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.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
0831852
Program Officer
Joseph Lyles
Project Start
Project End
Budget Start
2008-09-01
Budget End
2012-08-31
Support Year
Fiscal Year
2008
Total Cost
$330,000
Indirect Cost
Name
George Washington University
Department
Type
DUNS #
City
Washington
State
DC
Country
United States
Zip Code
20052