Pablo Morales-Ferreira, Miguel Santiago-Duran, Cristopher Gaytan-Diaz, J. L. González, Víctor Jesús Sosa Sosa, I. Lopez-Arevalo
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This service includes an information dispersal client for coding/decoding files in-memory, which improves the service experience of end-users when delivering/retrieving files to/from cloud storage services. It also includes a data placement method to allocate, locate and manage redundant pieces of heterogeneous size in a uniform manner, which produces load balancing in the storage nodes. A prototype of this service was implemented in a private cloud and containerized cluster. An experimental evaluation based on synthetic traces and a case study based on satellite images revealed that the service prototype preserved a balanced load even in scenarios when managing pieces of heterogeneous size and that, when performing coding/decoding in-memory, the service experience of end-users was improved in comparison with tested traditional solutions.","PeriodicalId":414464,"journal":{"name":"2018 IEEE Symposium on Service-Oriented System Engineering (SOSE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A Data Distribution Service for Cloud and Containerized Storage Based on Information Dispersal\",\"authors\":\"Pablo Morales-Ferreira, Miguel Santiago-Duran, Cristopher Gaytan-Diaz, J. L. González, Víctor Jesús Sosa Sosa, I. Lopez-Arevalo\",\"doi\":\"10.1109/SOSE.2018.00020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Information dispersal is a fault-tolerant technique where files of size |F| are split into n redundant pieces of size |F|/k that are dispersed to different servers where k pieces suffice for recovering the original file whenever k<n. This technique is a popular solution for service providers to withstand server failures and to improve the storage utilization. However, the coding/decoding service time produced by this technique as well as the management of pieces of heterogeneous size, that belong to different files, represent both a challenge for the deployment of this technique on clouds and clusters. This paper presents the design and development of a data distribution service for fault-tolerant cloud/cluster storage. This service includes an information dispersal client for coding/decoding files in-memory, which improves the service experience of end-users when delivering/retrieving files to/from cloud storage services. It also includes a data placement method to allocate, locate and manage redundant pieces of heterogeneous size in a uniform manner, which produces load balancing in the storage nodes. A prototype of this service was implemented in a private cloud and containerized cluster. 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A Data Distribution Service for Cloud and Containerized Storage Based on Information Dispersal
Information dispersal is a fault-tolerant technique where files of size |F| are split into n redundant pieces of size |F|/k that are dispersed to different servers where k pieces suffice for recovering the original file whenever k
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