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DEEP-SaM - Energy-Efficient Provisioning Policies for Computing Environments

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 5745))

Abstract

The cost of electricity for datacenters is a substantial operational cost that can and should be managed, not only for saving energy, but also due to the ecologic commitment inherent to power consumption. Often, pursuing this goal results in chronic underutilization of resources, a luxury most resource providers do not have in light of their corporate commitments. This work proposes, formalizes and numerically evaluates DEEP-Sam, for clearing provisioning markets, based on the maximization of welfare, subject to utility-level dependant energy costs and customer satisfaction levels. We focus specifically on linear power models, and the implications of the inherent fixed costs related to energy consumption of modern datacenters and cloud environments. We rigorously test the model by running multiple simulation scenarios and evaluate the results critically. We conclude with positive results and implications for long-term sustainable management of modern datacenters.

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References

  1. Aiber, S., Gilat, D., Landau, A., Razinkow, N., Sela, A., Wasserkrug, S.: Autonomic Self-Optimization According to Business Objectives. In: ICAC 2004: Proceedings of the First International Conference on Autonomic Computing (ICAC 2004), pp. 206–213 (2004)

    Google Scholar 

  2. Bapna, R., Das, S., Garfinkel, R., Stallaert, J.: A Market Design for Grid Computing. INFORMS Journal of Computing (2006)

    Google Scholar 

  3. Bradbury, D.: Real Innovation - Building Canada’s largest green data centre. Backbone Magazine (2008)

    Google Scholar 

  4. Burge, J., Ranganathan, P., Wiener, J.L. (CASH’EM) Cost-Aware Scheduling for Heterogeneous Enterprise Machines. HP-Labs: http://www.hpl.hp.com/techreports/2007/HPL-2007-63.pdf (retrieved March 23, 2007)

  5. Buyya, R., Abramson, D., Venugopal, S.: The Grid Economy. In: Proceedings of the IEEE 93 Nr. 3 (2005)

    Google Scholar 

  6. Carr, N.: IT doesn’t matter. Harvard Business Review 81(5), 41–49 (2003)

    Google Scholar 

  7. Chen, G., Malkowski, K., Kandemir, M., Raghavan, P.: Reducing power with performance constraints for parallel sparse applications. In: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (2005)

    Google Scholar 

  8. Chun, B.N., Culler, D.E.: User-Centric Performance Analysis of Market-Based Cluster Batch Schedulers. In: Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid. IEEE Computer Society, Los Alamitos (2002)

    Google Scholar 

  9. Coskun, A.K., Rosing, T.S., Whisnant, K.: Temperature aware task scheduling in MPSoCs. In: Proceedings of the conference on Design, automation and test in Europe, EDA Consortium, Nice, France (2007)

    Google Scholar 

  10. Ganek, A.G., Corbi, T.A.: The dawning of the autonomic computing era. IBM SYSTEMS JOURNAL 42(1) (2003)

    Google Scholar 

  11. Hamann, H.F.: A Measurement-Based Method for Improving Data Center Energy Efficiency. In: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), vol. 00. IEEE Computer Society, Los Alamitos (2008)

    Google Scholar 

  12. Heath, T., Diniz, B., Carrera, E.V., Wagner Jr., M., Bianchini, R.: Energy conservation in heterogeneous server clusters. In: Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming. ACM, Chicago (2005)

    Google Scholar 

  13. Feitelson, D.G.: Workload Modeling for Performance Evaluation. In: Calzarossa, M.C., Tucci, S. (eds.) Performance 2002. LNCS, vol. 2459, pp. 114–141. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  14. Freeh, V.W., Lowenthal, D.K., Pan, F., Kappiah, N., Springer, R., Rountree, B.L.: Analyzing the Energy-Time Trade-Off in High-Performance Computing Applications. IEEE Trans. Parallel Distrib. Syst. 18(6), 835–848 (2007)

    Article  Google Scholar 

  15. Ferguson, D.F., Nikolaou, C., Sairamesh, J., Yemini, Y.: Economic models for allocating resources in computer systems. In: Market-based control: a paradigm for distributed resource allocation, pp. 156–183 (1996)

    Google Scholar 

  16. Kurp, P.: Green computing. Communications of the ACM 51(10), 11–13 (2008)

    Article  Google Scholar 

  17. Lefurgy, C., Rajamani, K., Rawson, F., Felter, W., Kistler, M., Keller, T.W.: Energy Management for Commercial Servers Computer 36(12), 39–48 (2003)

    Google Scholar 

  18. Martello, S., Toth, P.: Knapsack problems. John Wiley, Chichester (1990)

    MATH  Google Scholar 

  19. Mastroleon, L., Bambos, N., Kozyrakis, C., Economou, D.: Autonomic Power Management Schemes for Internet Servers and Data Centers. In: IEEE Global Telecommunications Conference, GLOBECOMM (2005)

    Google Scholar 

  20. Meisner, D., Gold, B.T., Wenisch, T.F.: PowerNap: eliminating server idle power. In: Proceeding of the 14th international conference on Architectural support for programming languages and operating systems. ACM, Washington (2009)

    Google Scholar 

  21. Mutz, A., Wolski, R., Brevik, J.: Eliciting honest value information in a batch-queue environment. In: 2007 8th IEEE/ACM International Conference on Grid Computing, pp. 291–297 (2007); Nielsen, L.S., Niessen, C.: Low-power operation using self-timed circuits and adaptive scaling of the supply voltage. IEEE Trans. Very Large Scale Integr. Syst. 2(4), 391–397 (1994)

    Google Scholar 

  22. Parkes, D.C., Kalagnanam, J., Eso, M.: Achieving Budget-Balance with Vickrey-Based Payment Schemes in Combinatorial Exchanges. In: IBM Research Report RC 22218 W0110-065 (2001)

    Google Scholar 

  23. Pinheiro, E., Bianchini, R., Carrera, E.V., Heath, T.: Load Balancing and Unbalancing for Power and Performance in Cluster-Based Systems. In: Workshop on Compilers and Operating Systems for Low Power (COLP) (2001)

    Google Scholar 

  24. Poggi, N., Moreno, T., Berral, J.L., Gavaldà, R., Torres, J.: Web customer modeling for automated session prioritization on high traffic sites. In: Conati, C., McCoy, K., Paliouras, G. (eds.) UM 2007. LNCS, vol. 4511, pp. 450–454. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  25. Püschel, T., Borissov, N., Macías, M., Neumann, D., Guitart, J., Torres, J.: Economically enhanced resource management for internet service utilities. In: Benatallah, B., Casati, F., Georgakopoulos, D., Bartolini, C., Sadiq, W., Godart, C. (eds.) WISE 2007. LNCS, vol. 4831, pp. 335–348. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  26. Raghavendra, P.: Optimal algorithms and inapproximability results for every CSP? In: Proceedings of the 40th annual ACM symposium on Theory of computing. ACM, Canada (2008)

    Google Scholar 

  27. Rasmussen, N.: Implementing Energy Efficient Data Centers. In: APC White Paper # 114 (2006)

    Google Scholar 

  28. Rivoire, S., Shah, M.A., Ranganathan, P., Kozyrakis, C.: JouleSort: a balanced energy-efficiency benchmark. In: Proceedings of the 2007 ACM SIGMOD international conference on Management of data. ACM, Beijing (2007)

    Google Scholar 

  29. Rusu, C., Melhem, R., Mosse, D.: Maximizing Rewards for Real-Time Applications with Energy Constraints. ACM Transactions on Embedded Computer Systems 2, 537–559 (2003)

    Article  Google Scholar 

  30. Schnizler, B., Neumann, D., Veit, D., Weinhardt, C.: Trading Grid Services - a Multi Attribute Combinatorial approach. European Journal of Operational Research 187(3), 943–961 (2008)

    Article  MATH  Google Scholar 

  31. See, S.: Is there a pathway to a Green Grid, http://www.ibergrid.eu/2008/presentations/Dia%2013/4.pdf (retrieved March 23, 2007)

  32. Sharma, R.K., Shih, R., Bash, C., Patel, C., Varghese, P., Mekanapurath, M., Velayudhan, S., Manu Kumar, V.: On building next generation data centers: energy flow in the information technology stack. In: Proceedings of the 1st Bangalore annual Compute conference. ACM, Bangalore (2008)

    Google Scholar 

  33. Shivle, S., Siegel, H.J., Maciejewski, A.A., Sugavanam, P., Banka, T., Castain, R., Chindam, K., Dussinger, S., Pichumani, P., Satyasekara, P., Saylor, W., Sendek, D., Sousa, J., Sridharan, J., Velazco, J.: Static Allocation of Resources to Communicating Subtasks in a Heterogeneous ad-hoc Grid Environment. Journal of Parallel and Distributed Computing 66(4) (2006)

    Google Scholar 

  34. Stoesser, J., Neumann, D., Weinhardt, C.: GreedEx- A Scalable Clearing Mechanism for Utility Computing. Electronic Commerce Research 8(4) (2008)

    Google Scholar 

  35. Waldsburger, C., Hogg, T., Huberman, B.A., Kephart, J.O., Stornetta, W.S.: Spawn: A Distributed Computational Economy. IEEE Transactions on Software Engineering 18(2), 103–117 (1992)

    Article  Google Scholar 

  36. Wolski, R., Plank, J.S., Brevik, J., Bryan, T.: Analyzing Market-Based Resource Allocation Strategies for the Computational Grid. International Journal of High Performance Computing Applications (2001)

    Google Scholar 

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Bodenstein, C., Püschel, T., Hedwig, M., Neumann, D. (2009). DEEP-SaM - Energy-Efficient Provisioning Policies for Computing Environments. In: Altmann, J., Buyya, R., Rana, O.F. (eds) Grid Economics and Business Models. GECON 2009. Lecture Notes in Computer Science, vol 5745. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03864-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-03864-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03863-1

  • Online ISBN: 978-3-642-03864-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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