FASTCloud: A framework of assessment and selection for trustworthy cloud service based on QoS
release_cwqe2b7g7jcifevlimck5rcuhq
by
Xiang Li
2020
Abstract
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 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.
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