{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:31:03Z","timestamp":1760239863316,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T00:00:00Z","timestamp":1546992000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Henan Foundation and Frontier Research Project","award":["152300410212"],"award-info":[{"award-number":["152300410212"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>With the development and popularization of cloud storage technology, cloud storage has become a main method of data storage. Aiming at the problem of large delay and low availability incurred by multiple invalid nodes in cloud storage, a new type of concurrent nodes repair scheme called Distributed-Cross Repair Solution (DCRS) is proposed. In this scheme, system repair operation is performed in replacement nodes, and all of the replacement nodes cooperatively and crossly repair data to ensure that the data blocks that are required for repairing are only transmitted once within the system. This will solve the system repair bottleneck in the traditional repair scheme and resolve the problem of large internal network throughput and other problems, which can effectively reduce the repair delay of the system. At the same time, the repair trigger mechanism is adopted in order to avoid the repair failure problem caused by the coming of additional damaged nodes during the system reparation, which increases the system\u2019s reliability. The simulation results show that the DCRS has obvious effects in reducing system repair delay and increasing system availability.<\/jats:p>","DOI":"10.3390\/info10010020","type":"journal-article","created":{"date-parts":[[2019,1,10]],"date-time":"2019-01-10T03:22:31Z","timestamp":1547090551000},"page":"20","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generalized RDP Code Based Concurrent Repair Scheme in Cloud Storage Nodes"],"prefix":"10.3390","volume":"10","author":[{"given":"Guojun","family":"Xie","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiquan","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9632-2543","authenticated-orcid":false,"given":"Huanhuan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,9]]},"reference":[{"key":"ref_1","first-page":"865","article-title":"Traffic Flow Prediction with Big Data: A Deep Learning Approach","volume":"16","author":"Lv","year":"2015","journal-title":"IEEE Trans. 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