期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Wide Area Analytics for Geographically Distributed Datacenters
1
作者 Siqi Ji Baochun Li 《清华大学学报:自然科学英文版》 EI CAS CSCD 2016年第2期125-135,共11页
Big data analytics,the process of organizing and analyzing data to get useful information,is one of the primary uses of cloud services today.Traditionally,collections of data are stored and processed in a single datac... Big data analytics,the process of organizing and analyzing data to get useful information,is one of the primary uses of cloud services today.Traditionally,collections of data are stored and processed in a single datacenter.As the volume of data grows at a tremendous rate,it is less efficient for only one datacenter to handle such large volumes of data from a performance point of view.Large cloud service providers are deploying datacenters geographically around the world for better performance and availability.A widely used approach for analytics of geo-distributed data is the centralized approach,which aggregates all the raw data from local datacenters to a central datacenter.However,it has been observed that this approach consumes a significant amount of bandwidth,leading to worse performance.A number of mechanisms have been proposed to achieve optimal performance when data analytics are performed over geo-distributed datacenters.In this paper,we present a survey on the representative mechanisms proposed in the literature for wide area analytics.We discuss basic ideas,present proposed architectures and mechanisms,and discuss several examples to illustrate existing work.We point out the limitations of these mechanisms,give comparisons,and conclude with our thoughts on future research directions. 展开更多
关键词 big data ANALYTICS geo-distributed datacenters
上一页 1 下一页 到第
使用帮助 返回顶部 意见反馈