Providing flow-based quality-of-service control in a large-scale network

R. Kuroda, M. Katsuki, A. Otaka, N. Miki
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引用次数: 5

Abstract

QoS (Quality-of-Services) technologies are very important for services like video streaming and real-time communications because they require continuous fixed bandwidth. In this paper we propose a new "feedback and distribution method" that provides per-flow based QoS for large-scale networks. We enhanced the method's ability to control jitter when distributing streaming data to a large number of users. TCP traffic is burst-type traffic and is used for Web navigation and E-mail, and UDP traffic is constant streaming traffic used for real-time applications. A new method to provide ene-to-end bandwidth control for all users in a large-scale network where streaming services are expected to be very important commercially. The proposed method enabled streaming stable distribution because streaming packets that were susceptible to jitter were protected from burst-data by dividing the input for each different type of flow. Traffic bursts absorbed by setting the traffic measurement interval to an optimal length. Our simulation results showed that streaming data with high bit rates hardly affected TCP data. Therefore, the proposed method stably distributed streaming data, and furthermore, it satisfactorily managed a mixture of various types of data.
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在大规模网络中提供基于流的服务质量控制
QoS(服务质量)技术对于视频流和实时通信等服务非常重要,因为它们需要连续的固定带宽。本文提出了一种新的“反馈和分配方法”,为大规模网络提供基于逐流的QoS。我们增强了该方法在向大量用户分发流数据时控制抖动的能力。TCP流量是突发流量,主要用于Web导航和E-mail; UDP流量是连续流流量,主要用于实时应用。一种为大规模网络中所有用户提供端到端带宽控制的新方法,其中流媒体服务在商业上非常重要。该方法通过为不同类型的流划分输入,使易受抖动影响的流数据包免受突发数据的影响,从而实现了流稳定分布。通过设置流量测量间隔的最优长度来吸收突发流量。仿真结果表明,高比特率的流数据几乎不影响TCP数据。因此,该方法可以稳定地分布流数据,并且可以很好地管理各种类型的混合数据。
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