述

郝佳 张彬彬 岳昆

引用本文:
Citation:

云计算环境下虚拟机服务质量保证和评估方法:研究综述

    作者简介: 郝佳(1993-),女,云南人,博士生,研究方向为云计算与海量数据分析.E-mail:729897483@qq.com.;
    通讯作者: 岳昆, kyue@ynu.edu.cn
  • 基金项目:

    国家自然科学基金(61472345,61402398)

    云南大学青年英才培育计划(WX173602)

    云南大学理(工)科校级科研基金(2017YDJQ06).

A survey of approaches for QoS guarantee measurement of virtual machines in cloud computing environment

    Corresponding author: YUE Kun, kyue@ynu.edu.cn
  • 摘要: 云计算是一种按需付费的资源使用模式.它通过虚拟化技术,向用户提供具有服务质量保证的计算、存储以及网络资源.然而,与物理服务器相比,虚拟化环境的特点使得虚拟机的服务质量(Quality of Service,QoS)难以保证,例如,虚拟化技术本身的限制、虚拟机上所运行的应用的行为难以被准确预测、虚拟机性能评估困难、以及虚拟机行为监控困难等.分析上述困难,阐述学界对虚拟机服务质量保证的研究现状,总结对易于量化的QoS指标及难以量化的QoS指标的评估和保证方法.最后,总结与虚拟机QoS相关的问题,并展望未来的研究方向和亟待解决的问题.
  • [1] DANILOV A,ANDERSEN J, MOLODKINA.The NIST definition of cloud computing[J].Communications of the ACM,2011,53:50.DOI: 10.6028/NIST.SP.800-145.
    [2] ZHANG J,GU Z,ZHENG C.Survey of research progress on cloud computing[J].Application Research of Computers,2010,27(2):429-433.
    [3] JIANG Y M,LAN J L,ZHOU H Q.Resource monitoring policy for network virtualization environment[J].Journal of Electronics & Information Technology,2014,36(3):708-714.
    [4] LU C Z,YE K J,XU G Y,et al.Imbalance in the cloud:An analysis on Alibaba cluster trace[J].BigData,2017:2884-2892.
    [5] LI H R.The research and implementation of resource monitoring based on openstack virtual machine[D].Beijing:Beijing University of Posts and Telecommunications,2017.
    [6] ZHONG A,JIN H,SONG W.Performance implications of non-uniform VCPU-PCPU mapping in virtualization environment[J].Cluster Computing,2013,16(3):347-358.
    [7] WANG K,HOU Z F.An idle virtual CPU scheduling algorithm on Xen virtual machines[J].Journal of Computer Research and Development,2013,50(11):2429-2435.
    [8] ZHOU J C,ZHANG H Y,ZHA W L,et al.User-aware resource provision policy for cloud computing[J].Journal of Computer Research and Development.2014,51(5):1108-1119.
    [9] ROSENBLUM M,GARFINKEL l T.Virtual machine monitors:current technology and future trends[J].IEEE Computers,2005,38(5):39-47.
    [10] QIN Z Y,SHEN R S,ZHANG Q F,et al.Survey on virtual machine system security[J].Application Research of Computers,2012,9(5):1618-1622.
    [11] ZHU J,LI J,ZHUANG Y.Utility-based virtual cloud resource allocation model and algorithm in cloud computing[J].International Journal of Grid & Distributed Computing,2015,8:177-190.
    [12] ZHOU W Y,CHEN H P,YANG S B,et al.Resource scheduling in virtual machine cluster based on live migration of virtual machine[J].Journal of Huazhong University of Science and Technology:Nature Sciences,2011,39(S1):130-133.
    [13] CHEN P,NOBLE B.When virtual is better than real[C].Proceedings of the Workshop on Hot Topics in Operating Systems,2011:20-23.
    [14] ZENG W Q,YE J W,YANG Y,et al. VM s performance analysis based on application service[J].Computer Engineering and Design,2014(10):3631-3638.
    [15] IBRAHIM S,HE B,JIN H.Towards pay-as-you-consume cloud computing[C].Proceedings of the International Conference on Services Computing,2011:370-377.
    [16] LIN J,CHEN C.Interference-aware virtual machine placement in cloud computing systems[C].Proceedings of the International Conference on Computer & Information Science,2012:598-603.
    [17] CHIANG R,HUANG H.Tracon:Interference-aware scheduling for data-intensive applications in virtualized environments[C].Proceedings of the International Conference for High Performance Computing,Networking,Storage and Analysis,2011:1-12.
    [18] NATHUJI R,KANSAL A,GHAFFARKHAH A.Q-clouds:managing performance interference effects for qos-aware clouds[C].Proceedings of the 5th European Conference on Computer Systems,2010:237-250.
    [19] TICKOO O,IYER R,ILLIKKAL R.Modeling virtual machine performance:challenges and approaches[J].ACM Sigmetrics Performance Evaluation Review,2009,37(3):55-60.
    [20] 张建勋,古志民,郑超.云计算研究进展综述[J].计算机应用研究,2010,27(2):429-433.
    [21] KOH Y,KNAUERHASE Y,BRETT P.An analysis of performance interference effects in virtual environments[C].Proceedings of the International Symposium on Performance Analysis of Systems & Software,2007:200-209.
    [22] NOVAKOVIC D,VASIC N,OVAKOVIC S.Deep dive:Transparently identifying and managing performance interference in virtualized environments[C].Proceedings of the USENIX Conference on Annual Technical Conference,2013:219-230.
    [23] CALHEIROS R,RANJAN R,BUYYA R.Virtual machine provisioning based on analytical performance and QoS in cloud computing environments[C].Proceedings of the International Conference on Parallel Processing,2011:295-304.
    [24] FRANK Y,HYEONG K.Enabling consolidation and scaling down to provide power management for cloud computing[C].Proceedings of the USENIX Conference on Hot Topics in Cloud Computing,2011:14.
    [25] BARHAM P,DRAGOVIC B,FRASER K.Xen and the art of virtualization[C].Proceedings of ACM Symposium on Operating Systems Principles,2003:164-177.
    [26] ZHANG W,LIU J,LIU C.Workload modeling for virtual machine-hosted application[J].Expert Systems with Applications,2015,42(4):1835-1844.
    [27] LUO Z,QIAN Z.Burstiness-aware server consolidation via queuing theory approach in a computing cloud[C].Proceedings of the International Symposium on Parallel & Distributed Processing,2013:332-341.
    [28] QUIROZ A,KIM H,PARASHAR M.Towards autonomic workload provisioning for enterprise grids and clouds[C].Proceedings of the International Conference on Grid Computing,2009:50-57.
    [29] SHYAM G,MANVI S. Virtual resource prediction in cloud environment:A Bayesian approach[J].Journal of Network & Computer Applications,2016(65):144-154.
    [30] GAREY M,JOHNSON D.Computers and intractability:A guide to the theory of NP-Completeness[M].W H Freeman,1979.
    [31] KOUSIOURIS G,CUCINOTTA T,VARVARIGOU T.The effects of scheduling,workload type and consolidation scenarios on virtual machine performance and their prediction through optimized artificial neural networks[J].Journal of Systems & Software,2011,84(8):1270-1291.
    [32] HAO J,ZHANG B,YUE K.Performance measurement and configuration optimization of virtual machines based on the bayesian network[C].Proceedings of the 3rd International Conference on Cloud Computing and Security,2017:641-652.
    [33] LI F,YANG D,ZHOU P.Modeling application performance in a virtualized environment[J].Computer Systems & Applications,2015(24):9-15.
    [34] KRAFT S,CASALE G,KRISHNAMURTHY D.I/O performance prediction in consolidated virtualized environments[C].Proceedings of the International Conference on Performance Engineering,2011:295-306.
    [35] KUNDU S,RANGASWAMI R,DUTTA K.Application performance modeling in a virtualized environment[C].Proceedings of the International Symposium on High Performance Computer Architecture,2010:1-10.
    [36] WANG R.A virtual data center design and implementation of dynamic performance control system[D].Shanghai:Shanghai Jiaotong University,2011.
    [37] XIONG H,WANG C.Cloud application classification and fine-grained resource provision based on prediction[J].Journal of Computer Applications,2013,33(6):1534-1539.
    [38] 江逸茗,兰巨龙,周慧琴.网络虚拟化环境下的资源监控策略[J].电子与信息学报,2014,36(3):708-714.
    [39] 李浩然. OpenStack虚拟机资源监控关键技术的研究与实现[D].北京:北京邮电大学,2017.
    [40] MENG X,PAPPAS V,ZHANG L.Improving the scalability of data center networks with traffic-aware virtual machine placement[C].Proceedings of the 29th Conference on Information Communications,2010:1154-1162.
    [41] GUPTA D,CHERKASOVA L,GARDNER R.Enforcing performance isolation across virtual machines in Xen[C].Proceedings of the USENIX International Conference on Distributed System Platform,2006:342-362.
    [42] CUCINOTTA T,GIANI D,FAGGIOLI D.Providing performance guarantees to virtual machines using real-time scheduling[C].Proceedings of the Workshop on Virtualization & High-Performance Cloud Computing,2010:657-664.
    [43] 王凯,侯紫峰.Xen虚拟CPU空闲调度算法[J].计算机研究与发展,2013,50(11):2429-2435.
    [44] LI B,GUO S,WU Y. Construction and resource allocation of Cost-Efficient clustered virtual network in software defined networks[J].Journal of Grid Computing,2017(4):1-17.
    [45] ELI C,ANAND B,ALEXANDRE M.Resource central:understanding and predicting workloads for improved resource management in large cloud platforms[C].Proceedings of the Symposium on Operating System Principles,2017:153-167.
    [46] LU C,YE K,XU G.Imbalance in the cloud:An analysis on alibaba cluster trace[C].Proceedings of the IEEE International Conference on Big Data,2017:2884-2892.
    [47] MORSHEDLOU H,MEYBODI M.Decreasing impact of SLA violations:a proactive resource allocation approach for cloud computing environments[J].IEEE Transactions on Cloud Computing,2014,2(2):156-167.
    [48] WU L,GARG K,BUYYA R.SLA-based resource allocation for software as a service provider(SaaS) in cloud computing environments[C].Proceedings of the International Symposium on Cluster,Cloud and Grid Computing,2011:195-204.
    [49] SAGBO K,HOUNGUE P.Quality architecture for resource allocation in cloud computing[J].Service-oriented and Cloud Computing,2012(7592):154-168.
    [50] ERGU D,KOU G,PENG Y.The analytic hierarchy process:task scheduling and resource allocation in cloud computing environment[J].Journal of Supercomputing,2013,64(3):835-848.
    [51] EMEAKAROHA V,BRANDIC I.SLA-aware application deployment and resource allocation in clouds[C].Proceedings of the Computer Software and Applications Conference Workshops,2011:298-303.
    [52] DELIMITROU C,KOZYRAKIS C.Quasar:resource-efficient and QoS-aware cluster management[C].Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems,2014:127-144.
    [53] 周景才,张沪寅,查文亮,等.云计算环境下基于用户行为特征的资源分配策略[J].计算机研究与发展,2014,51(5):1108-1119.
    [54] RAJAN K,KAKADIA D,CURINO C.Perf orator:Eloquent performance models for resource optimization[C].Proceedings of the ACM Symposium on Cloud Computing,2016:415-427.
    [55] RUIU P,CARAGNANO G,GRAGLIA L.Automatic dynamic allocation of cloud storage for scientific applications[C].Proceedings of the International Conference on Complex,Intelligent,and Software Intensive Systems,2015:209-216.
    [56] XIA Q,LAN Y,XIAO L.Scheduling resource of IaaS clouds for energy saving based on predicting the overloading status of physical machines[C].Proceedings of the International Conference on Algorithms and Architectures for Parallel Processing,2015(9523):211-221.
    [57] RAMEZANI F,NADERPOUR M,LU J.Handling uncertainty in cloud resource management using fuzzy Bayesian networks[C].Proceedings of the IEEE International Conference on Fuzzy system,2015:1-8.
    [58] SHYAM G,MANVI S.Virtual resource prediction in cloud environment:A Bayesian approach[J].Journal of Network & Computer Applications,2016(65):144-154.
    [59] YAN C,LI Z,YU X.Bayesian networks-based selection algorithm for virtual machine to be migrated[C].Big Data and Cloud Computing,2016:573-578.
    [60] LI Z,YAN C,YU X.Bayesian network-based virtual machines consolidation method[C].Future Generation Computer Systems,2017:75-87.
    [61] REISS C,TUMANOV A,GANGER G R,et al.Heterogeneity and dynamicity of clouds at scale: Google trace analysis[C].ACM Symposium on Cloud Computing,2012:1-13.
    [62] MATLOOBI R,ZOMAYA Y.Managing performance degradation of collocated virtual machines in private cloud[C].Proceedings of the International Conference on High performance Computing and Communications,2017:128-135.
    [63] VINCENT C,EMEAKAROHA I,MICHAEL M.SLA-aware application deployment and resource allocation in clouds[C].Proceedings of the Computer Software & Application Conference Workshops,2011:298-303.
    [64] CURTIS A R,KESHAV S,LOPEZ-ORTIZ A.LEGUP:using heterogeneity to reduce the cost of data center network upgrades[C].ACM Conference on Emerging networking Experiments and Technology, 2010:1-12.
    [65] MHOUTI A E,ERRADI M,NASSEH A. Using cloud computing services in e-learning process:Benefits and challenges[J].Education & Information Technologies,2017(4):1-17.
    [66] AHAMED F,SHAHRESTANI S,JAVADI B.Security aware and energy-efficient virtual machine consolidation in cloud computing systems[C].Trustcom,2016:1516-1523.
    [67] 秦中元,沈日胜,张群芳,等.虚拟机系统安全综述[J].计算机应用研究,2012,9(5):1618-1622.
    [68] YADAV N,SINGH V,KUMARI M.Generalized reliability model for cloud computing[J].International Journal of Computer Applications,2014,88(14):13-16.
    [69] XU M,JIANG X,SANDHU R.Towards a VMM-based usage control framework for OS kernel integrity protection[C].Proceedings of lCACM Symposium on Access Control MODELS and Technologies,2007:71-80.
    [70] DENG W,LIU F,JIN H.Lifetime or energy:Consolidating servers with reliability control in virtualized cloud datacenters[C].Proceedings of the International Conference on Cloud Computing Technology and Science,2012:18-25.
    [71] LI J,CUI Y,MA Y.Modeling message queueing services with reliability guarantee in cloud computing environment using colored petri nets[C].Mathematical Problems in Engineering,2015:1-20.
    [72] JAYASINGHE D,PU C,EILAM T.Improving performance and availability of services hosted on IaaS clouds with structural constraint-aware virtual machine placement[C].Proceedings of IEEE International Conference on Services Computing,2011:72-79.
    [73] NACHI N.Characterizing cloud computing hardware reliability[C].Proceedings of ACM Symposium on Cloud Computing,2010:193-204.
    [74] YADA T,UEDA K.VM placement control considering network bandwidth for high availability distributed clusters[C].Proceedings of Asia-Pacific Conference on Communications,2018:1-6.
    [75] 周文煜,陈华平,杨寿保,等.基于虚拟机迁移的虚拟机集群资源调度[J].华中科技大学学报:自然科学版,2011,39(S1):130-133.
    [76] 曾文琦,叶家炜,杨阳,等. 面向应用服务的虚拟机性能评估[J].计算机工程与设计,2014(10):3631-3638.
    [77] HAMMER L,YAZIDI A,BEGNUM K.An inhomogeneous hidden markov model for efficient virtual machine placement in cloud computing environments[J].Journal of Forecasting,2017,36(4):407-420.
    [78] ANIS Y,FREDERIK UNG, HÄREK HAUGERUD.Effective live migration of virtual machines using partitioning and affinity aware-scheduling[J].Computers & Electrical Engineering,2018,69:240-255.
    [79] ALEXANDROV A,FOLKERTS E,SACHS K.Benchmarking in the cloud:What it should,can,and cannot be[C].Proceedings of TPC Technology Conference on Performance Evaluation & Benchmarking,2012:173-188.
    [80] TOMASZEK L.Model-driven development of virtual network embedding algorithms with model transformation and linear optimization techniques[C].MODEL,2018:39-54.
    [81] MINAROLLI D,FREISLEBEN B.Distributed resource allocation to virtual machines via artificial neural networks[C].Proceedings of Euromicro International Conference on Parallel,Distributed and Network-Based Processing,2014:490-499.
    [82] RADHAKRISHNAN A,KAVITHA V.Energy conservation in cloud data centers by minimizing virtual machines migration through artificial neural network[J].Concurrency and Computation:Practice and Experience,2016,98(11):1-18.
  • [1] 黄瑞锋 . 基于云计算政务网络安全集中管理. 云南大学学报(自然科学版), 2011, 33(S2): 260-263.
    [2] 冯韵李浩 . 一种基于银行模型的云计算资源定价算法研究. 云南大学学报(自然科学版), 2013, 35(S2): 178-. doi: 10.7540/j.ynu.2013b48
    [3] 沈济南胡俊鹏梁芳杨洁勇 . 基于API Hook的进程行为监控系统*. 云南大学学报(自然科学版), 2018, 40(3): 466-473. doi: 10.7540/j.ynu.20170399
    [4] 杨明华徐安士张遥郭磊 . 光突发交换及其服务质量分析. 云南大学学报(自然科学版), 2002, 24(5): 350-353.
    [5] 段杰新蒋文俊朱熙梅沙茜向文斌 . 准确定位 提高质量 服务产业. 云南大学学报(自然科学版), 2011, 33(S2): 141-143.
    [6] 温庆忠魏雪峰孔德昌赖兴会李世成丁福红 . 滇池流域森林生态服务功能价值评估. 云南大学学报(自然科学版), 2010, 32(3): 365-372 .
    [7] 李俊梅龚相澔张雅静段昌群高伟 . 滇池流域森林生态系统固碳释氧服务价值评估. 云南大学学报(自然科学版), 2019, 41(3): 629-637. doi: 10.7540/j.ynu.20180376
    [8] 李波黄鑫薛端侯严严裴以建 . 基于DTN的车载云计算卸载算法. 云南大学学报(自然科学版), 2018, 40(2): 215-221. doi: 10.7540/j.ynu.20170357
    [9] 李红星黄解军梁友嘉王欢张一驰 . 基于遥感生态指数的武汉市生态环境质量评估. 云南大学学报(自然科学版), 2020, 42(1): 81-90. doi: 10.7540/j.ynu.20190174
    [10] 许弟余焦善庆 . 对宇观天体和微观粒子质量-半径统一计算的注记. 云南大学学报(自然科学版), 2002, 24(4): 282-286.
    [11] 姜跃 . 基于云有序概念层次树的时间序列距离计算模型. 云南大学学报(自然科学版), 2003, 25(2): 115-120.
    [12] 杜云姜瑛 . 构件质量模型研究. 云南大学学报(自然科学版), 2011, 33(3): 281-288, .
    [13] 吴宗华赵东风 . 具有完全服务和门限服务的混合排队系统分析. 云南大学学报(自然科学版), 2007, 29(2): 132-135.
    [14] 赖裕平赵东风丁洪伟王明贵 . m级门限服务轮询系统队长特性分析. 云南大学学报(自然科学版), 2010, 32(6): 657-660 .
    [15] 施继红赵东风蔡光卉 . 多业务门限服务排队系统分析. 云南大学学报(自然科学版), 2003, 25(2): 105-109.
    [16] 王明贵赵东风丁洪伟赖裕平 . 服务2类业务的轮询系统性能分析. 云南大学学报(自然科学版), 2010, 32(2): 147-151 .
    [17] 丁世婷宋秀梅 . 期刊的编辑质量控制. 云南大学学报(自然科学版), 2011, 33(S2): 53-56.
    [18] 姜东慧廖微 . 《贵金属》的质量优化管理. 云南大学学报(自然科学版), 2011, 33(S2): 138-140.
    [19] 焦善庆许弟余周勋秀王蜀娟 . 光子静质量和光子结构. 云南大学学报(自然科学版), 2005, 27(6): 461-463,470.
    [20] 颜光前赵柳吴俊陈悦陈林裘之瑛 . 基于ABUS图像的轻量型切口疝补片计算机辅助检测与评估算法. 云南大学学报(自然科学版), 2017, 39(5): 768-779. doi: 10.7540/j.ynu.20160741
  • 加载中
计量
  • 文章访问数:  374
  • HTML全文浏览量:  75
  • PDF下载量:  102
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-06-30
  • 刊出日期:  2018-11-10

云计算环境下虚拟机服务质量保证和评估方法:研究综述

    作者简介:郝佳(1993-),女,云南人,博士生,研究方向为云计算与海量数据分析.E-mail:729897483@qq.com.
    通讯作者: 岳昆, kyue@ynu.edu.cn
  • 1. 云南大学 信息学院,云南 昆明 650500
基金项目:  国家自然科学基金(61472345,61402398) 云南大学青年英才培育计划(WX173602) 云南大学理(工)科校级科研基金(2017YDJQ06).

摘要: 云计算是一种按需付费的资源使用模式.它通过虚拟化技术,向用户提供具有服务质量保证的计算、存储以及网络资源.然而,与物理服务器相比,虚拟化环境的特点使得虚拟机的服务质量(Quality of Service,QoS)难以保证,例如,虚拟化技术本身的限制、虚拟机上所运行的应用的行为难以被准确预测、虚拟机性能评估困难、以及虚拟机行为监控困难等.分析上述困难,阐述学界对虚拟机服务质量保证的研究现状,总结对易于量化的QoS指标及难以量化的QoS指标的评估和保证方法.最后,总结与虚拟机QoS相关的问题,并展望未来的研究方向和亟待解决的问题.

English Abstract

参考文献 (82)

目录

    /

    返回文章
    返回