Selection problem of cloud solution for big data accessing: fuzzy AHPPROMETHEE as a proposed methodology
Omar Boutkhoum, Mohamed Hanine and Tarik Agouti, Abdessadek Tikniouine
Journal of Digital Information Management, Vol. 14, No. 6, 2016.
DOI: 
Link: http://dline.info/fpaper/jdim/v14i6/jdimv14i6_3.pdf
Abstract:
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.