CAREER: Beyond Akamai and BitTorrent: Information and Decision Dynamics in Content Distribution Networks

职业：超越 Akamai 和 BitTorrent：内容分发网络中的信息和决策动态

• 批准号: 1149458
• 负责人: Srinivas Shakkottai
• 金额: $ 40万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1149458&HistoricalAwards=false
• 关键词: CAREER; Beyond; Akamai; BitTorrent; Information

Recent studies estimate that a majority of Internet traffic is digital content distribution, whose dominant component is applications that require tight time deadlines, such as content streaming and realtime services. Excessive costs of always-available server-based content distribution networks (CDNs), and a lack of service guarantees in low-cost peer-to-peer (P2P) networks have led the pursuit of agile hybrids of both systems that seek to leverage the best of each. Such a hybrid requires coordination across peers, across information, and across shared resources available to the peers, which form the three research thrusts of this project. The first objective of this project is the development of a systematic analytical framework to achieve this coordination, using ideas drawn from game theory, learning and stochastic networks. The aim is to capture the fundamental properties of large-scale content distribution systems using analytical models, and bind together applications such as file sharing, streaming, cloud-based services, and device-to-device wireless networks by employing this framework. The second is to generate prescriptions for ensuring economic viability by using revelations on the value of the system to participating agents. Finally, the basic analytical methodology developed will be applicable generally beyond the core problem of content distribution. The analytical insights will be validated via a smart-phone-based server-assisted P2P content streaming network. Broader Impact: The project is supported by an education and outreach agenda that aims at familiarizing students with analytical results developed and how best to apply them in a real-world setting. A core component is a semester-long course for seniors and first-year grads in which classroom teaching is complemented by research experience through app development at the AM-Droiders smart-phone laboratory. Outreach includes demonstrations and illustrative projects at a yearly week-long summer camp for high school students, as well as tele-seminars in which students from multiple universities (including Prairie View A&M, an HBCU) can participate interactively. The project is further enhanced by strong collaborations with industry.

最近的研究估计，大部分互联网流量是数字内容分发，其主要组成部分是需要严格时间期限的应用程序，例如内容流和实时服务。 始终可用的基于服务器的内容分发网络 (CDN) 的成本过高，以及低成本点对点 (P2P) 网络缺乏服务保证，导致人们对这两种系统的敏捷混合体的追求，这些系统寻求利用每一个都是最好的。 这种混合需要同行之间、信息之间以及同行可用的共享资源之间的协调，这构成了该项目的三个研究重点。 该项目的首要目标是利用博弈论、学习和随机网络的思想，开发一个系统的分析框架来实现这种协调。 目的是使用分析模型捕获大规模内容分发系统的基本属性，并使用该框架将文件共享、流媒体、基于云的服务和设备到设备无线网络等应用程序绑定在一起。 第二个是通过向参与主体揭示系统的价值来制定确保经济可行性的处方。 最后，所开发的基本分析方法将普遍适用于内容分发的核心问题之外。 分析见解将通过基于智能手机的服务器辅助 P2P 内容流网络进行验证。 更广泛的影响：该项目得到了教育和推广议程的支持，旨在让学生熟悉所开发的分析结果以及如何最好地将其应用到现实世界中。 核心组成部分是为高年级学生和一年级毕业生开设的为期一个学期的课程，其中课堂教学辅以 AM-Droiders 智能手机实验室应用程序开发的研究经验。 外展活动包括每年为高中生举办的为期一周的夏令营中的演示和说明性项目，以及来自多所大学（包括 Prairie View A&M，HBCU）的学生可以互动参与的远程研讨会。 通过与业界的强有力合作，该项目得到进一步加强。