Abstract
With the increasing use of cloud computing, it is very important for the Cloud users to analyze and compare performance of the Cloud services. Since Cloud services selection problem contains several conflicting criteria, it is considered as a multi-criteria decision making (MCDM) problem. On another side, one of the most popular unsupervised data mining methods is Clustering which is used for grouping set of objects. The contribution of this paper is to propose an approach based on clustering, Pareto Optimal and MCDM methods. Our approach allows users to specify the quality requirements of the cloud services they want to use. It consists of three steps: in the first step, we use the clustering, more precisely the artificial neural network, to minimize the very large number of cloud services on the Net. In the second step, we apply Pareto Optimal algorithm to select non-dominated services. Finally, in the third step, we use the weights provided by the user to select the most appropriate cloud service for these requirements. To demonstrate the effectiveness of the proposed approach, a case study is presented.
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References
Hioual, O., Boufaïda, Z., Hemam, S.M.: Load balancing, cost and response time minimisation issues in agent-based multi cloud service composition. Int. J. Internet Protoc. Technol. 10, 73–88 (2017). https://doi.org/10.1504/IJIPT.2017.085187
Lloyd, S.: Least squares quantization in PCM. IEEE Trans. Inf. Theory 28, 129–137 (1982)
Hemam, S.M., Hioual, O.: A hybrid load balancing algorithm for P2P-cloud system aware of constraints optimisation of cost and reliability criteria. Int. J. Internet Protoc. Technol. 10, 99–114 (2017). https://doi.org/10.1504/IJIPT.2017.085189
Zeng, W., Zhao, Y., Zeng, J.: Cloud service and service selection algorithm research. In: Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation. pp. 1045–1048 (2009)
Kang, J., Sim, K.M.: Cloudle: a multi-criteria cloud service search engine. In: 2010 IEEE Asia-Pacific Services Computing Conference, pp. 339–346. IEEE (2010)
Resnik, P.: Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. J. Artif. Intell. Res. 11, 95–130 (1999)
Kang, J., Sim, K.M.: Cloudle: An agent-based cloud search engine that consults a cloud ontology. In: Cloud Computing and Virtualization Conference, pp. 312–318. Citeseer (2010)
Yoo, H., Hur, C., Kim, S., Kim, Y.: An Ontology-Based Resource Selection Service on Science Cloud. In: Ślęzak, D., Kim, T., Yau, S., Gervasi, O., Kang, B. (eds.) GDC 2009. CCIS, vol. 63, pp. 221–228. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10549-4_26
Zeng, C., Guo, X., Ou, W., Han, D.: Cloud Computing Service Composition and Search Based on Semantic. In: Jaatun, M., Zhao, G., Rong, C. (eds.) CloudCom 2009. LNCS, vol. 5931, pp. 290–300. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10665-1_26
Sun, L., Dong, H., Hussain, F.K., Hussain, O.K., Chang, E.: Cloud service selection: state-of-the-art and future research directions. J. Netw. Comput. Appl. 45, 134–150 (2014)
Saaty, T.L.: The analytic hierarchy process for decision in a complex world. Pittsburgh RWS Publ. (1980)
Satty, T.L.: Decisions with the analytic network process (ANP). Univ. Pittsburgh (USA), ISAHP (1996)
Churchman, C.W., Ackoff, R.L., Arnoff, E.L.: Introduction to operations research (1957)
Roy, B.: The Outranking Approach and the Foundations of the ELECTRE Methods. Theory and Decision (1991)
Godse, M., Mulik, S.: An approach for selecting software-as-a-service (SaaS) product. In: 2009 IEEE International Conference on Cloud Computing, pp. 155–158. IEEE (2009)
Karim, R., Ding, C., Miri, A.: An end-to-end QoS mapping approach for cloud service selection. In: 2013 IEEE Ninth World Congress On Services, pp. 341–348. IEEE (2013)
Tripathi, A., Pathak, I., Vidyarthi, D.P.: Integration of analytic network process with service measurement index framework for cloud service provider selection. Concurr. Comput. Pract. Exp. 29, e4144 (2017)
Tzeng, G.-H., Huang, J.-J.: Multiple Attribute Decision Making: Methods And Applications. CRC Press, USA (2011)
Van Rossum, G., Drake, F.L.: The Python Language Reference Manual. Network Theory Limited, UK (2011)
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Hioual, O., Hioual, O., Hemam, S.M. (2021). A Hybrid Approach for Clustering and Selecting of Cloud Services Based on User Preferences Evaluation. In: Kahraman, C., Cevik Onar, S., Oztaysi, B., Sari, I., Cebi, S., Tolga, A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197. Springer, Cham. https://doi.org/10.1007/978-3-030-51156-2_9
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