An efficient two-phase approach for reliable collaboration-aware service composition in cloud manufacturing

Xie, Na; Tan, Wenan; Zheng, Xianrong; Zhao, Lu; Huang, Li; Sun, Yong

doi:10.1016/j.jii.2021.100211

Cited by 34 publications

(20 citation statements)

References 43 publications

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“…Based on the internet, IoT and other related technologies such as distributed networks, completely automated protocols, and competitive production networks are driving Industry 4.0. The integration of leading technology players such as IoT, Blockchain, big data, edge and cloud computing, robotics, artificial intelligence, and open-source software has extended the scope of Industry 4.0, benefiting both industry and partners [99]. Incorporating these players into Industry 4.0 creates an integrated and automated system (a cyber-physical system, or CPS), turning the industrial infrastructure into an autonomous and dynamic system.…”

Section: Industry 40 and Blockchain Technologymentioning

confidence: 99%

A taxonomy study on securing Blockchain-based Industrial applications: An overview, application perspectives, requirements, attacks, countermeasures, and open issues

Hameed

Barika

Garg

et al. 2022

Journal of Industrial Information Integration

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Section: Industry 40 and Blockchain Technologymentioning

confidence: 99%

A taxonomy study on securing Blockchain-based Industrial applications: An overview, application perspectives, requirements, attacks, countermeasures, and open issues

Hameed

Barika

Garg

et al. 2022

Journal of Industrial Information Integration

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“…A service workflow, i.e., a composite service, includes a set of tasks [ 37 ]. According to service planning, there may be more than one way to build a composite service [ 36 ].…”

Section: Motivationmentioning

confidence: 99%

A Comprehensive and Unified Approach to Web Service Trust Evaluation Based on Uncertainty Methodology

Zhang

2022

Entropy

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Web services have the advantage of being able to generate new value-added services based on existing services. To effectively compose Web services, the composition process necessitates that the services that will participate in a given composite service are more trustworthy than those that provide similar functionality. The trust mechanism appears to be a promising way for determining service selection and composition. Existing trust evaluation approaches do not take into account customer expectations. Based on fuzzy set theory and probability theory, this work proposes a unique Web service trust evaluation approach that is notable for its ability to provide personalized service selection based on customer expectations and preferences. The proposed approach defines trust as a fuzzy notion that is related to prior experiences and ratings, and expresses trust in two different forms. This work mainly solves two key issues in Web service trust architectures, bootstrapping trust for the newcomer services and deriving trust for composite services. The proposed approach combines the solutions to numerous issues in a natural way. The case study and approaches comparison demonstrate that the proposed approach is feasible.

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“…Service selection [7,[9][10][11][12][13][14][15][16][17][18][19][20][21][22] is one of the most challenging research topics for cloud computing researchers, especially when multiple CSPs are taken into consideration. This paper reports three types of studies: the MCDM algorithms for selecting CSP, objective and subjective weighting techniques, and cloud service composition.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed algorithm helps the ACO algorithm to avoid stagnation problems and improve its performance. Xie et al [22] have proposed an efficient two-phase approach to solve the reliability issue in the cloud service composition. They have integrated the k-means clustering technique and chaos gauss-based particle swarm optimization (CG-PSO) to improve the QoS and reduce the searching space in order to find the optimal service composition.…”

Section: Cloud Service Compositionmentioning

confidence: 99%

An efficient composite cloud service model using multi-criteria decision-making techniques

et al. 2022

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Recent advancements in information technology (IT) have made cloud computing one of the most prominent technologies. It is most favorable for the bundle of services that it provides to its users. Since there is a wide range of cloud service providers (CSPs) with various services, it is challenging for the user to select a CSP that can meet all of its requirements. In this paper, we propose a composite cloud service (CCS) model, which is handled by a cloud agent, to identify the best cloud services/criteria from a set of CSPs by considering the objective and subjective opinions collected from the cloud users' feedback and reviews. Note that the cloud agent is an intermediary between the users and CSPs. Then the agent recommends the CSPs to assemble the identified services into unified group services to fulfill the users' requirements. Our model calculates the integrated objective and subjective weight of alternatives for a set of criteria and determines the best alternative for each criterion. For this, the application of two multi-criteria decision-making (MCDM) techniques, namely method based on the removal effect of criteria (MEREC) and extended step-wise weight assessment ratio analysis (ESWARA), are used to calculate the objective and subjective

show abstract

An efficient two-phase approach for reliable collaboration-aware service composition in cloud manufacturing

Cited by 34 publications

References 43 publications

A taxonomy study on securing Blockchain-based Industrial applications: An overview, application perspectives, requirements, attacks, countermeasures, and open issues

A taxonomy study on securing Blockchain-based Industrial applications: An overview, application perspectives, requirements, attacks, countermeasures, and open issues

A Comprehensive and Unified Approach to Web Service Trust Evaluation Based on Uncertainty Methodology

An efficient composite cloud service model using multi-criteria decision-making techniques

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