Evaluating the efficiency of cloud services using modified data envelopment analysis and modified super-efficiency data envelopment analysis
- 337 Downloads
Several cloud services with comparable functionality are now available to customers at different prices and performance levels. Often, there may be trade-offs among different functional and non-functional requirements fulfilled by different cloud providers. Hence, it is difficult to evaluate the relative performances of the cloud services and their ranking based on various quality of service attributes. In this paper, we propose a modified data envelopment analysis and a modified super-efficiency data envelopment analysis for evaluating the cloud services and their efficiencies considering user preferences. We compare these methods of cloud service selection based on sensitivity analysis, adequacy to changes in DMUs, adequacy to support decision making and modeling of uncertainty. The comparison helps customers to choose a cloud service that is most suitable to their requirements and also creates a healthy competition among the cloud service providers.
KeywordsCloud computing Data envelopment analysis Multi-criteria decision making Analytic hierarchy process Analytic network process
We thank Saurabh Kumar (IIT, Kanpur, India) and Akshay Jaiswal (IIT-BHU, Varanasi, India) for their help in implementing parts of DEA and SDEA (during their internships at IDRBT) in this work.
Compliance with ethical standards
Conflict of interest
Chandrashekar Jatoth declares that he has no conflict of interest. G. R. Gangadharan declares that he has no conflict of interest. Ugo Fiore declares that he has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- Bedi P, Kaur H, Gupta B (2012) Trustworthy service provider selection in cloud computing environment. In: Proceedings of the 2012 international conference on communication systems and network technologies, IEEE, pp 714–719Google Scholar
- Buyya R, Broberg J, Goscinski AM (2010) Cloud computing: principles and paradigms. Wiley, New JerseyGoogle Scholar
- Chandrashekar J, Gangadharan GR, Buyya R (2016) Computational intelligence based qos-aware web service composition: a systematic literature review. IEEE Trans Serv Comput. doi: 10.1109/TSC.2015.2473840
- Esposito C, Ficco M, Palmieri F, Castiglione A (2015) Smart cloud storage service selection based on fuzzy logic, theory of evidence and game theory. IEEE Trans Comput. doi: 10.1109/TC.2015.2389952
- Kwon HK, Seo KK (2013) A decision-making model to choose a cloud service using fuzzy ahp. Adv Sci Technol Lett 35:93–96Google Scholar
- Li A, Yang X, Kandula S, Zhang M (2010) Cloudcmp: comparing public cloud providers. In: Proceedings of the 10th ACM SIGCOMM conference on internet measurement, ACM, pp 1–14Google Scholar
- Saaty T (1980) Fundamentals of decision making and priority theory with analytical hierarchical process, vol 6. RWS Publications, University of Pittsburgh, PittusburghGoogle Scholar
- Saaty TL (1996) Analytical network process. RWS Publications, PittsburghGoogle Scholar
- Shivakumar U, Ravi V, Gangadharan GR (2013) Ranking cloud services using fuzzy multi-attribute decision making. In: Proceedings of the IEEE international conference on fuzzy systems, pp 1–8Google Scholar
- Xu C, Ma Y, Wang X (2015) A non-parametric data envelopment analysis approach for cloud services evaluation. In: Proceedings of the service-oriented computing-ICSOC 2014 workshops, Springer, pp 250–255Google Scholar
- Yan S, Chen C, Zhao G, Lee BS (2012) Cloud service recommendation and selection for enterprises. In: Proceedings of the 8th international conference on network and service management and workshop on systems virtualization management, IEEE, pp 430–434Google Scholar