On Web Service Composition with QoS Constraint

2011 ◽  
Vol 268-270 ◽  
pp. 1838-1843 ◽  
Author(s):  
Wen Tao Liu
Keyword(s):  
Genetic Algorithm ◽  
Web Service ◽  
Service Composition ◽  
Large Scale ◽  
Optimal Path ◽  
Web Service Composition ◽  
Large Scale Problems ◽  
Optimal Service ◽  
Construct System ◽  
The Web

The software architecture based on web service has become the critical technique to construct system in the distributed environments. The web service composition is the most important method to find the correct service in the complicated application circumstance. The key question is to find service based on the QoS and how to guarantee the quality. This thesis focuses the web service composition in order to get dynamic business cooperation and integration. The key component of web service is discussed and the method of web service composition is analyzed including the formalization verification and service composition architecture and the QoS-aware composition methods. Aimed at the application of web service composition, a method based on approved genetic algorithm is put forward. The simple genetic algorithm based web service composition has many problems such as slow convergence rate and non-optimal service composition. In this paper a genetic algorithm based on niche is provided for the Qos-aware composition and it can get more accurate service composition result and can get the optimal path quickly especially in the large scale problems according to the experiment.

scholarly journals Experimental Analysis for Semantic based Large Scale Service Composition using Deep Learning

2019 ◽  
Vol 8 (10) ◽  
pp. 4280-4283
Keyword(s):  
Deep Learning ◽  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Web Application ◽  
Large Scale ◽  
Learning Algorithm ◽  
Computational Cost ◽  
Web Service Composition ◽  
User Requirement

In Service Oriented Architecture (SOA) web services plays important role. Web services are web application components that can be published, found, and used on the Web. Also machine-to-machine communication over a network can be achieved through web services. Cloud computing and distributed computing brings lot of web services into WWW. Web service composition is the process of combing two or more web services to together to satisfy the user requirements. Tremendous increase in the number of services and the complexity in user requirement specification make web service composition as challenging task. The automated service composition is a technique in which Web Service Composition can be done automatically with minimal or no human intervention. In this paper we propose a approach of web service composition methods for large scale environment by considering the QoS Parameters. We have used stacked autoencoders to learn features of web services. Recurrent Neural Network (RNN) leverages uses the learned features to predict the new composition. Experiment results show the efficiency and scalability. Use of deep learning algorithm in web service composition, leads to high success rate and less computational cost.

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