Abstract
Time-aware (time series-based) Web service QoS modeling and forecasting have been investigated and addressed for over a decade and a large number of studies and approaches have been produced. However, these existing efforts lack a comprehensive and detailed review that profoundly and systematically organizes, analyzes, and discusses this body of work. Thus, to fill this gap, the authors offered the paper QoS Time Series Modeling and Forecasting for Web Services: A Comprehensive Survey, in which four essential research concerns of this area, namely, problems, approaches, performance measures, and QoS datasets, have been recognized and reviewed in detail. However, aside from these essential research concerns, we also identified two optional research concerns from the current studies, namely, the subsequent applications and experimental configurations. Due to space restrictions, these two optional research concerns were only briefly mentioned in the above survey article, and thus, in this supplementary paper, the authors thoroughly present and review these two optional research concerns.
The primary purpose of performing QoS time series modeling and forecasting is to obtain accurate future QoS estimations for subsequent usage (application), such as QoS-aware service composition and proactive service replacement for SLA/QoS management. Therefore, in the section addressing the first optional research concern, the application of each surveyed study is identified first, and then these current applications are introduced in detail. However, to comprehensively and rigorously observe and evaluate the performance of a proposed or employed approach under different conditions, a set of configuration settings must be varied to run experimentation. Thus, in the second part of this paper, we first define and discuss the identified experimental configuration parameters in this research area and then list the parameters and settings that have been considered in each surveyed study.
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This research is partially sponsored by the Ministry of Science and Technology (Taiwan) under the Grant MOST 108-2221-E-001-007-MY2.
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Syu, Y., Wang, CM. (2020). QoS Time Series Modeling and Forecasting for Web Services: A Comprehensive Survey of Subsequent Applications and Experimental Configurations. In: Wang, Q., Xia, Y., Seshadri, S., Zhang, LJ. (eds) Services Computing – SCC 2020. SCC 2020. Lecture Notes in Computer Science(), vol 12409. Springer, Cham. https://doi.org/10.1007/978-3-030-59592-0_1
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