Skip to main content

Advertisement

Springer Nature Link
Log in

A systematic literature review about integrating dependability attributes, performability and sustainability in the implantation of cooling subsystems in data center

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

In recent years, data centers (DCs) have evolved a lot, and this change is related to the advent of cloud computing, e-commerce, services aimed at social networks, and big data. Such architectures demand high availability, reliability, and performance at satisfactory service levels; requirements are often neglected at the expense of high costs. In addition, the use of techniques capable of promoting greater environmental sustainability is most often forgotten in the design phase of such architectures. Approaches to perform an integrated assessment of dependability attributes for DCs, in general, are not trivial. Thus, this work presents the dependability attributes (availability and reliability), performability, and sustainability parameters that need special attention in implementing a cooling subsystem in DCs. That is one of the most cost generators for these infrastructures. In this study, we use the hypothetical-deductive method through a quantitative and qualitative approach; as for the procedure, it is bibliographical research through the review of scientific studies, and the research objectives are exploratory in nature. The results show that among all the papers selected and analyzed in this systematic literature review (SLR), none have jointly addressed performability, dependability, and sustainability in cooling systems for DCs. The main results of this work are presented through research questions, as they bring evidence of gaps to be addressed in the area. The four research questions point out challenges in implementing cooling systems in DCs and present the techniques and/or methods most used to propose or analyze data center cooling infrastructures; addressing the essential sustainability requirements for cooling subsystems, and finally, presenting open questions that can be investigated in the area of sustainable cooling in DCs regarding the data center’s cooling and the difficulty of incorporating dependability attributes in the environmental context. In addition to these results, the present study actively contributes to the concept of a “green data center” for the companies, which ranges from the choice of renewable energy sources to more efficient information technology equipment. Hence, we show the relevance and originality of this SLR and its results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Data Availability

Data supporting the findings of this study are not openly available due to confidentiality reasons and are available from the corresponding author upon reasonable request. The data is arranged in the author’s Academic Drive and can be accessed through this link.

Notes

  1. http://lapes.dc.ufscar.br/tools/start_tool.

References

  1. Han B, Li W, Li M, Liu L, Song J (2020) Study on libr/h2o absorption cooling system based on enhanced geothermal system for data center. Energy Rep 6:1090–1098

    Google Scholar 

  2. Callou G, Maciel P, Tutsch D, Ferreira J, Araújo J, Souza R (2013) Estimating sustainability impact of high dependable data centers: a comparative study between Brazilian and us energy mixes. Computing 95(12):1137–1170

    Google Scholar 

  3. Gomes DM, Endo PT, Gonçalves G, Rosendo D, Santos GL, Kelner J, Sadok D, Mahloo M (2017) Evaluating the cooling subsystem availability on a cloud data center. In: 2017 IEEE symposium on computers and communications (ISCC). IEEE, pp 736–741

  4. Gagnaire M, Diaz F, Coti C, Cerin C, Shiozaki K, Xu Y, Delort P, Smets J-P, Le Lous J, Lubiarz S, et al (2012) Downtime statistics of current cloud solutions. Technical Report, international working group on cloud computing resiliency

  5. Ponemon L (2016) Cost of data center outages. Data Center Performance Benchmark Serie

  6. Wang J, Zhang Q, Yoon S, Yu Y (2019) Reliability and availability analysis of a hybrid cooling system with water-side economizer in data center. Build Environ 148:405–416

    Google Scholar 

  7. Camboim K, Araujo J, Melo C, Alencar F, Maciel P (2021) Dependability and sensitivity analysis in dense data center networks. In: 2021 16th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, pp 1–6

  8. Marin PS (2011) Data centers-desvendando cada passo: conceitos, projeto, infraestrutura física e eficiência energética. Érica, São Paulo

    Google Scholar 

  9. Munn L (2020) Injecting failure: data center infrastructures and the imaginaries of resilience. Inf Soc 36(3):167–176

    Google Scholar 

  10. Ritchie H, Roser M (2020) Co2 and greenhouse gas emissions. https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions. Accessed April 24, 2021

  11. Koomey J et al (2011) Growth in data center electricity use 2005 to 2010. A report by Analytical Press, completed at the request of The New York Times, vol 9, 2011, pp 161

  12. Lee S, Mun S, Kim J, Shin S, Seo Y, Choi Y (2009) The establishment method of green data center in public sector. J KIISE 27(11):48–57

    Google Scholar 

  13. Camboim K, Ferreira J, Araujo J, Alencar F (2020) Sustainability analysis in data center dense architectures. In: 2020 IEEE 9th International Conference on Cloud Networking (CloudNet). IEEE, pp 1–6

  14. Onyiorah C, Eiland R, Agonafer D, Schmidt R (2014) Effectiveness of rack-level containment in removing data center hot-spots. In: Fourteenth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm). IEEE, pp 798–806

  15. Bari MF, Boutaba R, Esteves R, Granville LZ, Podlesny M, Rabbani MG, Zhang Q, Zhani MF (2012) Data center network virtualization: a survey. IEEE Commun Surv Tutor 15(2):909–928

    Google Scholar 

  16. Headquarters A (2007) Cisco data center infrastructure 2.5 design guide. Cisco Validated Design I

  17. Fan X, Weber W-D, Barroso LA (2007) Power provisioning for a warehouse-sized computer. ACM SIGARCH Comput Archit News 35(2):13–23

    Google Scholar 

  18. Arregoces M, Portolani M (2003) Data center fundamentals. Cisco Press, Indianapolis

    Google Scholar 

  19. Patterson DA et al (2002) A simple way to estimate the cost of downtime. LISA 2:185–188

    Google Scholar 

  20. Marwah M, Maciel P, Shah A, Sharma R, Christian T, Almeida V, Araújo C, Souza E, Callou G, Silva B et al (2010) Quantifying the sustainability impact of data center availability. ACM SIGMETRICS Perform Eval Rev 37(4):64–68

    Google Scholar 

  21. Institute U (2021) Tier classification system. https://pt.uptimeinstitute.com/tiers. Accessed Dec, 2021

  22. Turner WP, Seader JH, Brill KG (2005) Industry standard tier classifications define site infrastructure performance. Uptime Institute, Santa Fe

    Google Scholar 

  23. Rong H, Zhang H, Xiao S, Li C, Hu C (2016) Optimizing energy consumption for data centers. Renew Sustain Energy Rev 58:674–691

    Google Scholar 

  24. Khoshkholghi MA, Derahman MN, Abdullah A, Subramaniam S, Othman M (2017) Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers. IEEE Access 5:10709–10722

    Google Scholar 

  25. Shehabi A, Smith S, Sartor D, Brown R, Herrlin M, Koomey J, Masanet E, Horner N, Azevedo I, Lintner W (2016) United states data center energy usage report

  26. Bein W (2018) Energy saving in data centers. Multidisciplinary Digital Publishing Institute

  27. Lima JM (2017) Data centres of the world will consume 1/5 of earth’s power by 2025. Data Economy

  28. Danilak R (2017) Why energy is a big and rapidly growing problem for data centers. Forbes 15:12–17

    Google Scholar 

  29. Ding T, Chen X, Cao H, He Z, Wang J, Li Z (2021) Principles of loop thermosyphon and its application in data center cooling systems: a review. Renew Sustain Energy Rev 150:111389

    Google Scholar 

  30. Ding T, Guang He Z, Hao T, Li Z (2016) Application of separated heat pipe system in data center cooling. Appl Therm Eng 109:207–216

    Google Scholar 

  31. Guimarães AP, da Silva AP (2020) Análise de aspectos de dependabilidade em infraestruturas de data centers considerando variação de temperatura e diferentes mecanismos de redundância. Revista Brasileira de Administração Científica 11(3):228–241

    Google Scholar 

  32. Daraghmeh HM, Wang C-C (2017) A review of current status of free cooling in datacenters. Appl Therm Eng 114:1224–1239

    Google Scholar 

  33. Nadjahi C, Louahlia H, Lemasson S (2018) A review of thermal management and innovative cooling strategies for data center. Sustain Comput Inf Syst 19:14–28

    Google Scholar 

  34. Burton I (1987) Our common future-the world-commission-on-environment-and-development. Environment 29(5):25–29

    Google Scholar 

  35. Brand K-W (2002) Politik der Nachhaltigkeit: Voraussetzungen, Probleme, Chancen: eine kritische Diskussion. Edition Sigma

  36. Harmon RR, Auseklis N (2009) Sustainable it services: assessing the impact of green computing practices. In: PICMET’09-2009 Portland International Conference on Management of Engineering and Technology. Citeseer, pp 1707–1717

  37. Murugesan S (2008) Harnessing green it: principles and practices. IT Pofessional 10(1):24–33

    MathSciNet  Google Scholar 

  38. Vale KMAC, de Alencar FMR (2020) Challenges, patterns and sustainability indicators for cloud computing. Braz J Dev 6(8):57031–57053

    Google Scholar 

  39. Kuo W, Zuo MJ (2003) Optimal reliability modeling: principles and applications. Wiley, New York

    Google Scholar 

  40. Laprie JCC, Avizienis A, Kopetz H (eds) (1992) Dependability: basic concepts and terminology. Springer, Secaucus

    MATH  Google Scholar 

  41. Maciel PRM, Trivedi KS, Matias R, Kim DS (2011) Dependability Modeling. Performance and dependability in service computing: concepts, techniques and research directions. Information science reference—Imprint of: IGI Publishing, Hershey, pp 53–97

  42. Avizienis A, Laprie JC, Randell B, Landwehr C (2004) Basic concepts and taxonomy of dependable and secure computing. IEEE Trans Dependable Secure Comput 1(1):11–33. https://doi.org/10.1109/TDSC.2004.2

    Article  Google Scholar 

  43. Haverkort BR, Niemegeers IG (1996) Performability modelling tools and techniques. Perform Eval 25(1):17–40

    MATH  Google Scholar 

  44. Meyer JF (1992) Performability: a retrospective and some pointers to the future. Perform Eval 14(3–4):139–156

    MATH  Google Scholar 

  45. Haverkort BR, Marie R, Rubino G, Trivedi KS (2001) Performability modelling: techniques and tools. Wiley, New York

    Google Scholar 

  46. MATOS JÚNIOR RdS (2016) Identification of availability and performance bottlenecks in cloud computing systems: an approach based on hierarchical models and sensitivity analysis

  47. Dâmaso A, Rosa N, Maciel P (2017) Integrated evaluation of reliability and power consumption of wireless sensor networks. Sensors 17(11):2547

    Google Scholar 

  48. Balbo G (2001) Introduction to Stochastic Petri Nets. lectures on formal methods and performance analysis, Springer

  49. Kitchenham B (2004) Procedures for performing systematic reviews. Keele Univ 33(2004):1–26

    Google Scholar 

  50. Brereton P, Kitchenham BA, Budgen D, Turner M, Khalil M (2007) Lessons from applying the systematic literature review process within the software engineering domain. J Syst Softw 80(4):571–583

    Google Scholar 

  51. Vale KMAC (2020) Analysis of dependability and sustainability requirements to support the deployment of dense data center architectures

  52. Kitchenham B, Charters S (2007) Guidelines for performing systematic literature reviews in software engineering

  53. Camboim K, Alencar FM (2018) Requisitos não funcionais e sustentabilidade para computação em nuvem: uma revisão sistemática da literatura. In: WER

  54. Callou G, Maciel P, Tavares E, Sousa E, Silva B, Figueiredo J, Araujo C, Magnani F, Neves F (2011) Sustainability and dependability evaluation on data center architectures. In: 2011 IEEE International Conference on Systems, Man, and Cybernetics. IEEE, pp 398–403

  55. Callou G, Maciel P, Tutsch D, Araujo J (2012) Models for dependability and sustainability analysis of data center cooling architectures. In: IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN 2012). IEEE, pp 1–6

  56. Callou G, Andrade E, Ferreira J (2019) Modeling and analyzing availability, cost and sustainability of it data center systems. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, pp 2127–2132

  57. Souza R, Callou G, Camboin K, Ferreira J, Maciel P (2013) The effects of temperature variation on data center it systems. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics. IEEE, pp 2354–2359

  58. Chen C, Wang G, Sun J, Xu W (2018) Detecting data center cooling problems using a data-driven approach. In: Proceedings of the 9th Asia-pacific workshop on systems, pp 1–8

  59. Gomes D, Leoni G, Sadok D, Gonçalves G, Endo P, Maciel P (2020) Temperature variation impact on estimating costs and most critical components in a cloud data centre. Int J Comput Appl Technol 62(4):361–374

    Google Scholar 

  60. Koo S, Chung T-S, Kim S (2015) Availability analysis for a data center cooling system with (n, k)-way CRACs. Springer, Berlin

    Google Scholar 

  61. Wang R, Van Le D, Tan R, Wong Y-W, Wen Y (2020) Real-time cooling power attribution for co-located data center rooms with distinct temperatures. In: Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp 190–199

  62. Bennaceur WM, Kloul L (2018) Electrical and thermal system impact on the availability of a data center’s system. In: 2018 3rd International Conference on System Reliability and Safety (ICSRS). IEEE, pp 142–148

  63. Callou G, Ferreira J, Maciel P, Tutsch D, Souza R (2014) An integrated modeling approach to evaluate and optimize data center sustainability, dependability and cost. Energies 7(1):238–277

    Google Scholar 

  64. Basmadjian R, Ghiassi-Farrokhfal Y, Vishwanath A (2018) Hidden storage in data centers: gaining flexibility through cooling systems. In: International Conference on Measurement, Modelling and Evaluation of Computing Systems. Springer, pp 68–82

  65. Wan J, Gui X, Kasahara S, Zhang Y, Zhang R (2018) Air flow measurement and management for improving cooling and energy efficiency in raised-floor data centers: a survey. IEEE Access 6:48867–48901

    Google Scholar 

  66. Zhang W, Wen Y, Wong YW, Toh KC, Chen C-H (2016) Towards joint optimization over ict and cooling systems in data centre: a survey. IEEE Commun Surv Tutor 18(3):1596–1616

    Google Scholar 

  67. Cheung H, Wang S (2019) Reliability and availability assessment and enhancement of water-cooled multi-chiller cooling systems for data centers. Reliab Eng Syst Saf 191:106573

    Google Scholar 

  68. Trivedi KS (2008) Probability and statistics with reliability, queuing and computer science applications, 2nd edn. Wiley. https://books.google.com.br/books?id=h9v8KhlN8tAC

  69. Helali L, Omri MN (2021) A survey of data center consolidation in cloud computing systems. Comput Sci Rev 39:100366

    Google Scholar 

  70. Jones N (2018) How to stop data centres from gobbling up the world’s electricity. Nature 561(7722):163–167

  71. Chen H, Peng Y, Wang Y (2019) Thermodynamic analysis of hybrid cooling system integrated with waste heat reusing and peak load shifting for data center. Energy Convers Manag 183:427–439

    Google Scholar 

  72. Demetriou DW, Kamath V, Mahaney H (2016) A holistic evaluation of data center water cooling total cost of ownership. J Electron Packag 138(1):010912

    Google Scholar 

  73. Ebrahimi K, Jones GF, Fleischer AS (2014) A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities. Renew Sustain Energy Rev 31:622–638

    Google Scholar 

  74. Garimella SV, Yeh L-T, Persoons T (2012) Thermal management challenges in telecommunication systems and data centers. IEEE Trans Compon Packag Manuf Technol 2(8):1307–1316

    Google Scholar 

  75. Camboim KMA Modelagem hierárquica e heterogênea para infraestrutura de redes convergentes e politica de manutencao para garantia de niveis de servicos

  76. Sahner R, Trivedi K, Puliafito A (1997) Performance and reliability analysis of computer systems (an example-based approach using the sharpe software. IEEE Trans Reliab 46(3):441–441

    MATH  Google Scholar 

  77. ReliaSoft: Blocksim: System reliability and maintainability analysis software tool. https://www.reliasoft.com/products/blocksim-system-reliability-availability-maintainability-ram-analysis-software (2010)

  78. Zimmermann A (2012) Modeling and evaluation of stochastic petri nets with timenet 4.1. In: 6th International ICST Conference on Performance Evaluation Methodologies and Tools. IEEE, pp 54–63

  79. Silva B, Matos R, Callou G, Figueiredo J, Oliveira D, Ferreira J, Dantas J, Lobo A, Alves V, Maciel P (2015) Mercury: an integrated environment for performance and dependability evaluation of general systems. In: Proceedings of Industrial Track at 45th Dependable Systems and Networks Conference, DSN

  80. Chiola G, Franceschinis G, Gaeta R, Ribaudo MG (1995) 1.7: graphical editor and analyzer for timed and stochastic Petri nets Perform. Eval. Elsevier Science Publishers BV

  81. Ciardo G, Muppala JK, Trivedi KS, et al (1989) Spnp: stochastic petri net package. In: PNPM, vol 89. Citeseer, pp 142–151

  82. Perry DE, Porter AA, Votta LG (2000) Empirical studies of software engineering: a roadmap. In: Proceedings of the Conference on The Future of Software Engineering, pp 345–355

  83. Silva B, Callou G, Tavares E, Maciel P, Figueiredo J, Sousa E, Araujo C, Magnani F, Neves F (2013) Astro: an integrated environment for dependability and sustainability evaluation. Sustain Comput Inf Syst 3(1):1–17

    Google Scholar 

  84. Kuncoro I, Pambudi N, Biddinika M, Widiastuti I, Hijriawan M, Wibowo K (2019) Immersion cooling as the next technology for data center cooling: a review. J Phys Conf Ser 1402:044057

    Google Scholar 

  85. Oró E, Depoorter V, Garcia A, Salom J (2015) Energy efficiency and renewable energy integration in data centres. Strategies and modelling review. Renew Sustain Energy Rev 42:429–445

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universidade de Pernambuco, Recife, PE, Brazil

    Lubnnia Souza & Fernanda Alencar

  2. Universidade Federal do Agreste de Pernambuco, Garanhuns, PE, Brazil

    Kádna Camboim

  3. Universidade Federal de Pernambuco, Recife, PE, Brazil

    Fernanda Alencar

Authors
  1. Lubnnia Souza
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Kádna Camboim
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Fernanda Alencar
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Lubnnia Souza.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Souza, L., Camboim, K. & Alencar, F. A systematic literature review about integrating dependability attributes, performability and sustainability in the implantation of cooling subsystems in data center. J Supercomput 78, 15820–15856 (2022). https://doi.org/10.1007/s11227-022-04515-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-022-04515-2

Keywords