Collaborative Research: NEDG: Throughput Optimization in Wireless Mesh Networks

合作研究：NEDG：无线网状网络的吞吐量优化

• 批准号: 0831852
• 负责人: Xiuzhen Cheng
• 金额: $ 33万
• 依托单位: George Washington 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=0831852&HistoricalAwards=false
• 关键词: Collaborative; Research; NEDG; Throughput; Optimization

This collaborative project investigates a number of fundamental problems that are very critical to wireless mesh network (WMN) throughput optimization. Wireless mesh networking is believed to be the most effective and efficient technology for the last-mile data connection to the Internet. The proposed research targets to solve the following challenges: 1) Throughput optimization in MR-MC WMNs: the complexity of throughput-optimal scheduling, real-time logical topology characterization and inference, the joint exploitation of both rate diversity and channel diversity, and game theory based throughput optimization. 2) Non information theory based approaches to throughput optimization in multi-hop MIMO-enabled WMNs: stochastically modeling different aspects of the mesh network, constructing Network Utility Maximization formulations, and applying Information Geometric Programming to solve global optimization problems. 3) Biologically-inspired WMN design for throughput optimizatio n. 4) A testbed to accomplish experimental tasks to validate the effectiveness of the design.This project is in nature multidisciplinary. It requires the joint effort from computer science, electrical engineering, mathematics, statistics, and biology, and therefore has the potential to inspire revolutionary methodologies that could be applied to many domains. In addition, the novelty of the proposed research has strong impact on wireless research. Furthermore, the success of this project is able to enhance the four universities? ability to educate, through the multi-disciplinary research effort, future scientists and engineers.

这个合作项目调查了一些基本问题，是非常关键的无线网状网络（WMN）的吞吐量优化。无线网状网络被认为是最有效和最高效的互联网最后一英里数据连接技术。1）MR-MC WMN的吞吐量优化问题：吞吐量优化调度的复杂性、实时逻辑拓扑描述和推理、速率分集和信道分集的联合利用以及基于博弈论的吞吐量优化。2)基于非信息论的多跳MIMO无线网状网吞吐量优化方法：对网状网络的不同方面进行随机建模，构建网络效用最大化公式，以及应用信息几何规划来解决全局优化问题。3)生物启发的WMN设计，用于吞吐量优化。4)一个测试平台，完成实验任务，以验证设计的有效性。这个项目是在性质上的多学科。它需要计算机科学、电气工程、数学、统计学和生物学的共同努力，因此有可能激发革命性的方法，可以应用于许多领域。此外，所提出的研究的新奇对无线研究有很大的影响。此外，这个项目的成功是能够提高四所大学？通过多学科的研究工作，培养未来的科学家和工程师的能力。