Selecting cloud computing service provider with fuzzy AHP

Abstract

Abstract-With the growing demand for outsourcing the ICT section of enterprises, Cloud Computing service providers increased their popularity. Selecting the most appropriate provider for a demanding enterprise depends on many criteria that are based on the strategies, requirements, and resources of the enterprise. Since this problem is a kind of decision problem and depends on criteria of decisionmaker, it can be modeled as Multi-criteria Decision Making (MCDM) problem. In this research, a pilot case study is conducted in which the Cloud Computing service provider selection problem is modeled as a MCDM problem. For selecting the most appropriate provider, Fuzzy Extend Analysis is implemented in the case study.

Cloud broker proposal based on multicriteria decision‐making and virtual infrastructure migration

“…Related to IaaS cloud provider selection, the analysis and selection of IaaS providers is based on the multicriteria decision-making (MCDM) method to qualify IaaS providers is a promising alternative. 10,[12][13][14] MCDM enabled a near-optimal mapping of virtual requests on cloud providers by performing simultaneous analysis of a set of relevant variables and candidates. In this work, the MCDM is guided by multiple criteria and trade-offs: energy versus performance and consolidation versus availability, among others.…”

“…The specialized literature proposed the use of AHP-based models to select providers and servers, highlighting the efficiency and impact of AHP parameterization to align provider objectives and the allocation results. 10,[12][13][14] However, the majority of proposals (discussed in Section 3) consider only the selection of VMs, disregarding the virtual private network details. The present work innovates by adding virtual network requirements to quality of service (QOS) and cost hierarchical weight schema used to guide the AHP model.…”

“…The second step is a comparison based on public market share data. The AHP weighting tables proposed by fuzzy AHP (FAHP) were selected for composing the baseline for comparison. The six criteria originally identified by FAHP (cost, availability, storage capacity, CPU capacity, performance indicator, and security) were slightly adapted to fit the VIMAM model.…”

“…The analytic hierarchy process (AHP) method stands out to make a decision with trade‐off and multicriteria, allowing to set assortment aspects and component hierarchy. The specialized literature proposed the use of AHP‐based models to select providers and servers, highlighting the efficiency and impact of AHP parameterization to align provider objectives and the allocation results . However, the majority of proposals (discussed in Section 3) consider only the selection of VMs, disregarding the virtual private network details.…”

Decision Support System for Developer Selection of The Project in TBIG Using The Fuzzy Ahp Method

“…[3] in their research developed the Fuzzy AHP method for the problem of university academic staff selection, while the variables used in decision making are: Academic Qualification, Research Experience, Individual Factor, while the results of this study are that Fuzzy AHP is proven to be a more useful tool for solving multi-criteria decision problems with uncertainty. The results show that the alternative with the highest normalized weight is the most suitable candidate to be selected [5] proposes a decision-making system that chooses the most appropriate Cloud Computing service provider using the fuzzy ahp method with the criteria used are Acquisition and transaction costs, Availability, Storage capacity, CPU, Performance, Security. From this research, 5 alternative cloud computing provider options have been ranked [6] proposed a decision-making system to assist in the selection of notebooks using the fuzzy ahp method, with the criteria used are weight, memory, processor, ram, price, and hard drive.…”