Throughput Optimization of Urban Wireless Mesh Networks
Abstract
Interference and collisions greatly limit the throughput of mesh networks that used contention-based MAC protocols such as 802.11. It is widely believed that significantly higher throughput is achievable if transmissions are scheduled. However, since the typical approach to this throughput optimization requires optimizing over a space that is exponential in the number of links, the optimal throughput has appeared to be computationally intractable for all but small networks. This research presents techniques that are typically able to efficiently compute optimal schedules as well as optimal routing. The technique consists of three layers of optimization. The inner-most optimization computes an estimate of the throughput. This optimization is a standard linear or nonlinear constrained optimization, depending on the objective function. The middle iteration uses the Lagrange multipliers from the inner-most optimization to modify the space over which inner-most optimization is performed. This is a graph theoretic optimization known as the maximum weighted independent set (MWIS) problem. The solvability of this problem is extensively studied, and the empirical evidence shows that usually MWIS arising from wireless mesh network can be solved quickly. The outer-most optimization uses the Lagrange multipliers from the inner-most optimization to find optimal routes. This optimization solves several least cost paths problems and several maximum weighted independent set problems. Together, these techniques allow optimal schedules to be computed for networks with hundreds and even a few thousand links, and allow optimal routes to be computed for networks with a few hundred links. Thus, the approach scales to the size of current and planned urban mesh networks. The techniques have been verified on networks generated with a realistic urban propagation simulator.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2008
- Accession Number
- AD1000178
Entities
People
- Peng Wang
Organizations
- University of Delaware