An Enhanced MCDM Model for Cloud Service Provider Selection

Abstract

Multi-Criteria Decision-Making (MCDM) techniques are often used to aid decision-makers in selecting the best alternative among several options. However, these systems have issues, including the Rank Reversal Problem (RRP) and decision-making ambiguity. This study aimed to propose a selection model for a Cloud Service Provider (CSP) that addresses these issues. This research used the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives. The entropy technique is utilized to determine the weight of the criteria, and Single Valued Neutrosophic (SVN) is employed to address uncertainty. To select the best cloud provider based on Quality of Service (QoS) criteria, we used a dataset from Cloud Harmony for this study. The results indicated that the suggested model could effectively resolve the RRP under conditions of uncertainty. This research is novel and is the first to address both the problem of uncertainty in decision-making and RRP in MCDM.

Cloud service ranking with an integration of k-means algorithm and decision-making trail and evaluation laboratory approach

“…It provides three distinct service models which are infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). These Service model also knowns as an internet Stack and meet a unique business need [5]. All the offered Services through computing stack are utilized efficiently between consumers through deployment model.…”

“…Many authors rambled on about different strategies for making decisions based on multiple criteria [4]. Abdelaziz et al [5] considered the cloud computing service paradigm and described the MCDM strategy. Alabool et al [6] also conducted a review based on the MCDM approach for evaluating cloud services and focused on cloud services as a fuzzy multicriteria dilemma [7].…”

New AHP Improvement using COMET Method Characteristic to Eliminate Rank Reversal Phenomenon

“…According to the literature on decision-making, several methods suffer from this phenomenon, and one of them is AHP [5]. From 2020 era until 2023 the RRP research focused on the new method and/or the enhancement of the old method in MCDM with the additional Fuzzy to eliminate RRP such as AHP and TOPSIS method [6][7] [8]. www.ijacsa.thesai.org AHP as the method that applied for the last 25 years in many MCDM decision-making, has been used in lots of decisions in various fields.…”