Trust level estimation for cloud service composition with inter-service constraints

Malouche, Hela; Halima, Youssef Ben; Ghezala, Henda Ben

doi:10.1007/s12652-019-01182-9

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…The literature introduces the preprocessing analysis of satellite imagery [ 18 ]. Based on the results of on-site verification and visual interpretation of UAV image data, we use object-oriented classification and a series of trials and errors to determine the scale with the best segmentation effect for various image objects [ 19 ]. This is to achieve the purpose of evaluating classification rules according to levels, as well as the accuracy of classification execution results, and extracting wetland information.…”

Section: Related Workmentioning

confidence: 99%

Using GIS Remote Sensing Image Data for Wetland Monitoring and Environmental Simulation

Cheng

Dang

2022

Computational Intelligence and Neuroscience

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Through a comprehensive theoretical basis and actual test analysis of the application system design and functional efficiency of the cloud platform, this paper puts forward an artificial intelligence environmental data monitoring and wetland environmental simulation method based on GIS remote sensing images. First, the basic storage and computing functions have been enhanced at the physical layer. Second, the middleware layer is more flexible in the use of management methods and strategies. There are many strategies and methods that can be used in combination. Finally, based on this, the application system design framework is more convenient and faster so that you can focus on business logic, and the strategic advantages of certain functions are very obvious. The method of object-oriented classification and visual interpretation using UAV image data and satellite remote sensing images from the typical recovery area and treatment area of wetland from 2016 to 2020 is given in detail together to extract wetland information and use GIS software for dynamic calculation. Using the wetland transmission matrix method, the distribution map of the characteristic types of the survey areas in the four periods and the conversion status of the characteristic types at each stage were obtained, and the effect of wetland treatment was quantitatively studied.

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Section: Related Workmentioning

confidence: 99%

Using GIS Remote Sensing Image Data for Wetland Monitoring and Environmental Simulation

Cheng

Dang

2022

Computational Intelligence and Neuroscience

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“…Cloud Service Selection, a primary concern where N number of services being deployed with many similar matching characteristic that needs to be addressed for the benefits of cloud consumers in a long run. Most perplexing task to find the reliable service from cloud server, hence cloud service recommendation is proposed [21,16] using clustering based on trust degree computation algorithm and service suggestion is given respectively. AHP techniques ensures the weights of user requirements, many researchers implemented for ranking the services as well [1, 7, 8,…”

Section: Related Workmentioning

confidence: 99%

“…Most perplexing task to find the reliable service from cloud server, hence cloud service recommendation is proposed [21,16] using clustering based on trust degree computation algorithm and service suggestion is given respectively. AHP techniques ensures the weights of user requirements, many researchers implemented for ranking the services as well [1,7,8,11,12,19].…”

Section: Related Workmentioning

confidence: 99%

C-DRM: Coalesced P-TOPSIS Entropy Technique addressing Uncertainty in Cloud Service Selection

Nivitha¹,

Pabitha²

2022

ITC

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Cloud Computing is diversified with its services exponentially and lured large number of consumers towards the technology indefinitely. It has become a highly challenging problem to satiate the user requirements. Most of the existing system ingest large search space or provide inappropriate service; hence, there is a need for the reliable and space competent service selection/ranking in the cloud environment. The proposed work introduces a novel pruning method and Dual Ranking Method (DRM) to rank the services from n services in terms of space conserving and providing reliable service quenching the user requirements as well. Dual Ranking Method (DRM) is proposed focusing on the uncertainty of user preferences along with their priorities; converting it to weights with the use of Jensen-Shannon (JS) Entropy Function. The ranking of service is employed through Priority-Technique for Order of Preference by Similarity to Ideal Solution (P-TOPSIS) and space complexity is reduced by novel Utility Pruning method. The performance of the proposed work Clustering – Dual Ranking Method (C-DRM) is estimated in terms of accuracy, Closeness Index (CI) and space complexity have been validated through case study where results outperforms the existing approaches

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“…How to select the desired component services and recommend the satisfactory composite services are very important issues [ 17 ]. The non-functional characteristics of Web services, such as QoS (Quality of Service) and trust, are very essential criteria when selecting and composing the desirable Web services [ 18 , 19 , 20 , 21 ].…”

Section: Introductionmentioning

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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Trust level estimation for cloud service composition with inter-service constraints

Cited by 6 publications

References 27 publications

Using GIS Remote Sensing Image Data for Wetland Monitoring and Environmental Simulation

Using GIS Remote Sensing Image Data for Wetland Monitoring and Environmental Simulation

C-DRM: Coalesced P-TOPSIS Entropy Technique addressing Uncertainty in Cloud Service Selection

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

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