首页> 外文会议>Distributed Computing Systems (ICDCS), 2012 IEEE 32nd International Conference on >Publiy+: A Peer-Assisted Publish/Subscribe Service for Timely Dissemination of Bulk Content
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Publiy+: A Peer-Assisted Publish/Subscribe Service for Timely Dissemination of Bulk Content

机译:Publiy +:及时发布大容量内容的同行协助发布/订阅服务

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摘要

Publish/Subscribe (P/S) systems and file sharing applications traditionally share the common goal of disseminating data among large populations of users. Despite this similarity, the former focuses on timely dissemination of small-sized notification messages, while the latter presumes larger types of bulk content with less emphasis on the time needed between release and delivery of data. In this paper, we develop a peer-assisted content dissemination mechanism to bridge this gap by adopting the P/S model. We propose a hybrid two-layer architecture in which P/S brokers act as coordinators and guide their clients with interest in similar content to engage in direct exchange of data blocks in a peer-to-peer and cooperative fashion. Furthermore, we use network coding in order to facilitate data exchange among clients. Our peer-assisted scheme offloads the burden of disseminating huge volumes of data from P/S brokers to subscribers themselves. As an added advantage of our approach, brokers employ strategies that help shape traffic flows in multi-domain network settings. Finally, we have implemented our approach and carried out extensive large-scale experimental evaluation on a cluster with aggregate data transfers of up to 1 TB and involving up to 1000 subscribers. Our results demonstrate good scalability and faster content delivery compared to file sharing protocols such as BitTorrent.
机译:传统上,发布/订阅(P / S)系统和文件共享应用程序具有在大量用户中分发数据的共同目标。尽管存在这种相似性,但前者着重于及时分发小型通知消息,而后者则假定较大类型的批量内容,而较少强调在数据发布和交付之间所需的时间。在本文中,我们开发了一种对等辅助的内容分发机制,通过采用P / S模型来弥合这种差距。我们提出了一种混合的两层体系结构,在该体系结构中,P / S代理充当协调者,并引导对相似内容感兴趣的客户以点对点和协作方式进行数据块的直接交换。此外,我们使用网络编码来促进客户端之间的数据交换。我们的同伴协助计划减轻了将大量数据从P / S代理分发给订户本身的负担。作为我们方法的另一个优势,经纪人采用的策略可帮助塑造多域网络设置中的流量。最后,我们已经实施了我们的方法,并对群集进行了大规模的大规模实验评估,该群集的总数据传输量高达1 TB,涉及的订户多达1000个。与文件共享协议(例如BitTorrent)相比,我们的结果证明了良好的可伸缩性和更快的内容交付。

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