Selection problem of cloud solution for big data accessing : fuzzy AHP-PROMETHEE as a proposed methodology

At present, many organizations try to gain value from their exponential growth of data by implementing new available technologies, processes and governance mechanisms, such as big data and Cloud computing. According to Gartner and Mackinsey predictions, big data has been largely adopted in 2013. Effectively, nowadays the challenge now is how to ensure an effective analysis and management of large-scale data by minimizing all the costs related to accessing and processing those data. The huge commitment of hardware and processing resources often needed when using big data, is one of the limitations that must be taken into consideration. Since the technology is permanently subject to advances and development, the question for many businesses is how they can benefit from big data using the power of technique flexibility that Cloud computing can provide. In this paper, we propose a decisional methodology based on Fuzzy Analytic Hierarchy Process (FAHP) and PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluations) for comparing, ranking and selecting the most suitable Cloud computing to accommodate and access big data. Due to the varying importance of the used criteria, we develop fuzzy AHP software based on extent analysis method to assign the importance weights to evaluation criteria, while the PROMETHEE process exploits these weighted criteria as input to evaluate and rank the decision alternatives. Subject Categories and Descriptors I.5 [Pattern Recognition]: Fuzzy set H.2 [Database Management] General Terms Fuzzy, Big Data, Cloud computing