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Efficient Web Service Selection Using KBAnalytics


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1 Sathyabama University, Chennai, India
     

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Web service selection has become a challenge and onerous task as numerous web services are available in the internet for a given functionality. Simultaneous availability of all required web services is of paramount importance for automatic web service composition. Furthermore, if the selected web service is not available in the internet, the entire web service selection activities tend to be futile. To alleviate the aforementioned difficulties, knowledge based web service selection approach has been introduced. In this approach, the Quality of Service (QoS) attributes such as response time, throughput, availability, reliability and cost are normalized and the rank value will be stored in the QoS Database (QoSDB). For a client request, the QoS manager filters the pertinent candidate services from QOSDB based on the threshold value for response time and throughput. The Knowledge Base Analytics (KBAnalytics) simultaneously verifies the list of matched web services tenability and existence in the internet. By getting the feedback from the KBAnalytics, the QoS manager removes the non available services from the list and final services will be provided to the client for setting the weights over QoS attributes. The highest ranked service will be provided to the client for invocation process. QoS Manager acts as an agent between client and service provider.

Keywords

QoSManager, KBAnalytics, Availability, Knowledgebase.
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  • Efficient Web Service Selection Using KBAnalytics

Abstract Views: 276  |  PDF Views: 2

Authors

R. Jeberson Retna Raj
Sathyabama University, Chennai, India
T. Sasipraba
Sathyabama University, Chennai, India

Abstract


Web service selection has become a challenge and onerous task as numerous web services are available in the internet for a given functionality. Simultaneous availability of all required web services is of paramount importance for automatic web service composition. Furthermore, if the selected web service is not available in the internet, the entire web service selection activities tend to be futile. To alleviate the aforementioned difficulties, knowledge based web service selection approach has been introduced. In this approach, the Quality of Service (QoS) attributes such as response time, throughput, availability, reliability and cost are normalized and the rank value will be stored in the QoS Database (QoSDB). For a client request, the QoS manager filters the pertinent candidate services from QOSDB based on the threshold value for response time and throughput. The Knowledge Base Analytics (KBAnalytics) simultaneously verifies the list of matched web services tenability and existence in the internet. By getting the feedback from the KBAnalytics, the QoS manager removes the non available services from the list and final services will be provided to the client for setting the weights over QoS attributes. The highest ranked service will be provided to the client for invocation process. QoS Manager acts as an agent between client and service provider.

Keywords


QoSManager, KBAnalytics, Availability, Knowledgebase.