Traffic balancing via smart packets

E. Gelenbe, R. Lent, A. Núñez
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引用次数: 4

Abstract

The World Wide Web (WWW) has caught people's attention since its inception and today is a major source of traffic in the Internet. WWW traffic is typically asymmetric: servers receive small requests but answer with large number of packets. To ensure good service, WWW servers require a large egress bandwidth to the Internet. We propose an innovative approach to connect Web servers to the Internet via many outgoing connections. We employ cognitive packet networks to make packets learn which link provides the best quality for each client so as to balance the WWW traffic effectively. Egress bandwidth can easily be increased by increasing the number of links to the Internet. The paper describes our traffic engineering approach, an implementation model, a testbed platform in the context of the Linux kernel, and measurement data; these indicate the usefulness of our proposal.
通过智能报文分担流量
万维网(WWW)自诞生以来就引起了人们的注意,今天是互联网流量的主要来源。WWW流量通常是不对称的:服务器接收小的请求,但是用大量的数据包回答。为了保证良好的服务,WWW服务器需要向Internet提供很大的出口带宽。我们提出了一种创新的方法,通过许多传出连接将Web服务器连接到Internet。我们采用认知分组网络,使分组学习哪条链路对每个客户端提供最好的质量,从而有效地平衡WWW流量。通过增加到Internet的链接数量,可以很容易地增加出口带宽。本文介绍了我们的流量工程方法、实现模型、Linux内核环境下的测试平台和测量数据;这些表明我们的建议是有用的。
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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