CAREER: Achieving Self-Tunability of Peer-to-Peer Streaming Service through User-Level QoS Inference

职业：通过用户级 QoS 推理实现点对点流媒体服务的自调节

• 批准号: 0643488
• 负责人: Yi Cui
• 金额: $ 31.94万
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0643488&HistoricalAwards=false
• 关键词: CAREER; Achieving; Self; Tunability; Peer

This project aims to build a self-tuning multimedia streaming service that optimizes the user viewing experience by analyzing user behavior, inferring personalized quality of service (QoS) requirements, and tuning system and network resources to maximize utilities of all users. The advent of peer-to-peer (P2P) technology has provided the ideal playground for this research. Traces from operating P2P streaming systems provide rich datasets with which to study the influence of QoS factors on users' viewing experience. In addition, the affordability of a P2P streaming testbed provides both the sandbox to test research ideas and a general educational platform accessible to a large Internet user base.This CAREER project has two complementary tracks: use-level QoS modeling and QoS-aware resource allocation. On the modeling track, the user utility function is formulated using statistical tools such as regression analysis to infer the influence of individual network- and system-level QoS factors on the user behaviors (e.g., skipping, changing channel, or premature leave), which reflect the subjective user viewing experience. On the resource allocation track, the problem is studied using a time-aware multi-dimensional optimization framework, which helps address the unique challenges posed by the semantics of a P2P system, e.g., how to inclusively optimize the resource allocation under heterogeneous user utility functions. Broader Impact:This research plan is expected to incubate the emergence of an extremely cost-effective and scalable P2P service platform as the innovation hotbed to significantly lower the entry barrier for new media-rich applications. The analytical outcome from user behavior study will also bring strategic insights and design guidelines applicable to all multimedia service paradigms beyond P2P.

该项目旨在建立一个自调整的多媒体流媒体服务，通过分析用户行为，推断个性化的服务质量(Qos)要求，并调整系统和网络资源，以最大化所有用户的效用，来优化用户的观看体验。P2P(Peer-to-Peer)技术的出现为本研究提供了理想的平台。P2P流媒体系统的运营痕迹为研究服务质量因素对用户观看体验的影响提供了丰富的数据集。此外，P2P流媒体试验床的可负担性既提供了测试研究想法的沙盒，也提供了一个可供大量互联网用户访问的通用教育平台。这个职业项目有两个互补的轨道：使用级服务质量建模和服务质量感知的资源分配。在建模轨道上，使用诸如回归分析之类的统计工具来表达用户效用函数，以推断个体网络和系统级的Qos因素对用户行为(例如，跳过、换频道或过早离开)的影响，这反映了用户的主观观看体验。在资源分配路径上，使用时间感知的多维优化框架来研究这一问题，该框架有助于解决P2P系统语义带来的独特挑战，例如如何在不同用户效用函数下对资源分配进行包容性优化。更广泛的影响：这项研究计划预计将孵化出一个极具成本效益和可扩展性的P2P服务平台，作为创新温床，显著降低富媒体新应用的进入门槛。用户行为研究的分析结果还将带来适用于P2P以外的所有多媒体服务范例的战略见解和设计指南。