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

通信网络的发展极大地增加了信息的可用性，提高了生产力。要继续从连接中获益，一个关键要求是普及无线网络的增长。无线网络是资源受限的，主要是由于其广播性质。缓解这一限制需要一个有效的，分布式的解决方案，媒体访问控制（MAC）的问题。在这个项目中，研究人员研究“本地最优调度和PHY适配”，通过将物理层（PHY）模型纳入最大调度以提高准确性，并采用优先级机制以提高效率。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。这项研究的结果，这是培养研究生博士，通过适当的出版物和研讨会传播，以指导未来无线网络MAC协议的发展，并纳入大学？一般自组织无线网络中的PHY适配和调度（MAC）是NP难问题，特别是如果期望分布式解决方案。在这个项目中，研究人员研究局部最优算法，最大调度的推广，使用广泛的排队结果，证明稳定性，并使其适应无线网络，仔细注意物理层模型。这些算法的性能的理论表征进行了使用图论和优化理论分析，沿着与直觉上的最佳（虽然，集中式）MAC算法的设计。本研究的关键思想，这是在通信理论，排队论，图论和优化的交叉点，被纳入大学课程，使用的概念，李雅普诺夫函数和流体模型。

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.