存储、调度和切换——大数据时代新的数据交付模式

Weiqiang Sun, Fengqin Li, W. Guo, Yaohui Jin, Weisheng Hu
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引用次数: 8

摘要

大数据时代对现有的网络基础设施提出了前所未有的挑战。在当今的网络中,数据在网络中传输是作为一系列数据包的组合,一个接一个地传递,而不考虑数据的整体和各自的服务水平要求。所谓的大象数据,可能对传输延迟不太敏感,与老鼠数据竞争宝贵的网络资源,在大多数情况下,来自交互式和延迟敏感的应用程序。因此,交互式应用的服务质量(QoS)难以提供,网络的利用率较低。我们提出了一个新的数据传输模型来补充现有的逐包转发范式。在新的数据传输模型中,(由数据源)为每个大数据传输请求分配服务级别需求。网络不是在进入网络后立即按包传输这些数据,而是将数据存储起来,直到发现有必要或有足够的网络资源可用于传输为止。通过动态电路交换实现了定时的数据传输。我们还给出了一些SSS网络的初步仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Store, schedule and switch - A new data delivery model in the big data era
The big data era is posing unprecedented challenges on the existing network infrastructure. In today's networks, data are transferred across the network as a combination of a series of packets, delivered one by one, without considering the data in their entirety with respective service level requirements. The so called elephant data, which may be less sensitive to transfer delay, compete precious network resources with mice data, in most cases from interactive and delay sensitive applications. Consequently, the Quality of Service (QoS) of interactive applications is hard to provision, and the utility of network is low. We propose a new data transfer model to complement the existing per-packet forwarding paradigm. In the new data transfer model, a service level requirement is assigned (by the data source) to each big data transfer request. Instead of transferring these data on per-packet bases immediately upon entering the network, the network stores the data until it find necessary, or enough network resource is available for that transfer. The scheduled data delivery is realized through the use of dynamic circuit switching. We also present some preliminary simulation results of SSS networks.
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