NeTS: Small: Inter-Domain Traffic Engineering though ISP Cooperation and Competition

NetS：小型：通过 ISP 合作与竞争进行域间流量工程

• 批准号: 1218374
• 负责人: Koushik Kar
• 金额: $ 40万
• 依托单位: Rensselaer Polytechnic Institute
• 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 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1218374&HistoricalAwards=false
• 关键词: NeTS; Small; Inter; Domain; Traffic

This project takes a comprehensive look at inter-domain traffic engineering, and how it can be done efficiently through cooperation as well as competition between Internet Service Providers (ISPs), and at different timescales. Using network flow decomposition and separate convex optimization techniques, the project seeks to design distributed inter-domain traffic engineering solutions that, along with effective intra-domain traffic engineering, converge to optimal traffic flows in the entire Internet. The project also involves modeling of traffic engineering - under competitive pricing of inter-domain forwarding by ISPs - as a two-timescale pricing-forwarding game, and the study of existence, computability, and efficiency of the equilibrium. The project explores dynamics and convergence of distributed pricing updates by ISPs, and compare different pricing strategies and models like point-to-destination pricing vs. point-to-anywhere pricing, linear vs. non-linear pricing, and cascaded vs. non-cascaded pricing.The project considers inter-ISP interactions and decision-making at multiple timescales that involve traffic forwarding (fast timescale) and pricing updates (slow timescale), where decision-making on a slower timescale may depend on that at a faster timescale. Furthermore, the project considers both cooperative and competitive approaches through which the Internet as a whole (and not individual ISP networks or Autonomous Systems) can be utilized efficiently. The models and approaches considered take into account the control and operational structure of the Internet that consists of multiple providers seeking to maximize their individual benefits, and accordingly considers the relevant issues like competitive efficiency. Using these models, the project seeks to develop competitive pricing-forwarding solutions that can converge to efficient and stable traffic flows in the entire network (Internet.Broader impact: The issues that the project investigates are timely, and fundamental to the efficient operation and economic viability of the Internet in the long run. Solutions that the project is developing will improve the overall use of the Internet bandwidth resources through optimal/near-optimal traffic cross-provider engineering in the Internet. Pricing strategies developed and investigated in this project will improve the Internet's economic efficiency and viability through inter-ISP competition. For providers, this would imply more efficient and flexible management of their available resources, better investment in infrastructure, and higher revenue overall. For end-users, it would imply better service at lower cost. Research results will be used in advanced graduate coursework on network optimization and algorithmic game theory. The PIs will also enhance the research and educational experience of undergraduate students, by supervising undergraduate research projects.

本项目全面探讨跨域通讯工程，以及如何透过互联网服务供应商（isp）之间的合作和竞争，在不同的时间尺度下，有效地完成这项工程。利用网络流分解和单独的凸优化技术，该项目寻求设计分布式域间流量工程解决方案，与有效的域内流量工程一起，收敛到整个互联网的最优流量。该项目还涉及流量工程建模-在互联网服务提供商的域间转发竞争性定价下-作为一个双时间尺度定价-转发博弈，并研究平衡的存在性、可计算性和效率。该项目探讨了互联网服务提供商分布式定价更新的动态和收敛性，并比较了不同的定价策略和模型，如点到目的地定价与点到任何地方定价、线性定价与非线性定价、级联定价与非级联定价。该项目考虑了isp之间的相互作用和多个时间尺度下的决策，包括流量转发（快速时间尺度）和价格更新（慢时间尺度），其中慢时间尺度上的决策可能取决于快时间尺度上的决策。此外，该项目考虑了合作和竞争两种方法，通过这种方法，互联网作为一个整体（而不是单个的ISP网络或自治系统）可以有效地利用。所考虑的模型和方法考虑了互联网的控制和运营结构，其中包括寻求最大化其个人利益的多个提供商，并相应地考虑了竞争效率等相关问题。利用这些模型，该项目寻求开发具有竞争力的定价转发解决方案，这些解决方案可以汇聚到整个网络（互联网）中高效和稳定的流量。更广泛的影响：该项目调查的问题是及时的，从长远来看，对互联网的有效运作和经济可行性至关重要。该项目正在开发的解决方案将通过互联网中最优/接近最优的流量跨提供商工程来改善互联网带宽资源的整体使用。本项目开发和研究的定价策略将通过互联网服务提供商之间的竞争提高互联网的经济效率和生存能力。对于供应商来说，这意味着更有效和灵活地管理他们的可用资源，更好地投资于基础设施，并获得更高的总体收入。对最终用户来说，这意味着以更低的成本获得更好的服务。研究成果将用于网络优化和算法博弈论的高级研究生课程。pi还将通过指导本科生的研究项目，提高本科生的研究和教育经验。