Academic Editor: David S. Kung
Copyright © 2009 Logan Rakai et al. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Routing in nanometer
nodes creates an elevated level of importance
for low-congestion routing. At the same time,
advances in mathematical programming have
increased the power to solve complex problems,
such as the routing problem. Hence, new routing
methods need to be developed that can
combine advanced mathematical programming and modeling techniques
to provide low-congestion solutions. In this paper, a hierarchical
mathematical programming-based global routing technique that
considers congestion is proposed. The main contributions presented
in this paper include (i) implementation of congestion estimation
based on actual routing solutions versus purely probabilistic
techniques, (ii) development of a congestion-based hierarchy for
solving the global routing problem, and (iii) generation of a
robust framework for solving the routing problem using
mathematical programming techniques. Experimental results
illustrate that the proposed global router is capable of reducing
congestion and overflow by as much as 36% compared to the
state-of-the-art mathematical programming models.