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Customer on-boarding strategies for cloud computing services with dynamic service-level agreements

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Abstract

A multi-tenant software as a service (SaaS) provider has to meet the needs of several tenants which adopt its services with diverse business requirements. The tenant needs vary widely with time, and the provider has to account for such fluctuations by suitable provisioning at its end. Handling this elasticity arising out of the tenant base is one of the key challenges for the SaaS provider. In this paper, we study the problem specifically in the SaaS context with the idea built around license provisioning in a tenant–provider perspective. For a given set of tenants with diverse license requirements, it is important to analyze whether there is any way to on-board them such that all constraints laid out as part of the service-level agreement can be honored. The total number of licenses available with the provider plays a crucial role in answering this question. We propose an intuitive model of elasticity that can capture anticipated license need variations at the tenant end. We propose an ILP-based approach for solving this schedulability problem for a collection of tenants. We also propose a simple-minded greedy heuristic to solve the on-boarding problem with elasticity constraints. Results show that our approach gives acceptable performance.

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References

  1. Buyya R, Garg SK, Calheiros RN (2011) Sla-oriented resource provisioning for cloud computing: challenges, architecture, and solutions. In: Proceedings of the 2011 international conference on cloud and service computing, ser. CSC ’11. Washington, DC, USA: IEEE Computer Society, pp 1–10. doi:10.1109/CSC.2011.6138522

  2. Ca technologies. http://www.ca.com/

  3. Compiere erp on cloud. http://www.compiere.com/

  4. Microsoft system center 2012 r2. http://www.microsoft.com/en-in/server-cloud/products/system-center-2012-r2/

  5. Amazon ec2. http://aws.amazon.com/ec2/

  6. Microsoft server. http://www.microsoft.com/en-in/server-cloud/products/system-center-2012-r2/Purchasing.aspx

  7. Microsoft server workload. http://www.hpcloud.com/pricing

  8. Wu L, Garg SK, Buyya R (2011) Sla-based resource allocation for software as a service provider (saas) in cloud computing environments. IEEE international symposium on cluster computing and the grid, vol 0, pp 195–204

  9. Hu Y, Wong J, Iszlai G, Litoiu M (2009) Resource provisioning for cloud computing. In: Proceedings of the 2009 conference of the center for advanced studies on collaborative research, ser. CASCON ’09. Riverton, NJ, USA: IBM Corp., pp 101–111. doi:10.1145/1723028.1723041

  10. Zhu Z, Bi J, Yuan H, Chen Y (2011) Sla based dynamic virtualized resources provisioning for shared cloud data centers. In: IEEE international conference on cloud computing (CLOUD)

  11. Sakr S, Liu A (2012) Sla-based and consumer-centric dynamic provisioning for cloud databases. In: Proceedings of the 2012 IEEE fifth international conference on cloud computing, ser. CLOUD ’12. Washington, DC, USA: IEEE Computer Society, pp 360–367. doi:10.1109/CLOUD.2012.11

  12. Espadas J, Molina A, JiméNez G, Molina M, RamíRez R, Concha D (2013) A tenant-based resource allocation model for scaling software-as-a-service applications over cloud computing infrastructures. Future Gener Comput Syst 29(1):273–286. doi:10.1016/j.future.2011.10.013

    Article  Google Scholar 

  13. Roy N, Dubey A, Gokhale A (2011) Efficient autoscaling in the cloud using predictive models for workload forecasting. In: IEEE international conference on cloud computing (CLOUD), pp 500–507

  14. Nandi BB et al. (2012) Stochastic VM multiplexing for datacenter consolidation. In: 2012 IEEE ninth international conference on services computing, Honolulu, HI, USA, June 24–29, 2012, pp 114–121

  15. Nandi BB, Banerjee A, Ghosh SC, Banerjee N (2013) Dynamic sla based elastic cloud service management: a saas perspective. In: IFIP/IEEE international symposium on integrated network management, pp 60–67

  16. Kuebert R, Gallizo G, Oberle K, Oliveros E (2010) Enhancing the sla framework of a virtualized service platform by dynamic re-negotiation. In: eChallenges, 2010. IEEE, pp 1–8

  17. Cucinotta T, Checconi F, Kousiouris G, Kyriazis D, Varvarigou T, Mazzetti A, Zlatev Z, Papay J, Boniface M, Berger S, et al. (2010) Virtualised e-learning with real-time guarantees on the irmos platform. In: 2010 IEEE international conference on service-oriented computing and applications (SOCA). IEEE, pp 1–8

  18. Voith T, Oberle K, Stein M (2012) Quality of service provisioning for distributed data center inter-connectivity enabled by network virtualization. Future Gener Comput Syst 28(3):554–562

  19. Roychoudhury A (2009) Embedded systems and software validation. ser. The Morgan Kaufmann series in systems on silicon. Morgan Kaufmann

  20. Feller W. (1968) An introduction to probability theory and Its Applications. vol. 1. 3rd edn. Wiley, p 160

  21. Ibm ilog cplex optimizer. http://www-01.ibm.com/software/in/integration/optimization/cplex/

  22. Google cloud. https://docs.google.com/file/d/0B5g07T_gRDg9Z0lsSTEtTWtpOW8/edit

  23. K-means. https://sites.google.com/site/dataclusteringalgorithms/k-means-clustering-algorithm

  24. Lee YC, Wang C, Zomaya AY, Zhou BB (2010) Profit-driven service request scheduling in clouds. In: Proceedings of the 2010 10th IEEE/ACM international conference on cluster, cloud and grid computing. ser. CCGRID ’10. Washington, DC, USA: IEEE Computer Society, pp 15–24. doi:10.1109/CCGRID.2010.83

  25. Meng X, Isci C, Kephart J, Zhang L, Bouillet E, Pendarakis D (2010) Efficient resource provisioning in compute clouds via vm multiplexing. In: Proceedings of the 7th international conference on autonomic computing. ser. ICAC ’10. New York, NY, USA: ACM, pp 11–20. doi:10.1145/1809049.1809052

  26. Chen Y, Wo T, Li J (2009) An efficient resource management system for on-line virtual cluster provision. In: IEEE CLOUD. IEEE, pp 72–79. http://dblp.uni-trier.de/db/conf/IEEEcloud/IEEEcloud2009.html#ChenWL09

  27. Xu J, Zhao M, Fortes J, Carpenter R, Yousif M (2007) On the use of fuzzy modeling in virtualized data center management. In: Proceedings of the fourth international conference on autonomic computing. ser. ICAC ’07. Washington, DC, USA: IEEE Computer Society, p 25. doi:10.1109/ICAC.2007.28

  28. Tannenbaum T, Wright D, Miller K, Livny M (2002) Beowulf cluster computing with linux. Cambridge, MA, USA: MIT Press, 2002, ch. Condor: A Distributed Job Scheduler, pp 307–350. http://dl.acm.org/citation.cfm?id=509876.509893

  29. JOF and In igo Goiri and Guitart J (2010) Sla-driven elastic cloud hosting provider. In: 18th euromicro international conference on parallel, distributed and network-based processing (PDP), pp 111–118

  30. Ali-Eldin A, Tordsson J, Elmroth E (2012) An adaptive hybrid elasticity controller for cloud infrastructures. In: IEEE network operations and management symposium (NOMS), pp 204–212

  31. Li H, Casale G, Ellahi T (2010) Sla-driven planning and optimization of enterprise applications. In: Proceedings of the first joint WOSP/SIPEW international conference on performance engineering. ser. WOSP/SIPEW ’10. New York, NY, USA: ACM, pp 117–128. doi:10.1145/1712605.1712625

  32. Cardellini V, Casalicchio E, Presti FL, Silvestri L (2011) Sla-aware resource management for application service providers in the cloud. First Int Symp Netw Cloud Comput Appl 2011:20–27

    Google Scholar 

  33. Bonvin N, Papaioannou TG, Aberer K (2011) Autonomic sla-driven provisioning for cloud applications. In: Proceedings of the 2011 11th IEEE/ACM international symposium on cluster, cloud and grid computing. ser. CCGRID ’11. Washington, DC, USA: IEEE Computer Society, pp 434–443. doi:10.1109/CCGrid.2011.24

  34. Banerjee A, Ghosh SC, Banerjee N (2012) Pack your sack for the cloud. In: India Software Engineering Conference, pp 157–160

  35. Song Y, Li Y, Wang H, Zhang Y, Feng B, Zang H, Sun Y (2008) A service-oriented priority-based resource scheduling scheme for virtualized utility computing. In: Proceedings of the 15th international conference on high performance computing. ser. HiPC’08, pp 220–231

  36. Yang J, Qiu J, Li Y (2009) A profile-based approach to just-in-time scalability for cloud applications. In: IEEE international conference on cloud computing, pp 9–16

  37. Padala P, Shin KG, Zhu X, Uysal M, Wang Z, Singhal S, Merchant A, Salem K (2007) Adaptive control of virtualized resources in utility computing environments. In: Proceedings of the 2nd ACM SIGOPS/EuroSys European conference on computer systems 2007. ser. EuroSys ’07. New York, NY, USA: ACM, 2007, pp 289–302. doi:10.1145/1272996.1273026

  38. Ren W, Cao Y (2011) Distributed coordination of multi-agent networks, emergent problems, models, and issues. Springer, Berlin

    Book  MATH  Google Scholar 

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Authors and Affiliations

  1. Indian Statistical Institute, Kolkata, India

    Bipin B. Nandi, Sasthi C. Ghosh & Ansuman Banerjee

  2. IBM Research, New Delhi, India

    Nilanjan Banerjee

Authors
  1. Bipin B. Nandi
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  2. Sasthi C. Ghosh
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  3. Ansuman Banerjee
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  4. Nilanjan Banerjee
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Correspondence to Ansuman Banerjee.

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Nandi, B.B., Ghosh, S.C., Banerjee, A. et al. Customer on-boarding strategies for cloud computing services with dynamic service-level agreements. SOCA 11, 47–63 (2017). https://doi.org/10.1007/s11761-016-0194-5

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  • DOI: https://doi.org/10.1007/s11761-016-0194-5

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