{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T16:32:08Z","timestamp":1743093128008,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030977733"},{"type":"electronic","value":"9783030977740"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-97774-0_18","type":"book-chapter","created":{"date-parts":[[2022,3,14]],"date-time":"2022-03-14T08:06:40Z","timestamp":1647245200000},"page":"198-207","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on Data Fault-Tolerance Method Based on Disk Bad Track Isolation"],"prefix":"10.1007","author":[{"given":"Xu","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Li","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Sujuan","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,3,15]]},"reference":[{"key":"18_CR1","doi-asserted-by":"publisher","unstructured":"Liang, W., Ning, Z., Xie, S., Hu, Yu., Lu, S., Zhang, D.: Secure fusion approach for the internet of things in smart autonomous multi-robot systems. Inf. Sci.1\u201320 (2021). https:\/\/doi.org\/10.1016\/j.ins.2021.08.035","DOI":"10.1016\/j.ins.2021.08.035"},{"key":"18_CR2","doi-asserted-by":"publisher","unstructured":"Liang, W., Zhang, D., Lei, X., Tang, M., Li, K., Zomaya, A.: Circuit copyright blockchain: blockchain-based homomorphic encryption for IP circuit protection. IEEE Trans. Emerg. Top. Comput. 1 (2020). https:\/\/doi.org\/10.1109\/TETC.2020.2993032","DOI":"10.1109\/TETC.2020.2993032"},{"key":"18_CR3","doi-asserted-by":"publisher","unstructured":"Liang, W., Xiao, L., Zhang, K., Tang, M., He, D., Li, K.C.: Data fusion approach for collaborative anomaly intrusion detection in blockchain-based systems. IEEE Internet Things J. 1 (2021). https:\/\/doi.org\/10.1109\/JIOT.2021.3053842","DOI":"10.1109\/JIOT.2021.3053842"},{"key":"18_CR4","doi-asserted-by":"publisher","unstructured":"Liang, W., et al.: Deep neural network security collaborative filtering scheme for service recommendation in intelligent cyber-physical systems. IEEE Internet Things J. (2021). https:\/\/doi.org\/10.1109\/JIOT.2021.3086845","DOI":"10.1109\/JIOT.2021.3086845"},{"issue":"3","key":"18_CR5","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1109\/TR.2002.802886","volume":"51","author":"GF Hughes","year":"2002","unstructured":"Hughes, G.F., Murray, J.F., Kreutz-Delgado, K., et al.: Improved disk-drive failure warnings. IEEE Trans. Reliab. 51(3), 350\u2013357 (2002)","journal-title":"IEEE Trans. Reliab."},{"issue":"03","key":"18_CR6","first-page":"341","volume":"11","author":"J Li","year":"2017","unstructured":"Li, J., Wang, G., Liu, X., Li, Z.: Overview of storage system reliability prediction. J. Front. Comput. Sci. Technol. 11(03), 341\u2013354 (2017)","journal-title":"J. Front. Comput. Sci. Technol."},{"key":"18_CR7","unstructured":"Xu, C.: Research and design of disaster data recovery system. Chongqing University of technology (2010)"},{"key":"18_CR8","doi-asserted-by":"crossref","unstructured":"Xie, Y., Dan, F., Fang, W., et al.: OME: an optimized modeling engine for disk failure prediction in heterogeneous datacentre. In: 2018 IEEE 36th International Conference on Computer Design (ICCD). IEEE Computer Society (2018)","DOI":"10.1109\/ICCD.2018.00089"},{"key":"18_CR9","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1007\/978-3-642-14400-4_30","volume-title":"Advances in Data Mining. Applications and Theoretical Aspects","author":"Y Zhao","year":"2010","unstructured":"Zhao, Y., Liu, X., Gan, S., Zheng, W.: Predicting disk failures with HMM- and HSMM-based approaches. In: Perner, P. (ed.) ICDM 2010. LNCS (LNAI), vol. 6171, pp. 390\u2013404. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-14400-4_30"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Zhu, B., Gang, W., Liu, X., et al.: Proactive drive failure prediction for large scale storage systems. In: Mass Storage Systems & Technologies. IEEE (2013)","DOI":"10.1109\/MSST.2013.6558427"},{"key":"18_CR11","doi-asserted-by":"crossref","unstructured":"Xiao, J., Xiong, Z., Wu, S., et al.: Disk failure prediction in data centers via online learning, pp. 1\u201310 (2018)","DOI":"10.1145\/3225058.3225106"},{"issue":"03","key":"18_CR12","first-page":"341","volume":"11","author":"J Li","year":"2017","unstructured":"Li, J., Wang, G., Liu, X., Li, Z.: Review of reliability prediction for storage system. J. Front. Comput. Sci. Technol. 11(03), 341\u2013354 (2017)","journal-title":"J. Front. Comput. Sci. Technol."},{"issue":"S2","key":"18_CR13","first-page":"54","volume":"52","author":"Y Jia","year":"2015","unstructured":"Jia, Y., Li, J., Jia, R., et al.: Hard disk failure prediction model validation in large data center environment. J. Comput. Res. Dev. 52(S2), 54\u201361 (2015)","journal-title":"J. Comput. Res. Dev."},{"issue":"02","key":"18_CR14","first-page":"118","volume":"47","author":"S Jiang","year":"2020","unstructured":"Jiang, S., Du, C., Chen, H., Li, J., Wu, J.: An unsupervised adversarial learning method for hard disk fault prediction. J. Xidian Univ. 47(02), 118\u2013125 (2020)","journal-title":"J. Xidian Univ."},{"key":"18_CR15","doi-asserted-by":"publisher","unstructured":"Tan, Y., Gu, X.: On predictability of system anomalies in real world. In: 2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, pp. 133\u2013140 (2010). https:\/\/doi.org\/10.1109\/MASCOTS.2010.22","DOI":"10.1109\/MASCOTS.2010.22"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"Patterson, D.A., Gibson, G.A., Katz, R.H.: A case for redundant arrays of inexpensive disks (RAID). In: Proceedings of the International Conference on Management of Data (SIGMOD), 109\u2013116. ACM, New York (1988)","DOI":"10.1145\/971701.50214"},{"key":"18_CR17","unstructured":"Hamerly, G., Elkan, C.: Bayesian approaches to failure prediction for disk drives (2003)"},{"key":"18_CR18","doi-asserted-by":"crossref","unstructured":"Agarwal, V., Bhattacharyya, C., Niranjan, T., et al.: Discovering rules from disk events for predicting hard drive failures. In: International Conference on Machine Learning & Applications. IEEE Computer Society (2009)","DOI":"10.1109\/ICMLA.2009.62"},{"key":"18_CR19","unstructured":"Xiotech: ISE-The new foundation of data storage, 08 May 2008. http:\/\/www.xiotech.com\/ise-technoloty.php"},{"issue":"2","key":"18_CR20","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s11265-009-0362-3","volume":"58","author":"Z Lei","year":"2010","unstructured":"Lei, Z., Qiu, M., Tseng, W.C., et al.: Variable partitioning and scheduling for MPSoC with virtually shared scratch pad memory. J. Signal Process. Syst. 58(2), 247\u2013265 (2010)","journal-title":"J. Signal Process. Syst."},{"key":"18_CR21","doi-asserted-by":"crossref","unstructured":"Guo, Y., Zhuge, Q., Hu, J., et al.: Optimal data allocation for scratch-pad memory on embedded multi-core systems. In: International Conference on Parallel Processing. IEEE (2011)","DOI":"10.1109\/ICPP.2011.79"},{"key":"18_CR22","doi-asserted-by":"crossref","unstructured":"Vishwanath, K.V., Nagappan, N.: Characterizing cloud computing hardware reliability. In: Proceedings of the 1st ACM symposium on Cloud computing (SoCC 2010), pp. 193\u2013204. Association for Computing Machinery, New York (2010)","DOI":"10.1145\/1807128.1807161"},{"issue":"02","key":"18_CR23","first-page":"306","volume":"57","author":"H Yang","year":"2020","unstructured":"Yang, H., Yang, Y., Tu, Y., Sun, G., Wu, Z.: Proactive fault tolerance based on \u201ccollection\u2014prediction\u2014migration\u2014feedback\u201d mechanism. J. Comput. Res. Dev. 57(02), 306\u2013317 (2020)","journal-title":"J. Comput. Res. Dev."},{"issue":"S1","key":"18_CR24","first-page":"148","volume":"51","author":"R Jia","year":"2014","unstructured":"Jia, R., Li, J., Wang, G., Li, Z., Liu, X.: Optimization and choice of hard disk fault prediction model based on AdaBoost and genetic algorithm. J. Comput. Res. Dev. 51(S1), 148\u2013154 (2014)","journal-title":"J. Comput. Res. Dev."},{"issue":"S1","key":"18_CR25","first-page":"7","volume":"48","author":"W Hu","year":"2011","unstructured":"Hu, W., Liu, G., Li, Q., Liu, X.: Research on intelligent failure prediction based self-healing storage system. J. Comput. Res. Dev. 48(S1), 7\u201311 (2011)","journal-title":"J. Comput. Res. Dev."},{"issue":"4","key":"18_CR26","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1109\/LES.2014.2344913","volume":"6","author":"M Qiu","year":"2014","unstructured":"Qiu, M., Chen, Z., Liu, M.: Low-power low-latency data allocation for hybrid scratch-pad memory. IEEE Embed. Syst. Lett. 6(4), 69\u201372 (2014)","journal-title":"IEEE Embed. Syst. Lett."},{"key":"18_CR27","unstructured":"Murray, J.F., Hughers, G., Kreutz-Delgado, K.: Hard drive failure prediction using non-parametric statistical methods. In: Procof the ICANN\/ICONIP, p. 1 (2003)"},{"key":"18_CR28","unstructured":"Murray, J.F., Hughes, G.F., et al.: Machine learning methods for predicting failures in hard drives: a multiple-instance application. J. Mach. Learn. Res. (2005)"}],"container-title":["Lecture Notes in Computer Science","Smart Computing and Communication"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-97774-0_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,14]],"date-time":"2022-03-14T08:10:38Z","timestamp":1647245438000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-97774-0_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030977733","9783030977740"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-97774-0_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"15 March 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SmartCom","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Smart Computing and Communication","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"New York, NY","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"smartc2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.cloud-conf.net\/smartcom\/2021\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"165","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"44","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"27% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"10","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference was held online due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}