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Understanding and Improving Large-scale Content Distribution.

机译：了解和改善大规模内容分发。

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摘要

The Internet architecture was not designed for delivering large-scale content. Therefore, with the increase in popularity and demand for videos on the Internet, video content providers(CPs) have to come up with a number of solutions to achieve high degree of scalability, resilience and performance requirements of video content distribution. In this thesis we aim to answer the following research questions: (a) how do large scale content distribution systems currently work and what problems do they encounter, and (b) how can we solve those problems both in the short term as well as in the long term. Towards this end, this thesis makes the following contributions:;First, we study original YouTube architecture to understand how a video delivery system with small number of large data centers handle scalability and performance challenges. Specifically, we uncover the use of location-agnostic proportional load-balancing strategy and how that affects its ISPs (Internet service providers).;Second, we investigate how a more distributed approach employed by current YouTube improves the resilience of its delivery system. Using active measurement study, we uncover the use of multiple namespaces, tiered cache hierarchy, dynamic and location aware DNS (Domain Name System). Although this approach improves the resilience and performance compared to location-agnostic approach, since YouTube uses its own content delivery infrastructure, it is likely encounter scalability challenges as its content size and popularity increases.;Third, to complement the two in-house content distribution architectures, we study Netflix and Hulu. These services make use of multiple third party content delivery networks (CDNs) to deliver their content. We find that their CDN selection and adaptation strategies lead to suboptimal user experience. We then propose inexpensive measurement-based CDN selection strategies that significantly improve the quality of the video streaming. Additionally, we find that although CDN networks themselves might be well designed the CDN selection mechanism and "intelligence" of the client software can be improved upon to provide users with better quality of service.;Finally, building upon the results of these and other recent works on understanding large scale content distribution systems, we propose a first step in the direction of an open CDN architecture that allows for better scalability and performance. The two key ingredient of this proposal are to let any willing ISP to participate as CDNs and instrument client software to make decisions based upon measurements. This proposal is incrementally deployable. It is also economically more sustainable as it opens up new sources of revenue for the ISPs. We also provide a proof of concept implementation for this architecture using PlanetLab infrastructure.
机译：Internet体系结构并非设计用于传递大规模内容。因此，随着互联网上视频的普及和需求的增加，视频内容提供商（CP）必须提出许多解决方案，以实现视频内容分发的高度可扩展性，弹性和性能要求。在本文中，我们旨在回答以下研究问题：（a）大型内容分发系统目前如何工作，它们会遇到什么问题，（b）在短期和短期内如何解决这些问题？从长远来看。为此，本论文做出了以下贡献：首先，我们研究原始的YouTube体系结构，以了解具有少量大型数据中心的视频交付系统如何应对可伸缩性和性能挑战。具体来说，我们发现与位置无关的比例负载平衡策略的使用以及它如何影响其ISP（互联网服务提供商）。其次，我们研究当前YouTube采用的更加分散的方法如何提高其交付系统的弹性。通过积极的度量研究，我们发现了多个名称空间，分层缓存层次结构，动态和位置感知DNS（域名系统）的使用。尽管与位置无关的方法相比，此方法提高了弹性和性能，但是由于YouTube使用自己的内容交付基础结构，因此随着内容大小和受欢迎程度的增加，它很可能会遇到可扩展性方面的挑战。第三，这是对两种内部内容分发的补充架构，我们研究Netflix和Hulu。这些服务利用多个第三方内容交付网络（CDN）交付其内容。我们发现，他们的CDN选择和适应策略会导致次优的用户体验。然后，我们提出便宜的基于测量的CDN选择策略，该策略可显着提高视频流的质量。此外，我们发现，尽管CDN网络本身可能设计得很好，但CDN选择机制和客户端软件的“智能”可以得到改进，从而为用户提供更好的服务质量。最后，在这些结果和其他最新结果的基础上致力于理解大规模内容分发系统，我们建议朝着开放CDN体系结构的方向迈出第一步，该CDN体系结构可提供更好的可伸缩性和性能。该提案的两个关键要素是让任何愿意的ISP作为CDN参与其中，并让仪器客户端软件根据测量结果做出决策。该提议是可增量部署的。它在经济上也更具可持续性，因为它为ISP开辟了新的收入来源。我们还提供了使用PlanetLab基础架构对此架构进行概念验证的方法。

著录项

  • 作者

    Adhikari, Vijay Kumar.;

  • 作者单位

    University of Minnesota.;

  • 授予单位 University of Minnesota.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 119 p.
  • 总页数 119
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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