{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:04:02Z","timestamp":1760231042570,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,20]],"date-time":"2022-08-20T00:00:00Z","timestamp":1660953600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shaanxi Province of China","award":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"],"award-info":[{"award-number":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"]}]},{"name":"Shaanxi Provincial Education Department","award":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"],"award-info":[{"award-number":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"]}]},{"name":"Xi\u2019an University of Posts and Telecommunications Key Innovation Fund","award":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"],"award-info":[{"award-number":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"]}]},{"name":"Construction of Key Disciplines in Universities in Shaanxi","award":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"],"award-info":[{"award-number":["2019ZDLGY07-08","2020JM-582","2021JQ-719","21JP115","CXJJZL2021013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the rise of mobile edge computing (MEC), mobile services with the same or similar functions are gradually increasing. Usually, Quality of Service (QoS) has become an indicator to measure high-quality services. In the real MEC service invocation environment, due to time and network instability factors, users\u2019 QoS data feedback results are limited. Therefore, effectively predicting the Qos value to provide users with high-quality services has become a key issue. In this paper, we propose a truncated nuclear norm Low-rank Tensor Completion method for the QoS data prediction. This method represents complex multivariate QoS data by constructing tensors. Furthermore, the truncated nuclear norm is introduced in the QoS data tensor completion in order to mine the correlation between QoS data and improve the prediction accuracy. At the same time, the general rate parameter is introduced to control the truncation degree of tensor mode. Finally, the prediction approximate tensor is obtained by the Alternating Direction Multiplier Method iterative optimization algorithm. Numerical experiments are conducted based on the public QoS dataset WS-Dream. The results indicate that our QoS prediction method has better prediction accuracy than other methods under different missing density QoS data.<\/jats:p>","DOI":"10.3390\/s22166266","type":"journal-article","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T01:56:40Z","timestamp":1661133400000},"page":"6266","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A QoS Prediction Approach Based on Truncated Nuclear Norm Low-Rank Tensor Completion"],"prefix":"10.3390","volume":"22","author":[{"given":"Hong","family":"Xia","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"},{"name":"Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi\u2019an 710121, China"},{"name":"Xi\u2019an Key Laboratory of Big Data and Intelligent Computing, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyi","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahao","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanping","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"},{"name":"Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi\u2019an 710121, China"},{"name":"Xi\u2019an Key Laboratory of Big Data and Intelligent Computing, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"},{"name":"Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi\u2019an 710121, China"},{"name":"Xi\u2019an Key Laboratory of Big Data and Intelligent Computing, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongmin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"},{"name":"Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi\u2019an 710121, China"},{"name":"Xi\u2019an Key Laboratory of Big Data and Intelligent Computing, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,20]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"IoT middleware: A survey on issues and enabling technologies","volume":"4","author":"Ngu","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_2","first-page":"29","article-title":"Mobile edge computing: Recent efforts and five key research directions","volume":"12","author":"Tran","year":"2017","journal-title":"IEEE Comsocmmtc Commun."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ren, T.F., Zhou, M.T., Yv, C.B., Shen, F., Li, J., and He, W. 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