NeTS:Small:Collaborative Research: Effective control of wireless networks via topology adaptation and randomization

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。无线网状网络已经成为提供最后一英里互联网接入的解决方案。通过利用先进的通信技术，他们可以实现非常高的速率。然而，有效地控制这些网络，特别是在先进的物理层技术、信道干扰的现实模型和分布式操作的背景下，仍然是一个主要的挑战。因此，该项目致力于开发有效实用的网络控制算法，通过联合拓扑自适应、网络层路由、MAC层调度以及物理层功率、信道和速率控制，有效利用无线资源。算法的设计利用了动态系统控制和随机算法的最新发展，并考虑了现实的通道模型。这包括:(1)拓扑自适应算法，利用信道分配、功率控制和部分节点的可控移动能力，将网络动态分解为子网，保证低复杂度的分布式调度和路由算法实现高吞吐量；（ii）仅使用局部拓扑和队列大小信息以计算效率的方式解决调度和路由问题的随机分布式算法，以及（iii）算法的评估？吞吐量、延迟和复杂性方面的性能。开发的算法将使无线网络的高效运行成为可能。该项目包括培训研究生和本科生，向当地高中教师开展拓展活动，以及向工业和政府实验室转让技术。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Wireless Mesh Networks have emerged as a solution for providing last-mile Internet access. By exploiting advanced communication technologies, they can achieve very high rates. However, effectively controlling these networks, especially in the context of advanced physical layer technologies, realistic models for channel interference, and distributed operation, remains a major challenge. Hence, the project focuses on developing effective and practical network control algorithms that make efficient use of wireless resources through joint topology adaptation, network layer routing, MAC layer scheduling, and physical layer power, channel, and rate control. The design of the algorithms leverages recent developments in the control of dynamical systems and randomized algorithms, and takes into account realistic channel models. This includes: (i) topology adaptation algorithms that take advantage of channel allocation, power control, and the controlled mobility capabilities of some of the nodes to dynamically decompose the network into sub-networks in which low-complexity distributed scheduling and routing algorithms are guaranteed to achieve high throughput, (ii) randomized distributed algorithms that solve the scheduling and routing problems in a computationally efficient manner using only local topological and queue size information, and (iii) evaluation of the algorithms? performance in terms of throughput, delay, and complexity. The developed algorithms will enable highly efficient operation of wireless networks. The project incorporates training of graduate and undergraduate students, outreach activities to local high-school teachers, and technology transfer to industry and government laboratories.