NEDG: Locally-optimal Power, Rate Adaptation and Scheduling in Wireless Networks

NEDG：无线网络中的局部最优功率、速率适应和调度

• 批准号: 0831973
• 负责人: Rohit Negi
• 金额: $ 35万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0831973&HistoricalAwards=false
• 关键词: NEDG; Locally; optimal; Power; Rate

The growth of communication networks has profoundly increased the availability of information and increased productivity. A key requirement in continuing to reap the benefits of connectivity is the growth of pervasive wireless networks. Wireless networks are resource constrained, primarily due to their broadcast nature. Alleviation of this constraint requires an efficient, distributed solution to the Medium Access Control (MAC) problem. In this project, the investigators study `locally-optimal scheduling and PHY adaptation', by incorporating physical layer (PHY) models into maximal scheduling for increased accuracy, and priority mechanisms for increased efficiency. This will result in the design of efficient, distributed MAC protocols, whose guarantees are accurate, from the PHY perspective. The results from this research, which is training a graduate Ph.D., are disseminated through appropriate publications and seminars, to guide the development of future wireless network MAC protocols and are incorporated into the university?s undergraduate and graduate courses.PHY adaptation and scheduling (MAC) in general ad hoc wireless networks, is an NP-hard problem, especially, if distributed solutions are desired. In this project, the investigators study locally-optimal algorithms, a generalization of maximal scheduling, using broad queuing results that prove stability, and adapt them to wireless networks, with careful attention paid to the PHY model. Theoretical characterization of the performance of these algorithms is carried out using graph theoretic and optimization theoretic analysis, along with intuition on the design of optimal (though, centralized) MAC algorithms. The key ideas of this research, which are at the intersection of communication theory, queuing theory, graph theory and optimization, are incorporated into university courses, using the concepts of Lyapunov functions and fluid models.

通信网络的发展深刻地增加了信息的可获得性，提高了生产率。继续受益于连接的一个关键要求是普及无线网络的增长。无线网络资源有限，这主要是因为它们的广播性质。要缓解这一限制，需要一种高效的分布式解决方案来解决媒体访问控制(MAC)问题。在这个项目中，研究人员通过将物理层(PHY)模型合并到最大调度中以提高精度，以及通过优先机制来提高效率，来研究“局部最优调度和PHY适应”。这将导致设计高效的分布式MAC协议，从PHY的角度来看，其保证是准确的。这项正在培养博士研究生的研究成果通过适当的出版物和研讨会传播，以指导未来无线网络MAC协议的开发，并被纳入大学-S本科和研究生课程。在一般自组织无线网络中，物理层适配和调度(MAC)是一个NP-Hard问题，特别是在需要分布式解决方案的情况下。在这个项目中，研究人员研究了局部最优算法，这是最大调度的推广，使用证明稳定性的广泛排队结果，并使它们适应无线网络，并仔细关注PHY模型。利用图论和最优化理论分析对这些算法的性能进行了理论表征，并直观地设计了最优(尽管是集中式)MAC算法。本研究的核心思想融合了传播学、排队论、图论和最优化理论，运用李雅普诺夫函数和流体模型的概念，融入到大学课程中。