dc.contributor.author | Prasanga, RKM | |
dc.contributor.author | Wijesiriwardana, C | |
dc.contributor.author | Weerasuriya, GT | |
dc.contributor.author | Fernando, S | |
dc.date.accessioned | 2017-03-11T10:09:27Z | |
dc.date.available | 2017-03-11T10:09:27Z | |
dc.identifier.uri | http://dl.lib.mrt.ac.lk/handle/123/12502 | |
dc.description.abstract | Over the last few decades, service oriented architectures, in particularly web services, have grown in popularity in the context of enterprise level application integration. As a result, most of the enterprise level software systems tended to be developed with a flavor of web service components. However, like all other distributed software technologies, web services also fail. Therefore, proper mechanisms and tools to handle system failures are vital to avoid such exceptional behaviors. To address that problem, this paper investigates a state prediction mechanism for web services using Hidden Markov Model (HMM). This approach is capable of predicting the future exceptional behaviors of the web service by analyzing and identifying the error patterns generated by long-running web services. This research can be further extended with an automated system input to determine the system state. | en_US |
dc.language.iso | en | en_US |
dc.subject | Failures | en_US |
dc.subject | Filtering | |
dc.subject | Hidden Markov Models | |
dc.subject | Log files | |
dc.subject | Prediction | |
dc.subject | Probability. | |
dc.subject | ||
dc.title | States Prediction of Web Services Using Hidden Markov Model | en_US |
dc.type | Conference-Full-text | en_US |
dc.identifier.faculty | IT | en_US |
dc.identifier.department | Department of Information Technology | en_US |
dc.identifier.year | 2015 | en_US |
dc.identifier.conference | ITRU RESEARCH SYMPOSIUM | en_US |
dc.identifier.place | UNIVERSITY OF MORATUWA | en_US |
dc.identifier.pgnos | 16-20 | en_US |
dc.identifier.email | malithrana@gmail.com | en_US |
dc.identifier.email | chaman@uom.lk | en_US |
dc.identifier.email | thiliniw@uom.lk | en_US |
dc.identifier.email | subhaf@uom.lk | en_US |