Dataset Information

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

ABSTRACT: Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard's Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments.

SUBMITTER: Pan Y

PROVIDER: S-EPMC4659544 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

Pan Yuchen Y Ding Shuai S Fan Wenjuan W Li Jing J Yang Shanlin S

PloS one 20151125 11

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service sel ...[more]

PMID: 26606388

Similar Datasets

Project description:UnlabelledThe aims of this study are to develop a cloud-based application of the Fracture Liaison Service for practitioners to coordinate the care of osteoporotic patients after suffering primary fractures and provide a performance feedback portal for practitioners to determine quality of care. The application provides continuity of care, improved patient outcomes, and reduced medical costs.IntroductionThe purpose of this study is to describe the content development and functionality of a cloud-based application to broadly deploy the Fracture Liaison Service (FLS) to coordinate post-fracture care for osteoporotic patients.MethodsThe Bone Health Collaborative developed the FLS application in 2013 to support practitioners' access to information and management of patients and provide a feedback portal for practitioners to track their performance in providing quality care. A five-step protocol (identify, inform, initiate, investigate, and iterate) organized osteoporotic post-fracture care-related tasks and timelines for the application. A range of descriptive data about the patient, their medical condition, therapies and care, and current providers can be collected. Seven quality of care measures from the National Quality Forum, The Joint Commission, and the Centers for Medicare and Medicaid Services can be tracked through the application.ResultsThere are five functional areas including home, tasks, measures, improvement, and data. The home, tasks, and data pages are used to enter patient information and coordinate care using the five-step protocol. Measures and improvement pages are used to enter quality measures and provide practitioners with continuous performance feedback. The application resides within a portal, running on a multitenant, private cloud-based Avedis enterprise registry platform. All data are encrypted in transit and users access the application using a password from any common web browser.ConclusionThe application could spread the FLS model of care across the US health care system, provide continuity of care, effectively manage osteoporotic patients, improve outcomes, and reduce medical costs.

Project description:Recently, manufacturing firms and logistics service providers have been encouraged to deploy the most recent features of Information Technology (IT) to prevail in the competitive circumstances of manufacturing industries. Industry 4.0 and Cloud manufacturing (CMfg), accompanied by a service-oriented architecture model, have been regarded as renowned approaches to enable and facilitate the transition of conventional manufacturing business models into more efficient and productive ones. Furthermore, there is an aptness among the manufacturing and logistics businesses as service providers to synergize and cut down the investment and operational costs via sharing logistics fleet and production facilities in the form of outsourcing and consequently increase their profitability. Therefore, due to the Everything as a Service (XaaS) paradigm, efficient service composition is known to be a remarkable issue in the cloud manufacturing paradigm. This issue is challenging due to the service composition problem's large size and complicated computational characteristics. This paper has focused on the considerable number of continually received service requests, which must be prioritized and handled in the minimum possible time while fulfilling the Quality of Service (QoS) parameters. Considering the NP-hard nature and dynamicity of the allocation problem in the Cloud composition problem, heuristic and metaheuristic solving approaches are strongly preferred to obtain optimal or nearly optimal solutions. This study has presented an innovative, time-efficient approach for mutual manufacturing and logistical service composition with the QoS considerations. The method presented in this paper is highly competent in solving large-scale service composition problems time-efficiently while satisfying the optimality gap. A sample dataset has been synthesized to evaluate the outcomes of the developed model compared to earlier research studies. The results show the proposed algorithm can be applied to fulfill the dynamic behavior of manufacturing and logistics service composition due to its efficiency in solving time. The paper has embedded the relation of task and logistic services for cloud service composition in solving algorithm and enhanced the efficiency of resulted matched services. Moreover, considering the possibility of arrival of new services and demands into cloud, the proposed algorithm adapts the service composition algorithm.

Project description:Industry 4.0 is the digitalization of the manufacturing systems based on Information and Communication Technologies (ICT) for developing a manufacturing system to gain efficiency and improve productivity. Cloud Manufacturing (CM) is a paradigm of Industry 4.0. Cloud Manufacturing System (CMS) considers anything as a service. The end product is developed based on the service composition in the CMS according to consumers' needs. Also, composite services are developed based on the interaction of MCS providers from different geographical locations. Therefore, the appropriate Manufacturing Cloud Service (MCS) composition is an important problem based on the real-world conditions in CMS. The game theory studies the mathematical model development based on interactions between MCS providers according to real-world conditions. This research develops an Equilibrial Service Composition Model in Cloud Manufacturing (ESCM) based on game theory. MCS providers and consumers get benefits mutually based on ESCM. MCS providers are players in the game. The payoff function is developed based on a profit function. Also, the game strategies are the levels of Quality of Service (QoS) based on consumers' needs in ESCM. Firstly, the article develops a composite service based on a non-cooperative game. The Nash equilibrium point demonstrates the QoS value of composite service and the payoff value for the players. Secondly, the article develops a composite service based on a cooperative game. The players participate in coalitions to develop the composite service based on formal cooperation. The grand coalition demonstrates the QoS value of composite service and the payoff value for the players in the cooperative game. The research has compared the games' results. The players' payoff and the QoS value are better in the cooperative game than in the non-cooperative game. Therefore, the MCS providers and consumers are satisfied mutually in the cooperative game based on ESCM. Finally, the article has applied ESCM in a Healthcare Service to equip 24 hospitals in the best time.

Dataset Information

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

Publications

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets