HPC2-ARS: An Architecture for Real-Time Analytic of Big Data Streams

Yingchao Cheng, Z. Hao, Ruichu Cai, Wen Wen
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引用次数: 3

Abstract

HPC2-ARS supports a high performance cloud computing (HPC2) based streaming data analytic system, which ensures real-time response on unpredictable and fluctuating Big Data Streams by provisioning and scheduling computing resources autonomously. It focuses on parallel high-volume streaming applications, which have stringent real-time constraints and bring Big Data issues. It is a brand-new three-layered architecture, which solves three essential problems: (a) how many resources are needed for each application to achieve real-time analytic on streaming Big Data, (b) where to best place the allocated resources to minimize resource consumption, and (c) how to minimize response time for parallel applications. In summary, HPC2-ARS provides high performance streaming services.
HPC2-ARS:用于大数据流实时分析的架构
HPC2- ars支持基于高性能云计算(HPC2)的流数据分析系统,通过自主分配和调度计算资源,确保对不可预测和波动的大数据流的实时响应。它专注于并行的大容量流应用程序,这些应用程序具有严格的实时限制并带来大数据问题。它是一个全新的三层架构,解决了三个关键问题:(a)每个应用程序需要多少资源才能实现对流大数据的实时分析;(b)分配的资源应该放在哪里以最小化资源消耗;(c)如何最小化并行应用程序的响应时间。总之,HPC2-ARS提供了高性能的流媒体服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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