{"title":"慢速感知混合存储","authors":"Priya Sehgal, K. Voruganti, R. Sundaram","doi":"10.1109/MSST.2012.6232385","DOIUrl":null,"url":null,"abstract":"In the past storage vendors used different types of storage depending upon the type of workload. For example, they used Solid State Drives (SSDs) or FC hard disks (HDD) for online transaction, while SATA for archival type workloads. However, recently many storage vendors are designing hybrid SSD/HDD based systems that can satisfy multiple service level objectives (SLOs) of different workloads all placed together in one storage box, at better cost points. The combination is achieved by using SSDs as a read-write cache while HDD as a permanent store. In this paper we present an SLO based resource management algorithm that controls the amount of SSD given to a particular workload. This algorithm solves following problems: 1) it ensures that workloads do not interfere with each other 2) it ensure that we do not overprovision (cost wise) the amount of SSD allocated to a workload to satisfy its SLO (latency requirement) and 3) dynamically adjust SSD allocated in light of changing workload characteristics (i.e., provide only required amount of SSD). We have implemented our algorithm in a prototype Hybrid Store, and have tested its efficacy using many real workloads. Our algorithm satisfies latency SLOs almost always by utilizing close to optimal amount of SSD and saving 6-50% of SSD space compared to the naïve algorithm.","PeriodicalId":348234,"journal":{"name":"012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"SLO-aware hybrid store\",\"authors\":\"Priya Sehgal, K. Voruganti, R. Sundaram\",\"doi\":\"10.1109/MSST.2012.6232385\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the past storage vendors used different types of storage depending upon the type of workload. For example, they used Solid State Drives (SSDs) or FC hard disks (HDD) for online transaction, while SATA for archival type workloads. However, recently many storage vendors are designing hybrid SSD/HDD based systems that can satisfy multiple service level objectives (SLOs) of different workloads all placed together in one storage box, at better cost points. The combination is achieved by using SSDs as a read-write cache while HDD as a permanent store. In this paper we present an SLO based resource management algorithm that controls the amount of SSD given to a particular workload. This algorithm solves following problems: 1) it ensures that workloads do not interfere with each other 2) it ensure that we do not overprovision (cost wise) the amount of SSD allocated to a workload to satisfy its SLO (latency requirement) and 3) dynamically adjust SSD allocated in light of changing workload characteristics (i.e., provide only required amount of SSD). We have implemented our algorithm in a prototype Hybrid Store, and have tested its efficacy using many real workloads. Our algorithm satisfies latency SLOs almost always by utilizing close to optimal amount of SSD and saving 6-50% of SSD space compared to the naïve algorithm.\",\"PeriodicalId\":348234,\"journal\":{\"name\":\"012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSST.2012.6232385\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSST.2012.6232385","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In the past storage vendors used different types of storage depending upon the type of workload. For example, they used Solid State Drives (SSDs) or FC hard disks (HDD) for online transaction, while SATA for archival type workloads. However, recently many storage vendors are designing hybrid SSD/HDD based systems that can satisfy multiple service level objectives (SLOs) of different workloads all placed together in one storage box, at better cost points. The combination is achieved by using SSDs as a read-write cache while HDD as a permanent store. In this paper we present an SLO based resource management algorithm that controls the amount of SSD given to a particular workload. This algorithm solves following problems: 1) it ensures that workloads do not interfere with each other 2) it ensure that we do not overprovision (cost wise) the amount of SSD allocated to a workload to satisfy its SLO (latency requirement) and 3) dynamically adjust SSD allocated in light of changing workload characteristics (i.e., provide only required amount of SSD). We have implemented our algorithm in a prototype Hybrid Store, and have tested its efficacy using many real workloads. Our algorithm satisfies latency SLOs almost always by utilizing close to optimal amount of SSD and saving 6-50% of SSD space compared to the naïve algorithm.