QoSDIST: A QoS Probability Distribution Estimation Tool for Web Service Compositions

Zheng, Huiyuan; Yang, Jian; Zhao, Weiliang

doi:10.1109/apscc.2010.19

Cited by 9 publications

(3 citation statements)

References 12 publications

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“…Finally, we generated the QoS parameters of the services. In this paper, we considered 4 QoS parameters: response time, throughput, reliability, availability and modeled them assuming they follow normal distribution [22]. Once the service repository was created, we generated a random query having random inputs, outputs, input-specifications, output-requirements and QoS constraints.…”

Section: Resultsmentioning

confidence: 99%

A Methodology for Search Space Reduction in QoS Aware Semantic Web Service Composition

Chattopadhyay¹,

Banerjee²

2018

Preprint

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The semantic information regulates the expressiveness of a web service. State-of-the-art approaches in web services research have used the semantics of a web service for different purposes, mainly for service discovery, composition, execution etc. In this paper, our main focus is on semantic driven Quality of Service (QoS) aware service composition. Most of the contemporary approaches on service composition have used the semantic information to combine the services appropriately to generate the composition solution. However, in this paper, our intention is to use the semantic information to expedite the service composition algorithm. Here, we present a service composition framework that uses semantic information of a web service to generate different clusters, where the services are semantically related within a cluster. Our final aim is to construct a composition solution using these clusters that can efficiently scale to large service spaces, while ensuring solution quality. Experimental results show the efficiency of our proposed method.

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Section: Resultsmentioning

confidence: 99%

A Methodology for Search Space Reduction in QoS Aware Semantic Web Service Composition

Chattopadhyay¹,

Banerjee²

2018

Preprint

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“…Several research works have been carried out on trust and reputation using various mechanisms, such as incentive-based, association-based, previous invocation-based etc. A distribution free non-parametric statistical method is proposed to estimate the PDF for QoS for web service discovery (Zheng et al, 2010b). A QoS distribution estimation tool (QoSDIST) is developed to estimate the QoS distributions for service compositions (Zheng et al, 2010a).…”

Section: Related Workmentioning

confidence: 99%

“…Some of the QoS parameters, such as response time dynamically changes; thereby, describing QoS of web services accurately becomes complicated. The estimated QoS for the service composition can be misleading, if the QoS distributions of component web services are not accurately modelled (Zheng et al, 2010b).…”

Section: Introductionmentioning

confidence: 99%

A mixed opinion-based reputation prediction approach for reliable web service discovery

Rathore

Suman

2016

IJBIS

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Prediction of service reputation is an important research issue to include reliable services in service discovery and composition. A user of the service plays an important role in the prediction of service reputation. Therefore, feedback ratings provided by service users cannot be completely avoided. Most of the existing approaches fully trust on service users' feedback rating for reputation prediction, which often leads to bias towards positive or negative ratings. In this paper, a mixed opinion-based reputation prediction approach is proposed, which uses theoretical t-probability distribution and propositional logic to assess and predict the service reputation. The proposed approach combines users' feedback ratings and run time access rate to minimise the probable bias towards feedback ratings provided by users. Experimental result shows that proposed approach provides effective solution for prediction of service reputation, which can be helpful in performing reliable service discovery and composition.Reference to this paper should be made as follows: Rathore, M. and Suman, U. (2016) 'A mixed opinion-based reputation prediction approach for reliable web service discovery', Int.

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An influence diagram based cloud service selection approach in dynamic cloud marketplaces

Sun

2017

Cluster Comput

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QoSDIST: A QoS Probability Distribution Estimation Tool for Web Service Compositions

Cited by 9 publications

References 12 publications

A Methodology for Search Space Reduction in QoS Aware Semantic Web Service Composition

A Methodology for Search Space Reduction in QoS Aware Semantic Web Service Composition

A mixed opinion-based reputation prediction approach for reliable web service discovery

An influence diagram based cloud service selection approach in dynamic cloud marketplaces

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