Title :
Evaluating Web Service Quality Using Finite State Models
Author :
Kondratyeva, Olga ; Kushik, Natalia ; Cavalli, Ana ; Yevtushenko, Nina
Author_Institution :
Dept. of Software Networks, TELECOM SudParis, Evry, France
Abstract :
This paper addresses the problem of evaluating the Web service quality using Finite State Machines. The most popular metrics for estimating such quality and user perception are Quality of Service (QoS) and Quality of Experience (QoE), which represent objective and subjective assessments, correspondingly. In this paper, we show how QoS can be estimated for Web services and their composition using finite state models. We also discuss how different machine learning algorithms can be applied for evaluating QoE of Web services based on known QoS parameter values.
Keywords :
Web services; finite state machines; learning (artificial intelligence); quality of experience; quality of service; QoE; QoS parameter values; Web service composition; Web service quality; finite state machines; finite state models; machine learning algorithms; objective assessments; quality of experience; quality of service; subjective assessments; user perception; Automata; Availability; Optimization; Probability; Quality of service; Vectors; Web services; QoE; QoS; finite state models; quality of (composite) service; web service;
Conference_Titel :
Quality Software (QSIC), 2013 13th International Conference on
Conference_Location :
Najing
DOI :
10.1109/QSIC.2013.52
