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A Truncated SVD-Based ARIMA Model for Multiple QoS Prediction in Mobile Edge Computing

College of Economic and Management, Shandong University of Science and Technology, Qingdao 266590, China
Weifang Key Laboratory of Blockchain on Agricultural Vegetables, Weifang University of Science and Technology, Weifang 262700, China
School of Computer Science, Qufu Normal University, Rizhao 276826, China
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Abstract

In the mobile edge computing environments, Quality of Service (QoS) prediction plays a crucial role in web service recommendation. Because of distinct features of mobile edge computing, i.e., the mobility of users and incomplete historical QoS data, traditional QoS prediction approaches may obtain less accurate results in the mobile edge computing environments. In this paper, we treat the historical QoS values at different time slots as a temporal sequence of QoS matrices. By incorporating the compressed matrices extracted from QoS matrices through truncated Singular Value Decomposition (SVD) with the classical ARIMA model, we extend the ARIMA model to predict multiple QoS values simultaneously and efficiently. Experimental results show that our proposed approach outperforms the other state-of-the-art approaches in accuracy and efficiency.

Keywords

edge computingQoS predictionAutoRegressive Integrated Moving Average (ARIMA)truncated Singular Value Decomposition (SVD)

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Tsinghua Science and Technology
Volume 27 Issue 2,
April 2022
Pages 315-324
DOI: 10.26599/TST.2021.9010040
Cite this article:
Yan C, Zhang Y, Zhong W, et al. A Truncated SVD-Based ARIMA Model for Multiple QoS Prediction in Mobile Edge Computing. Tsinghua Science and Technology, 2022, 27(2): 315-324. https://doi.org/10.26599/TST.2021.9010040
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