scholarly journals A User-Centric QoS-Based Web Service Selection Framework

2021 ◽  
Author(s):  
Delnavaz Mobedpour
Keyword(s):  
Query Language ◽  
Focal Point ◽  
Selection Process ◽  
Service Selection ◽  
Mixed Integer ◽  
User Support ◽  
Web Service Selection ◽  
Selection Framework ◽  
Description Languages ◽  
The One

With the proliferation of web services, the selection process, especially the one based on the non-functional properties (e.g. Quality of Service – QoS attributes) has become a more and more important step to help requestors locate a desired service. There have been many research works proposing various QoS description languages and selection models. However, the end user is not generally the focal point of their designs and the user support is either missing or lacking in these systems. The QoS language sometimes is not flexible enough to accommodate users’ various requirements and is too complex so that it puts extra burden on users. In order to solve this problem, in this thesis we design a more expressive and flexible QoS query language (QQL) targeted for non-expert users, together with the user support on formulating queries and understanding services in the registry. An enhanced selection model based on Mixed Integer Programming (MIP) is also proposed to handle the QQL queries. We performed experiments with a real QoS dataset to show the effectiveness of our framework.

scholarly journals A User-Centric QoS-Based Web Service Selection Framework

2021 ◽  
Author(s):  
Delnavaz Mobedpour
Keyword(s):  
Query Language ◽  
Focal Point ◽  
Selection Process ◽  
Service Selection ◽  
Mixed Integer ◽  
User Support ◽  
Web Service Selection ◽  
Selection Framework ◽  
Description Languages ◽  
The One

With the proliferation of web services, the selection process, especially the one based on the non-functional properties (e.g. Quality of Service – QoS attributes) has become a more and more important step to help requestors locate a desired service. There have been many research works proposing various QoS description languages and selection models. However, the end user is not generally the focal point of their designs and the user support is either missing or lacking in these systems. The QoS language sometimes is not flexible enough to accommodate users’ various requirements and is too complex so that it puts extra burden on users. In order to solve this problem, in this thesis we design a more expressive and flexible QoS query language (QQL) targeted for non-expert users, together with the user support on formulating queries and understanding services in the registry. An enhanced selection model based on Mixed Integer Programming (MIP) is also proposed to handle the QQL queries. We performed experiments with a real QoS dataset to show the effectiveness of our framework.

A QoS Aware, Cognitive Parameters Based Model for the Selection of Semantic Web Services

2010 ◽  
pp. 320-335
Author(s):  
Sandeep Kumar ◽  
Kuldeep Kumar
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Web Service ◽  
Selection Process ◽  
Service Selection ◽  
Semantic Web Services ◽  
Semantic Web Service ◽  
Web Service Selection ◽  
The One ◽  
Selection Of

Semantic Web service selection is considered as the one of the most important aspects of semantic web service composition process. The Quality of Service (QoS) and cognitive parameters can be a good basis for this selection process. In this paper, we have presented a hybrid selection model for the selection of Semantic Web services based on their QoS and cognitive parameters. The presented model provides a new approach of measuring the QoS parameters in an accurate way and provides a completely novel and formalized measurement of different cognitive parameters.

A Quality Driven Web Service Selection Model

2012 ◽  
pp. 142-164 ◽  
Author(s):  
Pierluigi Plebani ◽  
Filippo Ramoni
Keyword(s):  
Web Services ◽  
Web Service ◽  
Cost Benefit Analysis ◽  
Selection Process ◽  
Service Selection ◽  
User Preferences ◽  
Analytic Hierarchy ◽  
Web Service Selection ◽  
The One ◽  
The Web

The chapter introduces a quality of Web service model which can be exploited by a Web service broker during the Web service selection phase. The model considers both user and provider standpoints. On the one hand, providers express their capabilities with respect to measurable dimensions (e.g., response time, latency). On the other hand, users can define the requirements with a higher level of abstraction (e.g. performance). Since the quality is subjective by definition, the presented quality model also maps the user preferences, i.e., how much a quality dimension is more important than another one in evaluating the overall quality. The Analytic Hierarchy Approach (AHP) has been adopted as a technique for expressing user preferences. The chapter also describes how the model can be exploited in the Web service selection process. Starting from a set of functionally equivalent Web services, the selection process identifies which are the Web services able to satisfy the user requirements. Moreover, according to a cost-benefit analysis, the list of selected Web services is sorted and, as a consequence, the best Web service is identified.

scholarly journals A customizable web service selection framework using MCDM approaches

2021 ◽  
Author(s):  
Raed Karim
Keyword(s):  
Service Selection ◽  
User Requirements ◽  
Selection System ◽  
Functional Requirements ◽  
Selection Methods ◽  
Weighting Method ◽  
Web Service Selection ◽  
Calculation Process ◽  
Selection Framework ◽  
Selection And Ranking

With the tremendous increase of web services published online, the problem of selecting the best service offers becomes more challenging. Users need to make their decisions on multiple and conflicting non-functional requirements. It is a natural fit to apply the Multi-Criteria Decision Making (MCDM) theory to the service selection and ranking process. In our proposed QoS-based service selection system, we take the user-centric standpoint to design the system. We improve the original MCDM models so that the user requirements on the QoS criteria are included in the rank calculation process. Our proposed QoS weighting method considers the well-defined ANP method combined with the user-defined weights. We compared the improved selection methods and we found that the Constraint Programming method is the best in terms of its sensitivity to the changes made to the QoS weights. Consequently, the results produced from this comparison would be presented to the user.

Research on the Web Service Selection with Constraints Based on QoS

2013 ◽  
Vol 717 ◽  
pp. 726-731
Author(s):  
Sheng Jun Qin ◽  
Wei Li
Keyword(s):  
Web Service ◽  
Software Design ◽  
Service Selection ◽  
Allocation Scheme ◽  
Web Service Selection ◽  
Availability Constraints ◽  
The One ◽  
Qos Performance ◽  
Reliability And Availability ◽  
The Web

The SOA model brings new benefits to software design and architecture by enabling re-use and sharing of services. Due to the uncertain of web service, it is important to make sure that the selected service is always reliable and available. In this work, we propose an allocation scheme that minimizes the response time and cost of the solution subject to reliability and availability constraints in terms of expected value. The algorithm proposed in this paper aims to discover services with high QoS performance, and reduce the execute time at the same time. Finally, we proves the advantage of the new algorithm by comparing the time obtained by our proposed algorithm with the one achieved by other algorithm.

QoS-Based Extensible Selection Framework for Web Service

2012 ◽  
Vol 433-440 ◽  
pp. 1762-1765
Author(s):  
Li Qun Cui ◽  
Cui Cui Li
Keyword(s):  
Web Services ◽  
Web Service ◽  
Functional Properties ◽  
Service Providers ◽  
Rapid Development ◽  
Service Selection ◽  
Functional Requirements ◽  
Web Service Selection ◽  
Selection Framework

With the rapid development of Web services technology, more and more Web services emerged in the network. Service consumer attached importance to the functional properties of services, also more and more emphasis on non-functional properties, namely Quality of Service. The Ultimate goal is meet consumer the demand of QoS. Therefore, service providers paid more and more attention to quality of services to meets the needs of users. This takes into account the options to meet the functional requirements and the QoS requirements, and designed a Web service selection framework. At the same time, QoS attributes can be added or deleted the number, so it is an extendible framework. The results show that the framework could select the appropriate service for users.

scholarly journals QoS-based data analytic service selection: a comparative study of different learning models

2021 ◽  
Author(s):  
Bayan Alghofaily
Keyword(s):  
Learning Algorithm ◽  
Selection Process ◽  
Service Selection ◽  
Machine Learning Algorithms ◽  
Good Prediction ◽  
Web Service Selection ◽  
Good Prediction Accuracy ◽  
The Impact ◽  
The Given ◽  
Data Analytic

QoS-based web service selection has been studied in the service computing community for some time; however, data characteristics are not considered. In this work, we have studied the use of different machine learning algorithms as meta-learners in predicting the performance of data analytic services for the given dataset. We used a meta-learning algorithm to incorporate meta-features in the selection process and we used clustering services as an example of data analytic services. We have also investigated the impact of the number of data features on the performance of the meta-learners. We found that, out of the 5 classification models, SVM showed the best results in predicting the recommended service for the given dataset with an accuracy of 78%. When it comes to regression models, MLP was the best regressor. We recommend considering only simple meta-features that can be collected for most datasets, as those proved to be sufficient to achieve good prediction accuracy.

scholarly journals QoS-based data analytic service selection: a comparative study of different learning models

2021 ◽  
Author(s):  
Bayan Alghofaily
Keyword(s):  
Learning Algorithm ◽  
Selection Process ◽  
Service Selection ◽  
Machine Learning Algorithms ◽  
Good Prediction ◽  
Web Service Selection ◽  
Good Prediction Accuracy ◽  
The Impact ◽  
The Given ◽  
Data Analytic

QoS-based web service selection has been studied in the service computing community for some time; however, data characteristics are not considered. In this work, we have studied the use of different machine learning algorithms as meta-learners in predicting the performance of data analytic services for the given dataset. We used a meta-learning algorithm to incorporate meta-features in the selection process and we used clustering services as an example of data analytic services. We have also investigated the impact of the number of data features on the performance of the meta-learners. We found that, out of the 5 classification models, SVM showed the best results in predicting the recommended service for the given dataset with an accuracy of 78%. When it comes to regression models, MLP was the best regressor. We recommend considering only simple meta-features that can be collected for most datasets, as those proved to be sufficient to achieve good prediction accuracy.

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