Managing Imprecise Criteria in Cloud Service Ranking with a Fuzzy Multi-criteria Decision Making Method

  • Ioannis Patiniotakis
  • Stamatia Rizou
  • Yiannis Verginadis
  • Gregoris Mentzas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8135)

Abstract

The increase of cloud technology solutions has made the evaluation and selection of desired cloud services, a cumbersome task for the user. In particular, the lack of standard mechanisms that allow the comparison of cloud service specifications against user requirements taking into account the implicit uncertainty and vagueness is a major hindrance during the cloud service evaluation and selection. In this paper, we discuss an alternative classification of metrics used for ranking cloud services based on their level of fuzziness and present an approach that allows cloud service evaluation based on a heterogeneous model of service characteristics. Our approach allows the multi-objective assessment of cloud services in a unified way, taking into account precise and imprecise metrics. We use fuzzy numbers to model the imprecise service characteristics and vague user preferences and we validate a fuzzy AHP approach that solves the problem of service ranking.

Keywords

Cloud Services Ranking Imprecise Criteria Fuzzy MCDM 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ioannis Patiniotakis
    • 1
  • Stamatia Rizou
    • 2
  • Yiannis Verginadis
    • 1
  • Gregoris Mentzas
    • 1
  1. 1.Institute of Communications and Computer SystemsNational Technical University of AthensAthensGreece
  2. 2.European Projects DepartmentSingular Logic S.A.AthensGreece

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