Abstract
The problem of time-aware (time series-based) dynamic quality of service (QoS) forecasting has attracted increased attention over the past decade. Developed forecasting approaches have been used to obtain the future values of dynamic QoS attributes for the support of the proactive decisions of various QoS-based applications (e.g., QoS-aware service selection and composition). Thus far, however, a comprehensive investigation and overview of the current research on this topic has yet to be produced. This paper proposes and introduces six assessment criteria which are then applied to the existing literature to produce a comprehensive comparison. Based on this analysis, we describe potential future challenges and research directions in this research area, focusing on gaps in the current literature. This survey provides a clear understanding of the current status of this research area with this paper; additionally, we also technically point out what have to be done by the researchers in this area for the advance of this research topic.
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Acknowledgement
This research is partially sponsored by the Ministry of Science and Technology (Taiwan) under the Grant MOST106-2811-E-001-003 and MOST106-2221-E-001-007-MY2.
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Syu, Y., Wang, CM., Fanjiang, YY. (2018). A Survey of Time-Aware Dynamic QoS Forecasting Research, Its Future Challenges and Research Directions. In: Ferreira, J., Spanoudakis, G., Ma, Y., Zhang, LJ. (eds) Services Computing – SCC 2018. SCC 2018. Lecture Notes in Computer Science(), vol 10969. Springer, Cham. https://doi.org/10.1007/978-3-319-94376-3_3
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