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Issue No.02 - July-December (2013 vol.1)
pp: 215-228
Carlo Mastroianni , eco4cloud srl and ICAR-CNR, Rende
Michela Meo , Politecnico di Torino, Torino
Giuseppe Papuzzo , eco4cloud srl, Rende
ABSTRACT
Power efficiency is one of the main issues that will drive the design of data centers, especially of those devoted to provide Cloud computing services. In virtualized data centers, consolidation of Virtual Machines (VMs) on the minimum number of physical servers has been recognized as a very efficient approach, as this allows unloaded servers to be switched off or used to accommodate more load, which is clearly a cheaper alternative to buy more resources. The consolidation problem must be solved on multiple dimensions, since in modern data centers CPU is not the only critical resource: depending on the characteristics of the workload other resources, for example, RAM and bandwidth, can become the bottleneck. The problem is so complex that centralized and deterministic solutions are practically useless in large data centers with hundreds or thousands of servers. This paper presents $({\rm ecoCloud})$, a self-organizing and adaptive approach for the consolidation of VMs on two resources, namely CPU and RAM. Decisions on the assignment and migration of VMs are driven by probabilistic processes and are based exclusively on local information, which makes the approach very simple to implement. Both a fluid-like mathematical model and experiments on a real data center show that the approach rapidly consolidates the workload, and CPU-bound and RAM-bound VMs are balanced, so that both resources are exploited efficiently.
INDEX TERMS
Servers, Random access memory, Mathematical model, Virtual machining, Resource management, Probabilistic logic, Cloud computing,energy saving, Cloud computing, VM consolidation, data center
CITATION
Carlo Mastroianni, Michela Meo, Giuseppe Papuzzo, "Probabilistic Consolidation of Virtual Machines in Self-Organizing Cloud Data Centers", IEEE Transactions on Cloud Computing, vol.1, no. 2, pp. 215-228, July-December 2013, doi:10.1109/TCC.2013.17
REFERENCES
 [1] A. Beloglazov, J. Abawajy, and R. Buyya, "Energy-Aware Resource Allocation Heuristics for Efficient Management of Data Centers for Cloud Computing," Future Generation Computer Systems, vol. 28, no. 5, pp. 755-768, 2012. [2] L.A. Barroso and U. Hölzle, "The Case for Energy-Proportional Computing," IEEE Computer, vol. 40, no. 12, pp. 33-37, Dec. 2007. [3] G. Dasgupta, A. Sharma, A. Verma, A. Neogi, and R. Kothari, "Workload Management for Power Efficiency in Virtualized Data Centers," Comm. ACM, vol. 54, pp. 131-141, July 2011. [4] L. Hosman and B. Baikie, "Solar-Powered Cloud Computing Datacenters," IT Professional, vol. 15, no. 2, pp. 15-21, 2013. [5] M. Aggar, "Developers, Developers, Developers: Engaging the Missing Link in It Resource Efficiency," technical report, The Green Grid, Mar. 2013. [6] A. Greenberg, J. Hamilton, D.A. Maltz, and P. Patel, "The Cost of a Cloud: Research Problems in Data Center Networks," Proc. ACM SIGCOMM Computer Comm. Rev., vol. 39, no. 1, pp. 68-73, 2009. [7] M. Cardosa, M.R. Korupolu, and A. Singh, "Shares and Utilities Based Power Consolidation in Virtualized Server Environments," Proc. 11th IFIP/IEEE Integrated Network Management (IM '09), June 2009. [8] C. Mastroianni, M. Meo, and G. Papuzzo, "Self-Economy in Cloud Data Centers: Statistical Assignment and Migration of Virtual Machines," Proc. 17th Int'l European Conf. Parallel Processing (Euro-Par '11), pp. 407-418, Sept. 2011. [9] J.L. Deneubourg, S. Goss, N. Franks, A. Sendova-Franks, C. Detrain, and L. Chrétien, "The Dynamics of Collective Sorting: Robot-Like Ants and Ant-Like Robots," Proc. First Int'l Conf. Simulation of Adaptive Behavior on from Animals to Animats, pp. 356-363, 1990. [10] T. Hirofuchi, H. Ogawa, H. Nakada, S. Itoh, and S. Sekiguchi, "A Live Storage Migration Mechanism over Wan for Relocatable Virtual Machine Services on Clouds," Proc. Ninth IEEE/ACM Int'l Symp. Cluster Computing and the Grid (CCGrid '09), pp. 460-465, May 2009. [11] H. Liu, C.-Z. Xu, H. Jin, J. Gong, and X. Liao, "Performance and Energy Modeling for Live Migration of Virtual Machines," Proc. 20th Int'l Symp. High Performance Distributed Computing (HPDC '11), pp. 171-182, June 2011. [12] A. Khosravi, S. Garg, and R. Buyya, "Energy and Carbon-Efficient Placement of Virtual Machines in Distributed Cloud Data Centers," Proc. 19th Int'l Conf. Parallel Processing (Euro-Par '13), 2013. [13] M. Mazzucco, D. Dyachuk, and R. Deters, "Maximizing Cloud Providers" Revenues via Energy Aware Allocation Policies," Proc. 10th IEEE/ACM Int'l Symp. Cluster Computing and the Grid (CCGrid '10), pp. 131-138, May 2010. [14] S. Rivoire, P. Ranganathan, and C. Kozyrakis, "A Comparison of High-Level Full-System Power Models," Proc. Conf. Power Aware Computing and Systems (HotPower '08), Dec. 2008. [15] X. Fan, W.-D. Weber, and L.A. Barroso, "Power Provisioning for a Warehouse-Sized Computer," Proc. 34th Ann. Int'l Symp. Computer Architecture (ISCA '07), pp. 13-23, June 2007. [16] VMWare, "VMware vSphere 5.1 vMotion Architecture, Performance and Best Practices," technical report, VMWare tech. papers, http://www.vmware.com/resources/techresources 10305, Aug. 2012. [17] A. Verma, P. Ahuja, and A. Neogi, "pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems," Proc. ACM/IFIP/USENIX Ninth Int'l Middleware Conf. (Middleware '08), pp. 243-264, 2008. [18] M. Yue, "A Simple Proof of the Inequality FFD (L) $\le$ 11/9 OPT (L) + 1, for All L for the FFD Bin-Packing Algorithm," Acta Mathematicae Applicatae Sinica, vol. 7, no. 4, pp. 321-331, 1991. [19] K. Park and V.S. Pai, "CoMon: A Mostly-Scalable Monitoring System for Planetlab," ACM SIGOPS Operating Systems Rev., vol. 40, pp. 65-74, Jan. 2006. [20] A. Beloglazov and R. Buyya, "Energy Efficient Allocation of Virtual Machines in Cloud Data Centers," Proc. 10th IEEE/ACM Int'l Symp. Cluster Computing and the Grid (CCGrid '10), pp. 577-578, May 2010. [21] A. Beloglazov, R. Buyya, Y.C. Lee, and A.Y. Zomaya, "A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems," Proc. Advances in Computers, pp. 47-111, 2011. [22] L. Wang and S.U. Khan, "Review of Performance Metrics for Green Data Centers: A Taxonomy Study," The J. Supercomputing, pp. 1-18, Oct. 2011. [23] N. Greene et al., "White Paper on Digital Service Efficiency," technical report, eBay Inc., http://dse.ebay.com/sites/default/fileseBay-DSE-130305.pdf , Mar. 2013. [24] M. Patterson, S. Poole, C.-H. Hsu, D. Maxwell, W. Tschudi, H. Coles, D. Martinez, and N. Bates, "TUE, a New Energy-Efficiency Metric Applied at ORNL's Jaguar," Proc. Int'l Supercomputing Conf., 2013. [25] P. Graubner, M. Schmidt, and B. Freisleben, "Energy-Efficient Virtual Machine Consolidation," IT Professional, vol. 15, no. 2, pp. 28-34, 2013. [26] K. Schröder and W. Nebel, "Behavioral Model for Cloud Aware Load and Power Management," Proc. Int'l Workshop Hot Topics in Cloud Services (HotTopiCS '13), 2013. [27] Y. Chen, A. Das, W. Qin, A. Sivasubramaniam, Q. Wang, and N. Gautam, "Managing Server Energy and Operational Costs in Hosting Centers," ACM SIGMETRICS Performance Evaluation Rev., vol. 33, no. 1, pp. 303-314, June 2005. [28] D.M. Quan, R. Basmadjian, H. de Meer, R. Lent, T. Mahmoodi, D. Sannelli, F. Mezza, L. Telesca, and C. Dupont, "Energy Efficient Resource Allocation Strategy for Cloud Data Centres," Proc. 26th Int'l Symp. Computer and Information Sciences (ISCIS '11), pp. 133-141, Sept. 2011. [29] A. Gulati, A. Holler, M. Ji, G. Shanmuganathan, C. Waldspurger, and X. Zhu, "Vmware Distributed Resource Management: Design, Implementation, and Lessons Learned," VMware Technical J., https://labs.vmware.com/academic/publications gulati-vmtj-spring2012, Spring 2012. [30] K. Dhyani, S. Gualandi, and P. Cremonesi, "A Constraint Programming Approach for the Service Consolidation Problem," Proc. Int'l Conf. Integration of AI and OR Techniques in Constraint Programming (CPAIOR '10), pp. 97-101, June 2010. [31] A. Gandhi, V. Gupta, M. Harchol-Balter, and M.A. Kozuch, "Optimality Analysis of Energy-Performance Trade-Off for Server Farm Management," Performance Evaluation, vol. 67, no. 11, pp. 1155-1171, Nov. 2010. [32] A. Forestiero, C. Mastroianni, and G. Spezzano, "So-Grid: A Self-Organizing Grid Featuring Bio-Inspired Algorithms," ACM Trans. Autonomous and Adaptive Systems, vol. 3, no. 2,article 5, May 2008. [33] D. Barbagallo, E.Di Nitto, D.J. Dubois, and R. Mirandola, "A Bio-Inspired Algorithm for Energy Optimization in a Self-Organizing Data Center," Proc. First Int'l Conf. Self-Organizing Architectures (SOAR '09), pp. 127-151, Sept. 2009. [34] M. Marzolla, O. Babaoglu, and F. Panzieri, "Server Consolidation in Clouds through Gossiping," Proc. IEEE 12th Int'l Symp. a World of Wireless, Mobile and Multimedia Networks, pp. 1-6, June 2011. [35] H. Mi, H. Wang, G. Yin, Y. Zhou, D. Shi, and L. Yuan, "Online Self-Reconfiguration with Performance Guarantee for Energy-Efficient Large-Scale Cloud Computing Data Centers," Proc. IEEE Int'l Conf. Services Computing (SCC '10), pp. 514-521, July 2010. [36] L. Minas and B. Ellison, Energy Efficiency for Information Technology: How to Reduce Power Consumption in Servers and Data Centers. Intel Press, 2009. [37] S. Srikantaiah, A. Kansal, and F. Zhao, "Energy Aware Consolidation for Cloud Computing," Proc. USENIX Workshop Power Aware Computing and Systems, Dec. 2008. [38] N. Bobroff, A. Kochut, and K. Beaty, "Dynamic Placement of Virtual Machines for Managing SLA Violations," Proc. 10th IFIP/IEEE Int'l Symp. Integrated Network Management (IM '07), 2007. [39] T. Ferreto, M. Netto, R. Calheiros, and C. De Rose, "Server Consolidation with Migration Control for Virtualized Data Centers," Future Generation Computer Systems, vol. 27, no. 8, pp. 1027-1034, 2011. [40] S. Mehta and A. Neogi, "ReCon: A Tool to Recommend Dynamic Server Consolidation in Multi-Cluster Data Centers," Proc. IEEE Network Operations and Management Symp. (NOMS), 2008. [41] F. Hermenier, X. Lorca, J.-M. Menaud, G. Muller, and J. Lawall, "Entropy: A Consolidation Manager for Clusters," Proc. ACM SIGPLAN/SIGOPS Int'l Conf. Virtual Execution Environments (VEE), 2009. [42] K. Le, O. Bilgir, R. Bianchini, M. Martonosi, and T.D. Nguyen, "Managing the Cost, Energy Consumption, and Carbon Footprint of Internet Services," ACM SIGMETRICS Performance Evaluation Rev., vol. 38, pp. 357-358, June 2010. [43] S.K. Garg, C.S. Yeo, A. Anandasivam, and R. Buyya, "Environment-Conscious Scheduling of HPC Applications on Distributed Cloud-Oriented Data Centers," J. Parallel and Distributed Computing, vol. 71, pp. 732-749, June 2011.
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