Design and Comparative Analysis of MCDM-based Multi-dimensional Trust Evaluation Schemes for Determining Trustworthiness of Cloud Service Providers

Sidhu, Jagpreet; Singh, Sarbjeet

doi:10.1007/s10723-017-9396-0

Cited by 25 publications

(8 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The work in [34] evaluated trustworthiness of CSPs based on compliance values of CSPs, which were further processed using a variant of TOPSIS. The study in [33] compared three MCDM approaches (PROMETHEE, TOPSIS, and AHP) for determining multi-perspective trustworthiness of CSPs.…”

Section: B Rank Cloud Services Using Vikor Methodsmentioning

confidence: 99%

Evaluating and Ranking Cloud IaaS, PaaS and SaaS Models Based on Functional and Non-Functional Key Performance Indicators

Nadeem

2022

IEEE Access

View full text Add to dashboard Cite

With the recent maturity of Cloud computing technology and the flexibility of the Cloud services, the offering of Cloud services has spread exponentially. Different Cloud service providers offer their services highlighting different features of their services. Because of the diversity of Cloud services and their highlighted features, the choice of the most suitable Cloud service is a complex problem for the Cloud users. Many Cloud users are unable to identify the Cloud services that best suit their needs and thus choose an unsuitable Cloud service, which results in financial loses as well as time delays. To this end, in this study, we propose an efficient three layered framework for evaluating and ranking IaaS, PaaS and SaaS Cloud services. We identified the functional and non-functional key performance indicators (KPIs) for Cloud services from 6 KPI classes. We classified these KPIs with respect to their types and criticality so that the Cloud user can easily choose according to his needs. The relative importance of the KPIs was determined using CRITIC method. We combined the KPIs values and their relative importance for an overall evaluation and ranking of the Cloud services using Vikor method. A case study is also presented for a step by step demonstration of the proposed method.

show abstract

Section: B Rank Cloud Services Using Vikor Methodsmentioning

confidence: 99%

Evaluating and Ranking Cloud IaaS, PaaS and SaaS Models Based on Functional and Non-Functional Key Performance Indicators

Nadeem

2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…a) Trustworthy Services: Service trust solutions adopt different trust assessment solutions: fuzzy [3], probabilistic [4], machine learning [5], multi-criteria decision-making (MCDM) [6] and classical mathematical such as weighted-addition [7]. Service trust evaluation can be subjective [8], objective [7] and hybrid [9].…”

Section: Related Workmentioning

confidence: 99%

QoS-based Trust Evaluation for Data Services as a Black Box

Romdhani

Vargas-Solar

Bennani

et al. 2021

2021 IEEE International Conference on Web Services (ICWS)

View full text Add to dashboard Cite

“…This methodology assigns various ranks to cloud services based on the quantified QoS parameters using a novel extended grey TOPSIS integrated with analytical hierarchical process (AHP). In [10], three multiple criteria decision making (MCDM)-based multi-dimensional trust assessment schemes have been presented, which assess trustworthiness of CSPs by monitoring compliance provided by CSPs against the set SLAs. These schemes adopt three MCDM methods (AHP, TOPSIS and PROMETHEE) respectively that enable CSCs to determine the trustworthiness of a CSP from different perspectives.…”

Section: Related Workmentioning

confidence: 99%

“…The maximum and minimum values of these candidate CPSs on each QoS attribute are taken as their actual SLO interval, as shown in Table III. First, the normalized decision matrix of candidate CSPs R can be constructed by the data of Table III and equations ( 8) - (10), as shown in Figure 3.…”

Section: Case Studymentioning

confidence: 99%

“…• Step 1: In this step, a decision matrix consisting of the actual SLO values of m CSPs on the n QoS attributes needs to be constructed and normalized. Since the n QoS attributes may belong to different types (i.e., benefit and cost), in the worst case, the elements r ik in the decision matrix R m×n need to be normalized by equation ( 9) and (10). Thus, the time complexity of constructing the normalized decision matrix is:…”

Section: Time Complexity Of Tammentioning

confidence: 99%

See 1 more Smart Citation

FASTCloud: A framework of assessment and selection for trustworthy cloud service based on QoS

Li¹

2020

Preprint

View full text Add to dashboard Cite

By virtue of technology and benefit advantages, cloud computing has increasingly attracted a large number of potential cloud consumers (PCC) plan to migrate traditional business to the cloud service. However, trust has become one of the most challenging issues that prevent the PCC from adopting cloud services, especially in trustworthy cloud service selection. In addition, due to the diversity and dynamic of quality of service (QoS) in cloud environment, the existing trust assessment methods based on the single constant value of QoS attribute and the subjective weight assignment are not good enough to provides an effective solution for PCCs to identify and select a trustworthy cloud service among a wide range of functionally-equivalent cloud service providers (CSP). To address the challenge, a novel assessment and selection framework for trustworthy cloud service, FASTCloud, is proposed in this study. This framework facilitate PCCs to select a trustworthy cloud service based on their actual QoS requirements. In order to accurately and efficiently assess the trust level of cloud services, a QoS-based trust assessment model is proposed. This model represents a trust level assessment method based on the interval multiple attributes with a objective weight assignment method based on the deviation maximization to adaptively determine the trust level of different cloud services provisioned by candidate CSPs. The advantage of proposed trust level assessment method in time complexity is demonstrated by the performance analysis

show abstract

Design and Comparative Analysis of MCDM-based Multi-dimensional Trust Evaluation Schemes for Determining Trustworthiness of Cloud Service Providers

Abstract: This paper presents the design and comparative analysis of MCDM-based multi-dimensional trust evaluation schemes for determining trustworthi

Cited by 25 publications

References 40 publications

Evaluating and Ranking Cloud IaaS, PaaS and SaaS Models Based on Functional and Non-Functional Key Performance Indicators

Evaluating and Ranking Cloud IaaS, PaaS and SaaS Models Based on Functional and Non-Functional Key Performance Indicators

QoS-based Trust Evaluation for Data Services as a Black Box

FASTCloud: A framework of assessment and selection for trustworthy cloud service based on QoS

Contact Info

Product

Resources

About