{"title":"在异构网格环境中实现自优化、容错、高性能批量数据传输的框架","authors":"T. Kosar, George Kola, M. Livny","doi":"10.1109/ISPDC.2003.1267655","DOIUrl":null,"url":null,"abstract":"The drastic increase in the data requirements of scientific applications combined with an increasing trend towards collaborative research has resulted in the need to transfer large amounts of data among the participating sites. The general approach to transferring such large amounts of data has been to either dump data to tapes and mail them or employ scripts with an operator at each site to babysit the transfers to deal with failures. We introduce a framework which automates the whole process of data movement between different sites. The framework does not require any human intervention and it can recover automatically from various kinds of storage system, network, and software failures, guaranteeing completion of the transfers. The framework has sophisticated monitoring and tuning capability that increases the performance of the data transfers on the fly. The framework also generates on-the-fly visualization of the transfers making identification of problems and bottlenecks in the system simple.","PeriodicalId":368813,"journal":{"name":"Second International Symposium on Parallel and Distributed Computing, 2003. Proceedings.","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A framework for self-optimizing, fault-tolerant, high performance bulk data transfers in a heterogeneous grid environment\",\"authors\":\"T. Kosar, George Kola, M. Livny\",\"doi\":\"10.1109/ISPDC.2003.1267655\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The drastic increase in the data requirements of scientific applications combined with an increasing trend towards collaborative research has resulted in the need to transfer large amounts of data among the participating sites. The general approach to transferring such large amounts of data has been to either dump data to tapes and mail them or employ scripts with an operator at each site to babysit the transfers to deal with failures. We introduce a framework which automates the whole process of data movement between different sites. The framework does not require any human intervention and it can recover automatically from various kinds of storage system, network, and software failures, guaranteeing completion of the transfers. The framework has sophisticated monitoring and tuning capability that increases the performance of the data transfers on the fly. The framework also generates on-the-fly visualization of the transfers making identification of problems and bottlenecks in the system simple.\",\"PeriodicalId\":368813,\"journal\":{\"name\":\"Second International Symposium on Parallel and Distributed Computing, 2003. Proceedings.\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Second International Symposium on Parallel and Distributed Computing, 2003. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDC.2003.1267655\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Second International Symposium on Parallel and Distributed Computing, 2003. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPDC.2003.1267655","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A framework for self-optimizing, fault-tolerant, high performance bulk data transfers in a heterogeneous grid environment
The drastic increase in the data requirements of scientific applications combined with an increasing trend towards collaborative research has resulted in the need to transfer large amounts of data among the participating sites. The general approach to transferring such large amounts of data has been to either dump data to tapes and mail them or employ scripts with an operator at each site to babysit the transfers to deal with failures. We introduce a framework which automates the whole process of data movement between different sites. The framework does not require any human intervention and it can recover automatically from various kinds of storage system, network, and software failures, guaranteeing completion of the transfers. The framework has sophisticated monitoring and tuning capability that increases the performance of the data transfers on the fly. The framework also generates on-the-fly visualization of the transfers making identification of problems and bottlenecks in the system simple.