{"title":"比较ssd放置策略以扩展云中的数据库","authors":"Yingyi Bu, Hongrae Lee, J. Madhavan","doi":"10.1145/2523616.2525949","DOIUrl":null,"url":null,"abstract":"Flash memory solid state drives (SSDs) have increasingly been advocated and adopted as a means of speeding up and scaling up data-driven applications. However, given the layered software architecture of cloud-based services, there are a number of options available for placing SSDs. In this work, we studied the trade-offs involved in different SSD placement strategies, their impact of response time and throughput, and ultimately the potential in achieving scalability in Google Fusion Tables (GFT), a cloud-based service for data management and visualization [1].","PeriodicalId":298547,"journal":{"name":"Proceedings of the 4th annual Symposium on Cloud Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Comparing SSD-placement strategies to scale a database-in-the-cloud\",\"authors\":\"Yingyi Bu, Hongrae Lee, J. Madhavan\",\"doi\":\"10.1145/2523616.2525949\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Flash memory solid state drives (SSDs) have increasingly been advocated and adopted as a means of speeding up and scaling up data-driven applications. However, given the layered software architecture of cloud-based services, there are a number of options available for placing SSDs. In this work, we studied the trade-offs involved in different SSD placement strategies, their impact of response time and throughput, and ultimately the potential in achieving scalability in Google Fusion Tables (GFT), a cloud-based service for data management and visualization [1].\",\"PeriodicalId\":298547,\"journal\":{\"name\":\"Proceedings of the 4th annual Symposium on Cloud Computing\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th annual Symposium on Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2523616.2525949\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th annual Symposium on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2523616.2525949","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparing SSD-placement strategies to scale a database-in-the-cloud
Flash memory solid state drives (SSDs) have increasingly been advocated and adopted as a means of speeding up and scaling up data-driven applications. However, given the layered software architecture of cloud-based services, there are a number of options available for placing SSDs. In this work, we studied the trade-offs involved in different SSD placement strategies, their impact of response time and throughput, and ultimately the potential in achieving scalability in Google Fusion Tables (GFT), a cloud-based service for data management and visualization [1].
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