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On the scaling of congestion in the Internet graph

机译:关于互联网图中拥塞的缩放

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As the Internet grows in size, it becomes crucial to understand how the speeds of links in the network must improve in order to sustain the pressure of new end-nodes being added each day. Although the speeds of links in the core and at the edges improve roughly according to Moore's law, this improvement alone might not be enough. Indeed, the structure of the Internet graph and routing in the network might necessitate much faster improvements in the speeds of key links in the network.In this paper, using a combination of analysis and extensive simulations, we show that the worst congestion in the Internet AS-level graph in fact scales poorly with the network size (n(1+Omega(1)), where n is the number of nodes), when shortest-path routing is used to route traffic between ASes. We also show, somewhat surprisingly, that policy-based routing does not exacerbate the maximum congestion when compared to shortest-path routing.Our results show that it is crucial to identify ways to alleviate this congestion to avoid some links from being perpetually congested. To this end, we show that the congestion scaling properties of Internet-like graphs can be improved dramatically by introducing moderate amounts of redundancy in the graph in terms of parallel edges between pairs of adjacent nodes.
机译:随着Internet规模的增长,了解如何提高网络链接速度以承受每天添加的新终端节点的压力变得至关重要。尽管根据摩尔定律,核心和边缘的链接速度大致有所提高,但仅靠这种改进可能还不够。确实,Internet图的结构和网络中的路由可能需要更快地改善网络中关键链接的速度。在本文中,通过分析和广泛的模拟相结合,我们证明了Internet中最严重的拥塞当使用最短路径路由在AS之间路由流量时,AS级别图实际上无法随网络大小(n(1 + Omega(1)),其中n是节点数)缩放。我们还出乎意料的是,与最短路径路由相比,基于策略的路由并不会加剧最大的拥塞情况。我们的结果表明,找到缓解这种拥塞的方法至关重要,以避免某些链路永久拥塞。为此,我们表明,通过在图上根据相邻节点对之间的平行边引入适度的冗余,可以显着改善类似Internet的图的拥塞缩放属性。

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