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首页> 外文期刊>Cloud Computing, IEEE >Programming SDN-Native Big Data Applications: Research Gap Analysis
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Programming SDN-Native Big Data Applications: Research Gap Analysis

机译:编程SDN原生大数据应用程序:研究差距分析

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摘要

Software-Defined Networking has involved as a preferred abstraction for sharing network resources within a cloud datacenter in response to simultaneous data retrieval and computation demands from around the world. However, several research challenges need to be investigated before SDN powered-cloud datacenters are able to efficiently process big data as defined by its “4V” characteristics. Big data enabled-systems have to be able to respond to concurrent requests and allocate computing (e.g., virtual machine instances), storage (e.g., disk space) and networking (e.g., bandwidth) resources efficiently and effectively.
机译:作为一次优选的抽象,软件定义网络已涉及到共享云数据中心内的网络资源,以响应来自世界各地的同步数据检索和计算需求。但是,在SDN驱动的云数据中心能够有效处理按其“ 4V”特性定义的大数据之前,需要研究一些研究挑战。启用大数据的系统必须能够响应并发请求并高效地分配计算资源(例如虚拟机实例),存储资源(例如磁盘空间)和网络资源(例如带宽)。

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