QoS Time Series Modeling and Forecasting for Web Services: A Comprehensive Survey
Yang Syu, Chien‐Min Wang
Abstract
In research, time series-based (time-aware) QoS modeling and forecasting for Web services (WSs) has been studied for over a decade, and a large number of research papers have been published; however, this current research lacks a systematic and comprehensive survey. Thus, in this article, an insightful and detailed review and investigation of current WS QoS time series modeling and forecasting research is provided. Based on our investigation of the collected literature, we identify and divide the entire research subject into four essential research concerns (components): the addressed problem, the proposed or employed approach, the considered performance measure, and the adopted QoS time series dataset. This article reviews, classifies, and discusses current studies in terms of the four identified research concerns. Moreover, for each research concern, a set of criteria and classification are proposed for its detailed categorization and comparison. Finally, this survey also discusses the insufficiency of current studies in each research concern and the potential future directions of this research area. Overall, this article can be an informative guide for researchers to understand the concerns that they should address when studying this research subject and to clearly comprehend what has been done in current research for each identified research concern.