DONUT:在异构对等分布的大规模分散系统中构建捷径

Sergey Legtchenko, Sébastien Monnet, Pierre Sens
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引用次数: 1

摘要

大规模分布式系统聚集了分布在世界各地的数千个节点。这样的系统需要提供良好的路由性能,而不管它们的大小和高流失率。为了实现这一需求,系统必须为其逻辑图(覆盖)添加适当的快捷方式。但是,为了选择有效的快捷方式,对等体需要获取覆盖拓扑的信息。在异构对等分布的情况下,检索此类信息并不简单。此外,由于混乱,拓扑结构迅速发展,使收集到的信息过时。最先进的系统要么通过强制节点采用统一分布来避免这个问题,要么只部分满足这些要求。为了解决这个问题,我们提出了DONUT,这是一种建立近似于对等体分布的局部地图的机制,允许对等体使用局部算法准确地估计到其他对等体的图距离。使用真实延迟和流失跟踪执行的评估表明,与最先进的技术相比,我们的地图将路由过程效率提高了至少20%。它指出,每个映射都是轻量级的,并且可以在每个对等点上消耗不到10个bps的时间,从而有效地在网络中传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DONUT: Building Shortcuts in Large-Scale Decentralized Systems with Heterogeneous Peer Distributions
Large-scale distributed systems gather thousands of peers spread all over the world. Such systems need to offer good routing performances regardless of their size and despite high churn rates. To achieve that requirement, the system must add appropriate shortcuts to its logical graph (overlay). However, to choose efficient shortcuts, peers need to obtain information about the overlay topology. In case of heterogeneous peer distributions, retrieving such information is not straightforward. Moreover, due to churn, the topology rapidly evolves, making gathered information obsolete. State of- the-art systems either avoid the problem by enforcing peers to adopt a uniform distribution or only partially fulfill these requirements. To cope with this problem, we propose DONUT, a mechanism to build a local map that approximates the peer distribution, allowing the peer to accurately estimate graph distance to other peers with a local algorithm. The evaluation performed with real latency and churn traces shows that our map increases the routing process efficiency by at least 20% compared to the state-of-the-art techniques. It points out that each map is lightweight and can be efficiently propagated through the network by consuming less than 10 bps on each peer.
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