A Verified Application of Genetic Programming: QoS Time Series Modeling and Forecasting for Web Services

Created by W.Langdon from gp-bibliography.bib Revision:1.7810

@InProceedings{syu:2022:GECCOhop,

• author = "Yang Syu and Chien-Min Wang and Yong-Yi Fanjiang",
• title = "A Verified Application of Genetic Programming: {QoS} Time Series Modeling and Forecasting for Web Services",
• booktitle = "Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion",
• year = "2022",
• editor = "Marcus Gallagher",
• pages = "43--44",
• address = "Boston, USA",
• series = "GECCO '22",
• month = "9-13 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, machine learning, time series forecasting, service-oriented software engineering, web services",
• isbn13 = "978-1-4503-9268-6/22/07",
• DOI = "doi:10.1145/3520304.3534066",
• abstract = "In both academia and industry, Web services (WSs) technology (also called Web APIs in recent years) has been a fervid research target for years. In industry, software developers now often develop their application systems with diverse WSs on the internet (i.e., these developers often use service-oriented software engineering, SOSE). However, many companies and organizations, including most tech giants, such as Google, Meta, and Amazon, expose their services and business functionalities in the form of RESTful WSs (Web APIs) for external access (e.g., Amazon Web Services). As a focus of research in services computing, many topics and subjects regarding WSs have been identified, investigated, and addressed. A practical research issue that receives broad attention is the understanding (modeling) and prediction of the time-aware (time-varying) dynamic quality of service (QoS) of WSs.Based on a comprehensive survey and investigation presented in [1]: Y. Syu and C. M. Wang, {"}QoS Time Series Modeling and Forecasting for Web Services: A Comprehensive Survey{"}, IEEE Transactions on Network and Service Management (TNSM), Vol. 18, P.P. 926--944, 2021, this abstract paper concisely reports to the GECCO community a justified application of genetic programming (GP) on the modeling and forecasting of WS QoS time series. By introducing this employment of GP and the targeted research problem to the community, the purpose is to encourage and attract people in this field to further revise and improve GP to obtain a better solution to the problem or to try to use other evolutionary techniques to better address the problem.",
• notes = "GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Yang Syu Chien-Min Wang Yong-Yi FanJiang

Citations