{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,5,30]],"date-time":"2023-05-30T04:15:43Z","timestamp":1685420143168},"reference-count":0,"publisher":"National Library of Serbia","issue":"3","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ComSIS","COMPUT SCI INF SYST","COMPUT SCI INFORM SY","COMPUTER SCI INFORM","COMSIS J"],"published-print":{"date-parts":[[2021]]},"abstract":"<jats:p>The diagnosis of intermittent faults is challenging because of their random manifestation due to intricate mechanisms. Conventional diagnosis methods are no longer effective for these faults, especially for hierachical environment, such as cloud computing. This paper proposes a fault diagnosis method that can effectively identify and locate intermittent faults originating from (but not limited to) processors in the cloud computing environment. The method is end-to-end in that it does not rely on artificial feature extraction for applied scenarios, making it more generalizable than conventional neural network-based methods. It can be implemented with no additional fault detection mechanisms, and is realized by software with almost zero hardware cost. The proposed method shows a higher fault diagnosis accuracy than BP network, reaching 97.98% with low latency.<\/jats:p>","DOI":"10.2298\/csis200620040w","type":"journal-article","created":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T08:18:59Z","timestamp":1605601139000},"page":"771-790","source":"Crossref","is-referenced-by-count":0,"title":["End-to-end diagnosis of cloud systems against intermittent faults"],"prefix":"10.2298","volume":"18","author":[{"given":"Chao","family":"Wang","sequence":"first","affiliation":[{"name":"Computer School, Beijing Information Science and Technology University, Beijing, China + Beijing Advanced Innovation Center for Materials Genome Engineering, Beijing, China"}]},{"given":"Zhongchuan","family":"Fu","sequence":"additional","affiliation":[{"name":"Computer Science & Technology Department, Harbin Institute of Technology, Heilongjiang, China"}]},{"given":"Yanyan","family":"Huo","sequence":"additional","affiliation":[{"name":"Computer School, Beijing Information Science and Technology University, Beijing, China"}]}],"member":"1078","container-title":["Computer Science and Information Systems"],"original-title":[],"language":"en","deposited":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T08:05:21Z","timestamp":1685347521000},"score":1,"resource":{"primary":{"URL":"https:\/\/doiserbia.nb.rs\/Article.aspx?ID=1820-02142000040W"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021]]}},"URL":"https:\/\/doi.org\/10.2298\/csis200620040w","relation":{},"ISSN":["1820-0214","2406-1018"],"issn-type":[{"value":"1820-0214","type":"print"},{"value":"2406-1018","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}