FASTCloud: A novel framework of assessment and selection for trustworthy cloud service

TL;DR

FASTCloud is a new framework that helps potential cloud users select trustworthy services by accurately assessing trust levels based on dynamic QoS attributes and objective weighting, improving decision-making in cloud service selection.

Contribution

The paper introduces a novel trust assessment model using interval multiple attributes and deviation maximization for adaptive, efficient trust evaluation in cloud services.

Findings

The trust assessment model is efficient and has favorable time complexity.

Experimental results demonstrate the effectiveness of FASTCloud in trust evaluation.

FASTCloud aids PCCs in selecting trustworthy cloud services effectively.

Abstract

By virtue of technology and benefit advantages, cloud computing has increasingly attracted a large number of potential cloud consumers (PCC) plan to migrate the 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. Besides, due to the diversity and dynamic of quality of service (QoS) in the 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 provide an effective solution for PCCs to identify and select a trustworthy cloud service among a wide range of functionally-equivalent cloud service providers (CSPs). To address the challenge, a novel assessment and selection framework for trustworthy cloud service, FASTCloud, is proposed in this study. This framework facilitates 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 an 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 the proposed trust level assessment method in time complexity is demonstrated by the performance analysis and comparison. The experimental result of a case study with an open-source dataset shows that the trust model is efficient in cloud service trust assessment and the FASTCloud can effectively help PCCs select a trustworthy cloud service.