Fuzzy logic based cloud service trustworthiness model

Pandey, Sarvesh; Daniel, A. K.

doi:10.1109/icetech.2016.7569215

Cited by 9 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fuzzy logic is adopted in our study as it is the most widely adopted approach in evaluating trust as applied in several studies [24] [25] [26]. In [26] QoS, reputation, security aspects and social relationships are taken into account in their fuzzy control system.…”

Section: Trust Evaluation Using Fuzzy Logicmentioning

confidence: 99%

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

Rahman

Newaz

et al. 2020

Future Generation Computer Systems

View full text Add to dashboard Cite

Find My Trustworthy Fogs: A Fuzzy-based Trust Evaluation Frameworkhttp://researchonline.ljmu.ac.uk/id/eprint/8724/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively. AbstractThe growth of IoT is proven with the massive amount of data generated in 2015, and expected to be even more in the years to come. Relying on the cloud to meet the expanding volume, variety, and velocity of data that the IoT generates may not be feasible. In the last two years, fog computing has become a considerably important research topic in an attempt to reduce the burden on cloud and solve cloud's inability to meet the IoT latency requirement. However, fog environment is different than in cloud since fog environment is far more distributed. Due to the dynamic nature of fog, backups such as redundant power supply would deem unnecessary, and relying on just one Internet Service Provider for their fog device would be sufficient. If obstacles arise in this fog environment, factors such as latency, availability or reliability would in turn be unstable. Fogs become harder to trust, and this issue is more complicated and challenging in comparison to the conventional cloud. This implies that trustworthiness in fog is an imperative issue that needs to be addressed. With the help of a broker, managing trust in a distributive environment can be tackled. Acting as an intermediary, a broker helps in facilitating negotiation between two parties. Although the brokering concept has been around for a long time and is widely used in the cloud, it is a new concept in fog computing. As of late, there are several research studies that incorporates broker in fog where these brokers focus towards pricing management. However to the best of our knowledge there is no literature on broker-based trust evaluation in fog service allocation. This is the first work that proposes broker-based trust evaluation framework that focuses on identifying a trustworthy fog to fulfill the user requests. In this paper, fuzzy logic is used as the basis for the evaluation while considering the availability and cost of fog. We propose Request Matching algorithm to identify a user request, and Fuzzybased Filtering algorithm to match the request with one of the predefined sets created and managed by the broker. In this paper, we present a use case that illustrates how fuzzy logic works in determining the trustworthiness of a fog. Our findings suggest that the algorithms can successfully provide users a trustworthy fog that matches their requirement. .bn (Wida Susanty Suhaili), g.m.lee@ljmu.ac.uk (Gyu-Myoung Lee)

show abstract

Section: Trust Evaluation Using Fuzzy Logicmentioning

confidence: 99%

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

Rahman

Newaz

et al. 2020

Future Generation Computer Systems

View full text Add to dashboard Cite

show abstract

“…Usability is an attribute of a product that measures to what extent it can be usable by different users with efficiency, effectiveness and satisfaction to achieve their determined goals (ISO 1998a) (Pandey & Daniel, 2016). Also usability refers to the ability of a product to be understood, learned, operated and is habitually verified from its interfaces (Baharuddin, Singh & Razali, 2013;Thomas, Onyimbo & Logeswaran, 2016).…”

Section: Usability (C47)mentioning

confidence: 99%

A Proposition of Modifications and Extensions of Cloud Computing Standards for Trust Characteristics Measures

Eftekhar¹,

Suryn²

2019

CIS

View full text Add to dashboard Cite

In recent years, we have witnessed a marked rise in the number of cloud service providers with each offering a plethora of cloud services with different objectives. Gaining confidence for cloud technology adoption as well as selecting a suitable cloud service provider, both require a proper evaluation of cloud service trust characteristics. Hence, the evaluation of cloud services before used by the customer is of utmost importance. In this article, we adapt the extracted trust characteristics from both system and software quality standards and cloud computing standards, for evaluating cloud services. Moreover, we derive measures for each trust characteristics to evaluate the trustworthiness of different cloud service providers, and generalize these trust measures for any type of cloud services (e.g. Software as a Service, Platform as a Service, and Infrastructure as a Service). Our work thereby demonstrates a way to apply generalized trust measures for cloud services and therefore contributes to a better understanding of cloud services to evaluate their quality characteristics. As part of our ongoing research, the results of this study will be used to develop a comprehensive cloud trust model.

show abstract

“…The definition of cloud service trustworthiness varies according to the applications & the organizations [5]. A cloud service trustworthiness can be defined as the degree of confidence of cloud service to meet the set of requirements [1]. It is evaluated in terms of degree of confidence and set of requirements.…”

Section: Related Workmentioning

confidence: 99%

QoCS and Cost Based Cloud Service Selection Framework

Pandey¹,

Daniel²

2017

IJETT

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a QoCS and Cost Based Cloud Service Selection Framework based on fuzzy logicIt is a trustworthiness framework which helps in analyzing any cloud service in detail with multidimensional perspectives. It specifically analyze the trustworthiness of cloud service by using a set of parameters as Security, Finance, Maintainability, Reliability, and Usability. These parameters are collectively termed as quality of cloud service (QoCS) parameter. The framework is based on finance parameter as a major characteristic for selection of cloud service. Practical results show that the model improves the QoCS as well as assist the customer in making decision about the selection of cloud service based on their financial constraints from among the different cloud service providers for the same type of services.

show abstract

Fuzzy logic based cloud service trustworthiness model

Cited by 9 publications

References 8 publications

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

A Proposition of Modifications and Extensions of Cloud Computing Standards for Trust Characteristics Measures

QoCS and Cost Based Cloud Service Selection Framework

Contact Info

Product

Resources

About