在客户流失情况下评估DHT设计权衡的性能与成本框架

Li, Jeremy, R. Morris, Kaashoek, Thomer, Gil
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引用次数: 258

摘要

分布式哈希表(dht)的协议包含了一些特性,可以在成员不断变化的情况下实现查找请求的低延迟。这些协议特性可以包括有向标识符空间、并行查找、成员变更的主动泛洪以及用于维护准确路由的稳定协议。此外,DHT协议具有可调优的参数,以便在查找延迟和由于维护流量造成的通信成本之间实现不同的权衡。特征和参数的相对重要性还没有得到很好的理解,因为大多数先前的工作都是在静态网络上评估协议。本文提出了一个性能与成本框架(PVC),允许设计人员比较不同协议特性和参数值的影响。PVC将协议视为消耗一定数量的网络带宽以实现一定的查找延迟,并有助于揭示协议使用额外网络资源以改善延迟的效率。为了证明PVC的价值,本文在不同的工作负载下模拟了Chord, Kademlia, Kelips, OneHop和Tapestry,并使用PVC来了解在流失下哪些特性更重要。PVC分析表明,有效利用额外带宽的关键是协议调整其路由表大小。它还表明路由表稳定是浪费的,可以用通过正常查找流量的机会学习来取代。这些见解结合起来表明,PVC是DHT设计人员的一个有价值的工具。
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A performance vs. cost framework for evaluating DHT design tradeoffs under churn
Protocols for distributed hash tables (DHTs) incorporate features to achieve low latency for lookup requests in the face of churn, continuous changes in membership. These protocol features can include a directed identifier space, parallel lookups, pro-active flooding of membership changes, and stabilization protocols for maintaining accurate routing. In addition, DHT protocols have parameters that can be tuned to achieve different tradeoffs between lookup latency and communication cost due to maintenance traffic. The relative importance of the features and parameters is not well understood, because most previous work evaluates protocols on static networks. This paper presents a performance versus cost framework (PVC) that allows designers to compare the effects of different protocol features and parameter values. PVC views a protocol as consuming a certain amount of network bandwidth in order to achieve a certain lookup latency, and helps reveal the efficiency with which protocols use additional network resources to improve latency. To demonstrate the value of PVC, this paper simulates Chord, Kademlia, Kelips, OneHop, and Tapestry under different workloads and uses PVC to understand which features are more important under churn. PVC analysis shows that the key to efficiently using additional bandwidth is for a protocol to adjust its routing table size. It also shows that routing table stabilization is wasteful and can be replaced with opportunistic learning through normal lookup traffic. These insights combined demonstrate that PVC is a valuable tool for DHT designers.
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