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.

Chao Yan;Yankun Zhang;Weiyi Zhong;Can Zhang;Baogui Xin

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

清华大学学报自然科学版（英文版）

[1]Chao Yan;Yankun Zhang;Weiyi Zhong;Can Zhang;Baogui Xin-.A Truncated SVD-Based ARIMA Model for Multiple QoS Prediction in Mobile Edge Computing)[J].清华大学学报自然科学版（英文版）,2022(02):315-324

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