Can Degree Correlation Help to Design Resilient Superpeer Networks?

Animesh Srivastava, Niloy Ganguly, F. Peruani, Bivas Mitra
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引用次数: 1

Abstract

Resilience analysis of the popular P2P networks (like Gnutella) has emerged as an important research issue for the network community. Most of the contemporary studies primarily focused on the estimation of percolation threshold and disruption on the largest connected component due to node removal. However, real-world networks exhibit intrinsically degree-degree correlation, which makes the behavior of a real-world network distinctly different from a random network. We believe that the proper exploitation of the degree-degree correlation information can be helpful in healing the damage caused on P2P systems by the attacks. In order to investigate, we first develop an analytical framework to study the impact of degree-degree correlation on the resilience of real-world networks at different levels (node isolation, network density and component level). Our analysis shows that the Facebook-like network, which exhibits positive degree-degree correlation are much more robust than the negatively correlated network such as Gnutella. We capitalize on this observation and propose a lightweight correlation driven local link-rewiring mechanism that can improve the resilience of a Gnutella-like network against malicious node-perturbations. We substantiate our claims with the help of rigorous simulations on the real-world Gnutella topology and Facebook social graph as well as synthetic network datasets.
学位关联是否有助于设计弹性超级对等网络?
流行的P2P网络(如Gnutella)的弹性分析已经成为网络社区的一个重要研究问题。目前大多数研究主要集中在渗透阈值的估计和节点移除对最大连接分量的破坏上。然而,现实世界的网络表现出内在的程度相关性,这使得现实世界网络的行为与随机网络明显不同。我们认为,适当利用度相关信息可以帮助修复攻击对P2P系统造成的损害。为了进行研究,我们首先开发了一个分析框架来研究不同层次(节点隔离、网络密度和组件水平)的度相关对现实世界网络弹性的影响。我们的分析表明,与Gnutella等负相关网络相比,facebook类网络表现出正相关程度的鲁棒性要强得多。我们利用这一观察结果,提出了一种轻量级的相关驱动的本地链路重布线机制,该机制可以提高gnutella类网络对恶意节点扰动的弹性。我们通过对真实世界Gnutella拓扑和Facebook社交图谱以及合成网络数据集的严格模拟来证实我们的说法。
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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