Opus:覆盖对等实用服务

R. Braynard, Dejan Kostic, Adolfo Rodriguez, J. Chase, Amin Vahdat
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引用次数: 99

摘要

如今,越来越多的重要网络服务(如内容分发、复制服务和存储系统)正在跨多个Internet站点部署覆盖层,以提供更好的性能、可靠性和适应性。然而,目前这样的网络服务必须单独重新实现基本相似的功能。例如,应用程序必须配置覆盖以满足其对规模、服务质量和可靠性的特定需求。此外,它们必须动态地将数据和功能映射到网络资源(包括服务器、存储和网络路径)上,以适应负载或网络条件的变化。在本文中,我们介绍了Opus,这是一个大规模的覆盖实用服务,它为同时托管多个分布式应用程序提供了一个公共平台和必要的抽象。在我们的实用新型中,广域资源映射由应用程序的性能和可用性目标规范指导。Opus然后根据动态变化的系统特性分配可用节点来满足竞争应用程序的需求。具体来说,我们描述了与以下方面相关的问题和初步结果:i)开发一种通用架构,使广泛的应用程序能够在网络上推动其功能;ii)构建与单个应用程序的性能和可靠性特征相匹配的覆盖层,并扩展到数千个参与节点;iii)使用服务水平协议在竞争应用程序之间动态分配公用事业资源。iv)开发分散的技术,通过使用层次、聚合和近似来跟踪全局系统特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Opus: an overlay peer utility service
Today, an increasing number of important network services, such as content distribution, replicated services, and storage systems, are deploying overlays across multiple Internet sites to deliver better performance, reliability and adaptability. Currently however, such network services must individually reimplement substantially similar functionality. For example, applications must configure the overlay to meet their specific demands for scale, service quality and reliability. Further, they must dynamically map data and functions onto network resources-including servers, storage, and network paths-to adapt to changes in load or network conditions. In this paper, we present Opus, a large-scale overlay utility service that provides a common platform and the necessary abstractions for simultaneously hosting multiple distributed applications. In our utility model, wide-area resource mapping is guided by an application's specification of performance and availability targets. Opus then allocates available nodes to meet the requirements of competing applications based on dynamically changing system characteristics. Specifically, we describe issues and initial results associated with: i) developing a general architecture that enables a broad range of applications to push their functionality across the network, ii) constructing overlays that match both the performance and reliability characteristics of individual applications and scale to thousands of participating nodes, iii) using Service Level Agreements to dynamically allocate utility resources among competing applications, and iv) developing decentralized techniques for tracking global system characteristics through the use of hierarchy, aggregation, and approximation.
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