Holistic virtual machine scheduling in cloud datacenters towards minimizing total energy

Article English OPEN
Li, Xiang; Garraghan, Peter; Jiang, Xiaohong; Wu, Zhaohui; Xu, Jie;
(2018)

Energy consumed by Cloud datacenters has dramatically increased, driven by rapid uptake of applications and services globally provisioned through virtualization. By applying energy-aware virtual machine scheduling, Cloud providers are able to achieve enhanced energy eff... View more
  • References (35)
    35 references, page 1 of 4

    [1] R. Brown, E. Masanet, B. Nordman et al., Report to Congress on Server and Data Center Energy Efficiency: Public Law, 109-431 Berkeley: Lawrence Berkeley National Laboratory, technical report, 2008.

    [2] K. Jonathan, , 2011; http://www.analyticspress.com/datacenters.html [3] L. Christian, Projecting Annual new Datacenter Construction Market This paper presents an in-depth model capturing the oper- Size Technique report, Microsoft Corp., 2010.

    ational and thermal characteristics of Cloud datacenters. [4] L. A. Barroso, J. Clidaras, U. Hölzle, The Datacenter as a Computer: An We detail the methodology used to identify key parame- Introduction to the Design of Warehouse-Scale Machines Synthesis lecters for cooling model construction and validate its accu- tures on computer architecture, 2013, 8(3): 1-154.

    racy in simulation using realistic datacenter operational [5] Y. C. Lee and A. Y. Zomaya, Energy Efficient Utilization of Resources conditions. This model forms the foundation to propose a in Cloud Computing System The Journal of Supercomputing, 2012, vol.

    greedy-based VM scheduling algorithm named GRANITE. 60(2), pp. 268-280.

    It comprises two separated components: initial placement [6] A. Murtazaev, S. Oh, Sercon: Server Consolidation Algorithm Using and dynamic live migration that targets reducing total en- Live Migration of Virtual Machines for Green Computing IEEE Techergy cost of cooling and servers while minimizing the like- nical Review, 2011, 28(3): 212-231.

    lihood of SLA violation. The algorithm is evaluated against [7] T. C. Ferreto, M. Netto, R. Calheiros et al., Server Consolidation With numerous algorithms within CloudSim - a well-known Migration Control for Virtualized Data Future Generation tool for simulating Cloud datacenter. From the observa- Computer Systems, 2011, 27(8): 1027-1034.

    tions and experiment results presented within this paper, [8] J. Moore, J. Chase, P. Ranganathan et al., Making Scheduling cool : we draw the following conclusions. Temperature-Aware Workload Placement in Data Centers USENIX To our knowledge, this is the first paper that captures Annual Technical Conf., 2005.

    CRAC cooling, datacenter thermal characteristics, CPU [9] R. Zhou, Z. Wang, C. Bash et al., Data Center Cooling Management temperature and workload in a fine-grained manner. Our and Analysis-A Model Based Approach . Semiconductor Thermal Measmodel is capable of modeling server temperature by cap- urement and Management Symposium (SEMI-THERM), 2012: 98-103.

    turing thermal characteristics of datacenter holistically. [10] S. Shrivastava, B. Sammakia, R. Schmidt R et al., Comparative AnalyThis model can be used by researchers in order to evaluate sis of Different Data Center Airflow Management Configurations Proc.

  • Metrics
Share - Bookmark