Dimensioning the relationship between availability and data center energy flow metrics
Keywords:Availability --- Data centers --- Energy flow model --- colored petri nets
AbstractThe advancement of technology and the growing number of applications available to network users have increased the demand for services hosted in cloud environments. In 2020, more than 4 billion of people access these services through the Internet, a value 7% higher in comparison to the same period in 2019. To support the demand for such services, an environment that provides such conditions for applications available whenever needed has grown in importance. These environments are generally available from large data centers, which consume large amounts of electricity to provide such demand service capacity. In this context, this work proposes an integrated and dynamic strategy that demonstrates the impact of the availability on the energy
consumption of the devices that compose the data center system architecture. In order to accomplish this, colored Petri net models were proposed for quantifying the cost, environmental impact and availability of the electric energy infrastructure ofdata centers. The models presented in this work are supported by the developed prototype. Two case studies illustrate the applicability of the proposed models and strategy. Significant results were obtained, showing an increase close to 100% in the system availability, with practically the same operational cost and environmental impact.
KEMP, S. Digital 2020: 3.8 billion people use social media. We are social, 2020.
CHANGCHIT, C.; CHUCHUEN, C. Cloud computing: An examination of factors impacting users’ adoption. Journal of Computer Information Systems, Taylor & Francis, v. 58, n. 1, p. 1-9, 2018.
LAWLER, J.; JOSEPH, A.; HOWELL-BARBER, H. H.-B. A case study of determinants of an effective cloud computing strategy. Review of Business Information Systems (RBIS), v. 16, n. 3, p. 145-156, 2012.
MELL, P.; GRANCE, T. Draft nist working definition of cloud computing. Referenced on June. 3rd, v. 15, n. 32, p. 2, 2009.
UZAMAN, S. K. et al. A systems overview of commercial data centers: initial energy and cost analysis. International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, v. 14, n. 1, p. 42-65, 2019.
POESS, M.; NAMBIAR, R. O. Energy cost, the key challenge of today’s data centers: A power consumption analysis of tpc-c results. Proc. VLDB Endow., VLDB Endowment, v. 1, n. 2, p. 1229-1240, ago. 2008.
BUYYA, R.; VECCHIOLA, C.; SELVI, S. T. Mastering Cloud Computing: Foundations and Applications Programming. 1st. ed. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2013.
CALLOU, G. et al. Energy consumption and execution time estimation of embedded system applications. Microprocessors and Microsystems, Elsevier, v. 35, n. 4, p. 426-440, 2011.
ANDRADE, E. et al. Availability modeling and analysis of a disaster-recovery-as-a-service solution. Computing, Springer, p. 1-26, 2017.
TALEBBERROUANE, M.; KHAN, F.; LOUNIS, Z. Availability analysis of safety critical systems using advanced fault tree and stochastic petri net formalisms. Journal of Loss Prevention in the Process Industries, Elsevier, v. 44, p. 193-203, 2016.
MELO, C. et al. Capacity-oriented availability model for resources estimation on private cloud infrastructure. In: IEEE. Dependable Computing (PRDC), 2017 IEEE 22nd Pacific Rim International Symposium on. [S.l.], 2017. p. 255-260.
ROCHA, É. et al. Analyzing the impact of power infrastructure failures on cloud application availability. In: IEEE.
Systems, Man, and Cybernetics (SMC), 2017 IEEE International Conference on. [S.l.], 2017. p. 1746-1751.
LIU, Y. et al. A colored generalized stochastic petri net simulation model for service reliability evaluation of active-active cloud data center based on it infrastructure. In: IEEE. 2017 2nd International Conference on System Reliability and Safety (ICSRS). [S.l.], 2017. p. 51-56.
SAMPAIO, A. M.; BARBOSA, J. G. A comparative cost analysis of fault-tolerance mechanisms for availability on the cloud. Sustainable Computing: Informatics and Systems, Elsevier, v. 19, p. 315-323, 2018.
FERREIRA, J. et al. An algorithm to optimise the energy distribution of data centre electrical infrastructures. International Journal of Grid and Utility Computing, Inderscience Publishers (IEL), v. 11, n. 3, p. 419-433, 2020.
VALENTIM, T.; CALLOU, G. A model-based strategy for quantifying the impact of availability on the energy flow of data centers. The Journal of Supercomputing, Springer, p. 1-24, 2020.
HEADQUARTERS, A. Cisco data center infrastructure 2.5 design guide. Cisco Validated Design I. Cisco Systems, Inc, 2007.
MURATA, T. Petri nets: Properties, analysis and applications. Proceedings of the IEEE, IEEE, v. 77, n. 4, p. 541-580, 1989.
MILNER, R. The definition of standard ML: revised. [S.l.]: MIT press, 1997.
JENSEN, K.; KRISTENSEN, L. M.; WELLS, L. Coloured petri nets and cpn tools for modelling and validation of concurrent systems. International Journal on Software Tools for Technology Transfer, Springer, v. 9, n. 3-4, p. 213-254, 2007.
JENSEN, K. A brief introduction to coloured petri nets. In: SPRINGER. International Workshop on Tools and Algorithms for the Construction and Analysis of Systems. [S.l.], 1997. p. 203-208.
JENSEN, K.; KRISTENSEN, L. M. Coloured Petri nets: modelling and validation of concurrent systems. [S.l.]: Springer Science & Business Media, 2009.
CALLOU, G. R. d. A. Assessment to support the planning of sustainable data centers with high availability. [S.l.]: Universidade Federal de Pernambuco, 2013.
AVIZIENIS, A. et al. Fundamental concepts of dependability. [S.l.]: University of Newcastle upon Tyne, Computing Science, 2001.
DINCER, I. Thermodynamics, exergy and environmental impact. Energy sources, Taylor & Francis, v. 22, n. 8, p. 723-732, 2000.
SCHMIDT, D. Low exergy systems for high-performance buildings and communities. Energy and Buildings, Elsevier, v. 41, n. 3, p. 331-336, 2009.
AVELAR, V. Comparing availability of various rack power redundancy configurations. APC White Paper, v. 48, p. 1-22, 2003.
IEEE Gold Book 473, Design of Reliable Industrial and Commercial Power Systems. [S.l.: s.n.], 2010.
HEWLETT-PACKARD. Hp power advisor tool. 2013. hhttp://h18004.www1.hp.com/products/solutions/poweri