{"title":"预算-传输:一种低成本的跨业务数据存储和传输方案","authors":"Galen Deal, Yang Peng, Hua Qin","doi":"10.1109/BigDataCongress.2018.00022","DOIUrl":null,"url":null,"abstract":"With the offerings of compelling cloud storage services from various cloud service providers, numerous web and mobile applications are leveraging cloud to store data for long-term usage. In this paper, we propose Budget-Transfer, a unique scheme to reduce the long-term cost of storing large data sets using cloud storage services. In contrast to most existing works, we study the storage cost-minimization problem by leveraging various available storage services that can provide different levels of performance at different pricing cost, under the constraint of data-access performance requirement. The key idea of Budget-Transfer is to continually transfer large data sets between different cloud storage services so as to satisfy performance requirements while avoiding overpaying for unnecessarily high performance guarantees. Budget-Transfer selects which service to use for each request with a goal towards minimizing the overall storage cost, rather than selecting whichever would be the locally cheapest service. Thus, the accumulative data-transfer and data-storage cost over a long period of time to satisfy a sequence of data-access requests can be reduced for the system. Simulation results show that Budget-Transfer performs well under various system parameters and request patterns, and can significantly reduce costs compared to other schemes.","PeriodicalId":177250,"journal":{"name":"2018 IEEE International Congress on Big Data (BigData Congress)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Budget-Transfer: A Low Cost Inter-Service Data Storage and Transfer Scheme\",\"authors\":\"Galen Deal, Yang Peng, Hua Qin\",\"doi\":\"10.1109/BigDataCongress.2018.00022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the offerings of compelling cloud storage services from various cloud service providers, numerous web and mobile applications are leveraging cloud to store data for long-term usage. In this paper, we propose Budget-Transfer, a unique scheme to reduce the long-term cost of storing large data sets using cloud storage services. In contrast to most existing works, we study the storage cost-minimization problem by leveraging various available storage services that can provide different levels of performance at different pricing cost, under the constraint of data-access performance requirement. The key idea of Budget-Transfer is to continually transfer large data sets between different cloud storage services so as to satisfy performance requirements while avoiding overpaying for unnecessarily high performance guarantees. Budget-Transfer selects which service to use for each request with a goal towards minimizing the overall storage cost, rather than selecting whichever would be the locally cheapest service. Thus, the accumulative data-transfer and data-storage cost over a long period of time to satisfy a sequence of data-access requests can be reduced for the system. Simulation results show that Budget-Transfer performs well under various system parameters and request patterns, and can significantly reduce costs compared to other schemes.\",\"PeriodicalId\":177250,\"journal\":{\"name\":\"2018 IEEE International Congress on Big Data (BigData Congress)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Congress on Big Data (BigData Congress)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BigDataCongress.2018.00022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Congress on Big Data (BigData Congress)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BigDataCongress.2018.00022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Budget-Transfer: A Low Cost Inter-Service Data Storage and Transfer Scheme
With the offerings of compelling cloud storage services from various cloud service providers, numerous web and mobile applications are leveraging cloud to store data for long-term usage. In this paper, we propose Budget-Transfer, a unique scheme to reduce the long-term cost of storing large data sets using cloud storage services. In contrast to most existing works, we study the storage cost-minimization problem by leveraging various available storage services that can provide different levels of performance at different pricing cost, under the constraint of data-access performance requirement. The key idea of Budget-Transfer is to continually transfer large data sets between different cloud storage services so as to satisfy performance requirements while avoiding overpaying for unnecessarily high performance guarantees. Budget-Transfer selects which service to use for each request with a goal towards minimizing the overall storage cost, rather than selecting whichever would be the locally cheapest service. Thus, the accumulative data-transfer and data-storage cost over a long period of time to satisfy a sequence of data-access requests can be reduced for the system. Simulation results show that Budget-Transfer performs well under various system parameters and request patterns, and can significantly reduce costs compared to other schemes.