References

  1. AnyLogic (2000): AnyLogic: Multimethod Simulation Software. Available at http://www.anylogic.com/.
  2. M. Arregoces & M. Portolani (2003): Data Center Fundamentals. Cisco Press, Indianapolis.
  3. L. Barroso & U. Hölzle (2007): The case for energy-proportional computing. Computer 40(12), pp. 33–37, doi:10.1109/MC.2007.443.
  4. L. Benini, A. Bogliolo & G.D. Micheli (2000): A survey of design techniques for system-level dynamic power management. IEEE Transactions on Very Large Scale Integration (VLSI) Systems 8(3), pp. 299–316, doi:10.1109/92.845896.
  5. F. van den Berg, B. Haverkort & J. Hooman (2016): Efficiently Computing Latency Distributions by Combined Performance Evaluation Techniques. In: Proceedings of the 9th EAI International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS'15. ICST, pp. 158––163, doi:10.4108/eai.14-12-2015.2262725.
  6. F. van den Berg, J. Hooman, A. Hartmanns, B. Haverkort & A. Remke (2015): Computing Response Time Distributions Using Iterative Probabilistic Model Checking. In: EPEW, Lecture Notes in Computer Science 9272. Springer, pp. 208–224, doi:10.1007/978-3-319-23267-6_14.
  7. F. van den Berg, A. Remke & B. Haverkort (2014): A domain specific language for performance evaluation of medical imaging systems. In: MCPS 2014, OASICS 36. Schloss Dagstuhl, pp. 80–93, doi:10.4230/OASIcs.MCPS.2014.80.
  8. F. van den Berg, A. Remke & B. Haverkort (2015): iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems. In: EPEW, LNCS 9272. Springer, pp. 227–242, doi:10.1007/978-3-319-23267-6_15.
  9. R. Calheiros, R. Ranjan, A. Beloglazov, C. De Rose & R. Buyya (2011): CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience 41(1), pp. 23–50.
  10. Emerson Network Power (2009): Energy Logic: Reducing Data Center Energy Consumption by Creating Savings that Cascade Across Systems. White Paper of Emerson Electric Co.
  11. A. Gandhi (2013): Dynamic Server Provisioning for Data Center Power Management. Phd thesis. Carnegie Mellon University, doi:10.1.1.376.4361.
  12. A. Gandhi, M. Harchol-Balter & M. Kozuch (2012): Are sleep states effective in data centers?. In: Proc. of Int. Green Computing Conference. IEEE, pp. 1–10, doi:10.1109/IGCC.2012.6322260.
  13. A. Hartmanns & H. Hermanns (2009): A Modest approach to checking probabilistic timed automata. In: QEST. IEEE, pp. 187–196, doi:10.1109/QEST.2009.41.
  14. A. Hinton, M. Kwiatkowska, G. Norman & D. Parker: PRISM: A tool for automatic verification of probabilistic systems, doi:10.1007/11691372_29.
  15. J. Koomey (2011): Growth in data center electricity use 2005 to 2010. Oakland, CA: Analytics Press. August 1.
  16. N. Kroes (2012): Using ICT to build Sustainable Cities.
  17. K. Larsen, P. Pettersson & W. Yi (1997): UPPAAL in a nutshell. STTTT 1(1), pp. 134–152, doi:10.1007/s100090050010.
  18. J. Nolan (2010): “An Inconvenient Truth” Increases Knowledge, Concern, and Willingness to Reduce Greenhouse Gases. Environment and Behavior 42(5), pp. 643–658, doi:10.1177/0013916509357696.
  19. V. Petrucci, E. Carrera, O. Loques, J. Leite & D. Mossé (2011): Optimized Management of Power and Performance for Virtualized Heterogeneous Server Clusters. In: 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. IEEE, pp. 23–32, doi:10.1109/CCGrid.2011.15.
  20. E. Pinheiro, R. Bianchini, E. Carrera & T. Heath (2001): Load balancing and unbalancing for power and performance in cluster-based systems. Work. on compilers and operating systems for low power 180.
  21. B. Postema & B. Haverkort (2015): An AnyLogic Simulation Model for Power and Performance Analysis of Data Centres. In: M. Beltrán, W. Knottenbelt & J. Bradley: Computer Performance Engineering, Lecture Notes in Computer Science 9272. Springer International Publishing Switzerland, Madrid, Spain, pp. 258–272, doi:10.1007/978-3-319-23267-6_17.
  22. H. Van, F. Tran & J. Menaud (2010): Performance and Power Management for Cloud Infrastructures. In: 2010 IEEE 3rd International Conference on Cloud Computing. IEEE, pp. 329–336, doi:10.1109/CLOUD.2010.25.

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