【專題演講】Search Based Approach to Forecasting QoS Attributes of Web Services using Genetic Programming
Search Based Approach to Forecasting QoS Attributes of Web Services using Genetic Programming
Currently, many service operations performed in service-oriented software engineering (SOSE), such as service composition and discovery, depend heavily on Quality of Service (QoS). Due to factors such as varying loads, the real value of some dynamic QoS attributes (e.g., response time and availability) changes over time. To predict dynamic QoS values, the objective is to devise an approach that can generate a predictor to perform QoS forecasting based on past QoS observations. We use a kind of search-based software engineering (SBSE) method called genetic programming (GP) to Forecasting QoS attributes of web services. In our proposed approach, GP is used to search and evolve expression-based, one-step-ahead QoS predictors. To evaluate the performance (accuracy) of our GP-based approach, we also implement most current time series forecasting methods; a comparison between our approach and these other methods is discussed in the context of real-world QoS data.
Yong-Yi Fanjiang received his MS and PhD degree in Computer Science and Information Engineering from National Chiao Tung University, Taiwan, in 1998 and from National Central University, Taiwan, in 2004, respectively. Currently, he is an associate professor of the Department of Computer Science and Information Engineering and the chair of the Bachelor's Program in Software Engineering and Digital Innovation Applications, Fu Jen Catholic University, Taiwan, from 2007 and 2012, respectively. His research interests include mobile and pervasive computing, software engineering, semantic web, and human computer interaction.