On the Implicit Cost Structure of Service Levels from the Perspective of the Service Consumer

Maximilian Christ, Julius Neuffer, Andreas W. Kempa-Liehr

2017

Abstract

As services are ubiquitous in the modern business landscape, there is the need to define them in a binding legal framework, the Service Level Agreement (SLA). The most important aspect of a SLA is the agreed service level, which specifies the availability of the service. In this work, we discuss a simple mathematical service model, where the availability of a service is based on a singular resource. In this model one can relate the parameter of a linear cost structure to the purchased service level. Based on this relation we formulate a rule of thumb enabling a service consumer to check if an agreed service level fits their cost structure.

References

  1. Allen, P. and Higgins, S. (2006). Service Orientation: Winning Strategies and Best Practices. Cambridge University Press.
  2. Ardagna, D., Casale, G., Ciavotta, M., PĂ©rez, J. F., and Wang, W. (2014). Quality-of-service in cloud computing: modeling techniques and their applications. Journal of Internet Services and Applications, 5(1):11.
  3. Birge, J. R. and Louveaux, F. (2011). Introduction to stochastic programming. Springer Science & Business Media, Berlin.
  4. Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Information Science and Statistics). SpringerVerlag New York, Inc., Secaucus, NJ, USA.
  5. Campo, K., Gijsbrechts, E., and Nisol, P. (2000). Towards understanding consumer response to stock-outs. Journal of Retailing, 76(2):219-242.
  6. Chaisiri, S., Lee, B.-S., and Niyato, D. (2012). Optimization of Resource Provisioning Cost in Cloud Computing. IEEE Transactions on Services Computing, 5(2):164- 177.
  7. Chase, R. B. and Apte, U. M. (2007). A history of research in service operations: What's the big idea? Journal of Operations Management, 25(2):375 - 386.
  8. Cherbakov, L., Galambos, G., Harishankar, R., Kalyana, S., and Rackham, G. (2005). Impact of service orientation at the business level. IBM Systems Journal, 44(4):653-668.
  9. Della Vedova, M. L., Tessera, D., and Calzarossa, M. C. (2016). Probabilistic provisioning and scheduling in uncertain Cloud environments. In 2016 IEEE Symposium on Computers and Communication (ISCC), pages 797- 803. IEEE.
  10. Emeakaroha, V. C., Brandic, I., Maurer, M., and Dustdar, S. (2010). Low level metrics to high level SLAs - LoM2HiS framework: Bridging the gap between monitored metrics and sla parameters in cloud environments. In High Performance Computing and Simulation (HPCS), 2010 International Conference on, pages 48-54. IEEE.
  11. Feindt, M. and Kerzel, U. (2015). Prognosen bewerten. Springer Berlin Heidelberg.
  12. Fu, X., Li, X., Zhu, Y., Wang, L., and Goh, R. S. M. (2014). An intelligent analysis and prediction model for on-demand cloud computing systems. In 2014 International Joint Conference on Neural Networks (IJCNN), pages 1036-1041. IEEE.
  13. Furht, B. and Escalante, A. (2010). Handbook of Cloud Computing. Computer science. Springer US.
  14. Kempa-Liehr, A. (2015). Performance analysis of concurrent workflows. Journal of Big Data, 2(10):1-14.
  15. Meiss, M., Menczer, F., Fortunato, S., Flammini, A., and Vespignani, A. (2008). Ranking Web Sites with Real User Traffic. In Proc. First ACM International Conference on Web Search and Data Mining (WSDM), pages 65-75.
  16. Misra, S. C. and Mondal, A. (2011). Identification of a companys suitability for the adoption of cloud computing and modelling its corresponding return on investment. Mathematical and Computer Modelling, 53(3):504-521.
  17. Office of Government Commerce (2007). ITIL Lifecycle Publication Suite Books. The Stationary Office, London.
  18. Oliva, R. and Kallenberg, R. (2003). Managing the transition from products to services. International Journal of Service Industry Management, 14(2):160-172.
  19. Osterwalder, A., Pigneur, Y., and Tucci, C. L. (2005). Clarifying business models: Origins, present, and future of the concept. Communications of the association for Information Systems, 16(1).
  20. Patel, P., Ranabahu, A. H., and Sheth, A. P. (2009). Service level agreement in cloud computing. In Cloud Workshops at OOPSLA09.
  21. Roy, N., Dubey, A., and Gokhale, A. (2011). Efficient autoscaling in the cloud using predictive models for workload forecasting. In 2011 IEEE 4th International Conference on Cloud Computing, pages 500-507.
  22. Royden, H. L. and Fitzpatrick, P. (1988). Real Analysis.
  23. Further, it has to fulfill a sufficient condition such as Schlaifer, R. and Raiffa, H. (1961). Applied Statistical Decision Theory. Division of Research, Harvard Business School.
  24. Talia, D. (2013). Toward cloud-based big-data analytics. IEEE Computer Science, pages 98-101.
  25. thyssenkrupp Elevator AG (2016). MAX - the game changing predictive maintenance service for elevators. TKElevator-Broschure EN, Elevator Technology, Essen.
  26. Truong, H.-L. and Dustdar, S. (2010). Composable cost estimation and monitoring for computational applications in cloud computing environments. Procedia Computer Science, 1(1):2175-2184.
  27. Van Houtum, G. J. and Zijm, W. H. M. (2000). On the relationship between cost and service models for general inventory systems. Statistica Neerlandica, 54(2):127- 147.
  28. Vargo, S. L. and Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68(1):1-17.
  29. Wieder, P., Butler, J. M., Theilmann, W., and Yahyapour, R., editors (2011). Service Level Agreements for Cloud Computing. Springer, New York.
  30. Wu, L., Garg, S. K., Versteeg, S., and Buyya, R. (2014). SLA-Based Resource Provisioning for Hosted Softwareas-a-Service Applications in Cloud Computing Environments. IEEE Transactions on Services Computing, 3:465-485.
  31. Yan, J. (2015). Machinery Prognostics and Prognosis Oriented Maintenance Management. John Wiley & Sons, Singapore.
  32. Yildirim, I., Tan, B., and Karaesmen, F. (2005). A multiperiod stochastic production planning and sourcing problem with service level constraints. OR Spectrum, 27(2- 3):471-489.
  33. Zott, C., Amit, R., and Massa, L. (2011). The business model: recent developments and future research. Journal of management, 37(4):1019-1042.
Download


Paper Citation


in Harvard Style

Christ M., Neuffer J. and Kempa-Liehr A. (2017). On the Implicit Cost Structure of Service Levels from the Perspective of the Service Consumer . In Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-243-1, pages 531-538. DOI: 10.5220/0006310505310538


in Bibtex Style

@conference{closer17,
author={Maximilian Christ and Julius Neuffer and Andreas W. Kempa-Liehr},
title={On the Implicit Cost Structure of Service Levels from the Perspective of the Service Consumer},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2017},
pages={531-538},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006310505310538},
isbn={978-989-758-243-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - On the Implicit Cost Structure of Service Levels from the Perspective of the Service Consumer
SN - 978-989-758-243-1
AU - Christ M.
AU - Neuffer J.
AU - Kempa-Liehr A.
PY - 2017
SP - 531
EP - 538
DO - 10.5220/0006310505310538