Improved TOPSIS Method Based Trust Evaluation Framework for Determining Trustworthiness of Cloud Service Providers

Sidhu, Jagpreet; Singh, Sarbjeet

doi:10.1007/s10723-016-9363-1

Cited by 59 publications

(26 citation statements)

References 39 publications

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“…The paper [13] presents the design of a trust evaluation framework that uses the compliance monitoring mechanism to determine the trustworthiness of service providers. The compliance values are computed and then processed using an improved TOPSIS method to obtain trust on the service providers.…”

Section: One Of the Most Used Madm Methods Is Technique For Order Prementioning

confidence: 99%

An Extended TOPSIS Approach for Ranking Cloud Service Providers

Rădulescu¹,

Radulescu²

2017

SIC

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There are many Cloud Service Providers (CSPs) in the global cloud computing market and customers may need to use scientific decision making methods for evaluating and ranking the CSPs according to their own requirements. Among the several approaches that have been proposed to solve the CSPs evaluation and ranking problem, there are Multi Attribute Decision Making (MADM) methods. One of the most commonly used MADM method is Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). In this paper, we extend the TOPSIS method by using the Minkowski distance. We propose an Extended TOPSIS (E-TOPSIS) approach by varying the parameter p in the Minkowski distance. The applicability of the proposed E-TOPSIS approach is presented in a case study for CSPs evaluation and ranking in relation to a set of Service Measurement Index -SMI criteria. An analysis of E-TOPSIS solutions and the CSPs order change relative to parameter p variation is realized. A comparison of the E-TOPSIS solutions with TOPSIS solution is presented.

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Section: One Of the Most Used Madm Methods Is Technique For Order Prementioning

confidence: 99%

An Extended TOPSIS Approach for Ranking Cloud Service Providers

Rădulescu¹,

Radulescu²

2017

SIC

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“…The authors do not focus on consideration of user requirements for attributes, in evaluating trust value of a resource. Frameworks are proposed by [25,26] for trust evaluation of cloud service providers based on QoS attributes. The approaches are based on monitoring QoS attributes and evaluating the compliance with regard to the SLA.…”

Section: Related Workmentioning

confidence: 99%

“…The approach takes into account QoS requirements of user and computes the trust of a service based on fulfillment of the requirements. However, the approaches [11,25,26,27] do not offer dynamic trust update in cloud environment. A model is proposed by Manuel [28] to evaluate trust of a resource based on its capabilities and measured QoS attributes.…”

Section: Related Workmentioning

confidence: 99%

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Preferences based Customized Trust Model for Assessment of Cloud Services

Deshpande¹,

Ingle²

2018

IJECE

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In cloud environment, many functionally similar cloud services are available. But, the services differ in Quality of Service (QoS) levels, offered by them. There is a diversity in user requirements about the expected qualities of cloud services. Trust is a measure to understand whether a cloud service can adequately meet the user requirements. Consequently, trust assessment plays a significant role in selecting the suitable cloud service. This paper proposes preferences based customized trust model (PBCTM) for trust assessment of cloud services. PBCTM takes into account user requirements about the expected quality of services in the form of preferences. Accordingly, it performs customized trust assessment based on the evidences of various attributes of cloud service. PBCTM enables elastic trust computation, which is responsive to dynamically changing user preferences with time. The model facilitates dynamic trust based periodic selection of cloud services according to varying user preferences. Experimental results demonstrate that the proposed preferences based customized trust model outperforms the other model in respect of accuracy and degree of satisfaction.Copyright c 2018 Institute of Advanced Engineering and Science.All rights reserved.Corresponding Author: Shilpa Deshpande, Department of Computer Engineering, College of Engineering Pune, Savitribai Phule Pune University, Pune, Maharashtra, India Email: shilpshree@yahoo.com INTRODUCTIONCloud computing has entered mainstream and received wider acceptance. It is increasingly adopted by individuals, small and medium scale enterprises (SMEs) and government organizations to run their critical applications. The reason for this acceptance is the characteristics of cloud like scalability, on demand service, anytime-anywhere access, economic benefits of pay-per-use, delegation of maintenance and administration, performance and disaster recovery. Cloud services have proliferated to include software as a service, database as a service, platform as a service, infrastructure as a service, security as a service and storage as a service [1]. Cloud environment still remains challenging to rely on because of factors like loss of control over applications and data, increased threats of security [2], performance issues related to virtualization [3], enterprise grade availability requirements [4,5,6] and adequately meeting Quality of Service (QoS) expectations of users [7].Cloud computing has compelling advantages yet challenges too. For an enterprise to adopt cloud, it is important that enterprise has a certain belief that advantages of cloud can be realized. Trust is a measure of this belief [8]. Conventionally, people rely on reputation [4,8], service level agreement (SLA) [6,9], self-assessment [8,9] and cloud auditing [8,9] for trust assessment in cloud environment. However, trust assessment in cloud environment poses further important issues, which are revealed as part of the following discussion.Reputation based traditional trust assessment technique relies on ...

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“…As already defined, trustworthiness is the adherence or compliance of a CSP to promised quantitative QoS parameters as defined in a Service Level Agreement (SLA), we defined some important QoS parameters. Many of these QoS parameters can be computed automatically whereas others require manual intervention for their computation [39].…”

Section: Trust Evaluation and Qos Parametersmentioning

confidence: 99%