{"title":"Incremental Elasticity for NoSQL Data Stores","authors":"Antonis Papaioannou, K. Magoutis","doi":"10.1109/SRDS.2017.26","DOIUrl":null,"url":null,"abstract":"Service elasticity, the ability to rapidly expand or shrink service processing capacity on demand, has become a first-class property in the domain of infrastructure services. Scalable NoSQL data stores are the de-facto choice of applications aiming for scalable, highly available data persistence. The elasticity of such data stores is still challenging, due to the complexity and performance impact of moving large amounts of data over the network to take advantage of new resources (servers). In this paper we propose incremental elasticity, a new mechanism that progressively increases processing capacity in a fine-grain manner during an elasticity action by making sub-sections of the transferred data available for access on the new server, prior to completing the full transfer. In addition, by scheduling data transfers during an elasticity action in sequence (rather than as simultaneous transfers) between each pre-existing server involved and the new server, incremental elasticity leads to smoother elasticity actions, reducing their overall impact on performance.","PeriodicalId":6475,"journal":{"name":"2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS)","volume":"71 1","pages":"174-183"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SRDS.2017.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Service elasticity, the ability to rapidly expand or shrink service processing capacity on demand, has become a first-class property in the domain of infrastructure services. Scalable NoSQL data stores are the de-facto choice of applications aiming for scalable, highly available data persistence. The elasticity of such data stores is still challenging, due to the complexity and performance impact of moving large amounts of data over the network to take advantage of new resources (servers). In this paper we propose incremental elasticity, a new mechanism that progressively increases processing capacity in a fine-grain manner during an elasticity action by making sub-sections of the transferred data available for access on the new server, prior to completing the full transfer. In addition, by scheduling data transfers during an elasticity action in sequence (rather than as simultaneous transfers) between each pre-existing server involved and the new server, incremental elasticity leads to smoother elasticity actions, reducing their overall impact on performance.