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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Randomized Protocols for Duplicate Elimination in Peer-to-Peer Storage Systems
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Randomized Protocols for Duplicate Elimination in Peer-to-Peer Storage Systems

机译：对等存储系统中消除重复的随机协议

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摘要

Distributed peer-to-peer systems rely on voluntary participation of peers to effectively manage a storage pool. In such systems, data is generally replicated for performance and availability. If the storage associated with replication is not monitored and provisioned, the underlying benefits may not be realized. Resource constraints, performance scalability, and availability present diverse considerations. Availability and performance scalability, in terms of response time, are improved by aggressive replication, whereas resource constraints limit total storage in the network. Identification and elimination of redundant data pose fundamental problems for such systems. In this paper, we present a novel and efficient solution that addresses availability and scalability with respect to management of redundant data. Specifically, we address the problem of duplicate elimination in the context of systems connected over an unstructured peer-to-peer network in which there is no a priori binding between an object and its location. We propose two randomized protocols to solve this problem in a scalable and decentralized fashion that does not compromise the availability requirements of the application. Performance results using both large-scale simulations and a prototype built on PlanetLab demonstrate that our protocols provide high probabilistic guarantees while incurring minimal administrative overheads.
机译：分布式对等系统依靠对等方的自愿参与来有效地管理存储池。在此类系统中，通常会复制数据以提高性能和可用性。如果没有监视和配置与复制相关的存储，则可能无法实现潜在的好处。资源限制，性能可伸缩性和可用性提出了多种考虑。主动复制提高了响应时间方面的可用性和性能可伸缩性，而资源限制限制了网络中的总存储量。识别和消除冗余数据给此类系统带来了根本问题。在本文中，我们提出了一种新颖有效的解决方案，该解决方案针对冗余数据的管理解决了可用性和可伸缩性。具体来说，我们解决了在通过非结构化对等网络连接的系统中消除重复项的问题，在该网络中，对象与其位置之间没有先验绑定。我们提出了两种随机协议以可扩展和分散的方式解决此问题，而不会损害应用程序的可用性要求。使用大规模仿真和在PlanetLab上构建的原型所获得的性能结果表明，我们的协议可提供较高的概率保证，同时将管理开销降至最低。

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