2015Unpublished venueRequires access

Optimization to Quality-of-service-driven web service composition using modified genetic algorithm

Indresh Kumar Gupta, Jeetendra Kumar, Pradeep Rai

Open publisher page 16 citations

Abstract

In the web service management Quality of service (QoS) has become an important issue due to the vast number of services that provide the same functionality but with different features. Selecting QoS based services for web services is considered to be global optimization problem. There are several non-functional factors that integrated into Quality of service in web services such as execution cost, execution time, availability, successful execution rate and security. There is a huge demand from the clients for the multiple functionalities in services. Therefore, optimization in the selection of web services from among numerous plans that satisfies client requirements has become a top priority. In this paper, the improved Genetic Algorithm (iGA) is used for QoS-based web service composition. The experiments show that the algorithm is a feasible and efficient method for Web services selection. The dataset of web services used in this study is available at http://bit.ly/WSSelection.

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What this paper is about

In the web service management Quality of service (QoS) has become an important issue due to the vast number of services that provide the same functionality but with different features. Selecting QoS based services for web services is considered to be global optimization problem. There are several non-functional factors that integrated into Quality of service in web services such as execution cost, execution time, availability, successful execution rate and security. There is a huge demand from the clients for the multiple functionalities in services. Therefore, optimization in the selection of web services from among numerous plans that satisfies client requirements has become a top priority. In this paper, the improved Genetic Algorithm (iGA) is used for QoS-based web service composition. The experiments show that the algorithm is a feasible and efficient method for Web services selection. The dataset of web services used in this study is available at http://bit.ly/WSSelection.

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OpenAlex reports 16 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In the web service management Quality of service (QoS) has become an important issue due to the vast number of services that provide the same functionality but with different features. Selecting QoS based services for web services is considered to be global optimization problem. There are several non-functional factors that integrated into Quality of service in web services such as execution cost, execution time, availability, successful execution rate and security. There is a huge demand from the clients for the multiple functionalities in services. Therefore, optimization in the selection of web services from among numerous plans that satisfies client requirements has become a top priority. In this paper, the improved Genetic Algorithm (iGA) is used for QoS-based web service composition. The experiments show that the algorithm is a feasible and efficient method for Web services selection. The dataset of web services used in this study is available at http://bit.ly/WSSelection.

Key concepts: Web service, Computer science, WS-Policy, Quality of service, WS-Addressing, Web application security, Genetic algorithm, Service (business)

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