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Green Service Level Agreement (GSLA) framework for cloud computing

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Abstract

As the organizations are shifting their workload on cloud computing, the demand of cloud services has increased tremendously. With the increased usage of cloud data centers, there is huge consumption of energy (power and heat), contributing to high operational costs and carbon footprints to the environment. So far, research has been carried out to optimize energy usage for cloud resources. However, most of the work on energy optimization is centered on the operational phase of a data center. This paper focuses on energy reduction at Service Level Agreement (SLA) level. Cloud resources are provisioned with Green SLA aware cloud resource reservation (GSLACRR) algorithm. This work proposes Green Service Level Agreement (GSLA) template and negotiation strategies for cloud services. It offers cloud resource services in an energy efficient manner to the users.

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References

  1. Beloglazov A, Abawajy J, Buyya R (2012) Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Futur Gener Comput Syst 28(5):755–768

    Article  Google Scholar 

  2. Minh QD, Federico M, Domenico S, Giafreda R (2012) T-Alloc A practical energy efficient resource allocation algorithm for traditional data centers. Futur Gener Comput Syst 28(5):791–800

    Article  Google Scholar 

  3. Lee YC, Zomaya AY (2012) Energy efficient utilization of resources in cloud computing systems. J Supercomput 60(2):268–280

    Article  MathSciNet  Google Scholar 

  4. Beloglazov A, Buyya R (2012) Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers. Concurr Comput Pract Exp 24(13):1397–1420

    Article  Google Scholar 

  5. Rizvandi NB, Taheri J, Zomaya AY (2011) Some observations on optimal frequency selection in DVFS-based energy consumption minimization. J Parallel Distrib Comput 71(8):1154–1164

    Article  MATH  Google Scholar 

  6. Beloglazov A, Buyya R (2010) Energy efficient resource management in virtualized cloud data centers. In: Proceedings of the 2010 10th IEEE/ACM international conference on cluster, cloud and grid computing, pp 826–831

  7. Kim KH, Beloglazov A, Buyya R (2009) Power-aware provisioning of cloud resources for real-time services. In: Proceedings of the 7th international workshop on middleware for grids, clouds and e-science, p 1

  8. Kan EY, Chan WK, Tse TH (2012) EClass: An execution classification approach to improving the energy-efficiency of software via machine learning. J Syst Softw 85(4):960–973

    Article  Google Scholar 

  9. Guzek M, Diaz CO, Pecero JE, Bouvry P, Zomaya AY (2012) Impact of Voltage Levels Number for Energy-aware Bi-objective DAG Scheduling for Multi-processors Systems. Advances in Information Technology. Springer, Berlin, pp 70–80

  10. Sharma RK, Bash CE, Patel CD, Friedrich RJ, Chase JS (2005) Balance of power: Dynamic thermal management for internet data centers. Internet Comput IEEE 9(1):42–49

    Article  Google Scholar 

  11. Moore JD, Chase JS, Ranganathan P, Sharma RK (2005) Making Scheduling Cool: Temperature-Aware Workload Placement in Data Centers. In USENIX annual technical conference, General Track, pp 61–75

  12. Chaudhry MT, Ling TC, Manzoor A, Hussain SA, Kim J (2015) Thermal-aware scheduling in green data centers. ACM Comput Surv (CSUR) 47(3):39

    Article  Google Scholar 

  13. Haque ME, Le K, Goiri Í, Bianchini R, Nguyen TD (2013) Providing Green SLAs in High Performance Computing Clouds. In: IEEE international Green computing conference (IGCC). IEEE, Arlington, pp 1–11

  14. Bunse C, Klingert S, Schulze T (2012) GreenSLAs: Supporting energy-efficiency through contracts. Energy Efficient Data Centers. Springer, Berlin, pp 54–68

  15. von Laszewski G, Wang L (2010) GreenIT service level agreements. In: Grids and Service-Oriented Architectures for Service Level Agreements Springer, US, pp 77–88

  16. Dupont C, Giuliani G, Hermenier F, Schulze T, Somov A (2012) An energy aware framework for virtual machine placement in cloud federated data centres. In: IEEE third international conference on future energy systems: where energy, computing and communication meet (e-Energy), pp 1–10

  17. Copil G, Moldovan D, Salomie I, Cioara T, Anghel I, Borza D (2012) Cloud SLA negotiation for energy saving—a particle swarm optimization approach. In: IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), pp 289–296

  18. Rasheed H, Rumpl A, Wäldrich O, Ziegler W (2012) A standards-based approach for negotiating service QoS with cloud infrastructure providers. In: eChallenges Conference

  19. Gao Y, Guan H, Qi Z, Wang B, Liu L (2013) Quality of service aware power management for virtualized data centers. J Syst Arch 59(4):245–259

    Article  Google Scholar 

  20. Chen X, Li K, Liu C, Li K (2014) SLA-based energy aware scheduling of precedence-constrained applications on DVFS-enabled clusters. In: 20th IEEE international conference on parallel and distributed systems (ICPADS). IEEE, Hsinchu

  21. Basmadjian R, Bunse C, Georgiadou V, Giuliani G, Klingert S, Lovasz G, Majanen M (2010) Fit4green-energy aware ICT optimization policies. In: Proceedings of the COST Action IC0804 on energy efficiency in large scale distributed systems—1st year, pp 88–92

  22. Dupont Corentin et al (2015) Plug4Green: a flexible energy-aware VM manager to fit data centre particularities. Ad Hoc Netw 25:505–519

    Article  Google Scholar 

  23. http://www.google.com/about/datacenters/renewable/. Accessed 7 Jan 2016

  24. Deng N, Stewart C, Gmach D, Arlitt M, Kelley J (2012) Adaptive green hosting. In: ACM Proceedings of the 9th international conference on Autonomic computing, pp 135–144

  25. 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. doi:10.1016/j.rser.2014.10.035

    Article  Google Scholar 

  26. Li C, Hu Y, Zhou R, Liu M, Liu L, Yuan J, Li T (2013) Enabling datacenter servers to scale out economically and sustainably. In: Proceedings of the 46th annual IEEE/ACM international symposium on microarchitecture, pp 322–333

  27. Li C, Zhou R, Li T (2013) Enabling distributed generation powered sustainable high-performance data center. In: IEEE proceeding of the 19th international symposium on high performance computer architecture (HPCA2013), pp 35-46

  28. Deng N, Stewart C, Li J (2011) Concentrating renewable energy in grid-tied datacenters. In: IEEE proceeding of international symposium on sustainable systems and technology (ISSST), pp 1–6

  29. Orgerie AC (2011) An energy-efficient reservation framework for large-scale distributed systems. PhD thesis, Ecole Normale Supérieure de Lyon–France

  30. Goyal S, Bawa S, Singh B (2015) Energy optimized resource scheduling algorithm for private cloud computing. International Journal of AdHoc and Ubiquitous Computing, Inderscience (In Press, Accepted Manuscript)

  31. Kernel-based Virtual Machine: http://www.linux-kvm.org/page/Main_Page

  32. Ubuntu operating system. http://www.ubuntu.com/

  33. Power consumption of Dell PowerEdge r710 server (2014) http://www.dell.com/downloads/global/products/pedge/en/dell_poweredge_r710_2p_e5620_870w_energy_star_data_sheet.pdf

  34. Power consumption of Dell PowerEdge 2900 server (2014) http://www.intel.com/content/dam/www/public/us/en/documents/datasheets/quad-core-xeon-5400-datasheet.pdf

  35. Gavrichenkov I, CPU Benchmark (2014) http://www.xbitlabs.com/articles/cpu/display/cpu-benchmark-mainstream_10.html

  36. Gavrichenkov I (2014) Power consumption of intelCore i5 processor. http://www.xbitlabs.com/articles/cpu/display/core-i5-2500-2400-2300_10.html

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Correspondence to Sudhir Goyal.

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Goyal, S., Bawa, S. & Singh, B. Green Service Level Agreement (GSLA) framework for cloud computing. Computing 98, 949–963 (2016). https://doi.org/10.1007/s00607-015-0481-6

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  • DOI: https://doi.org/10.1007/s00607-015-0481-6

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