On the 1.1 edge-coloring of multigraphs
SIAM Journal on Discrete Mathematics
Improving a family of approximation algorithms to edge color multigraphs
Information Processing Letters
Improved Approximation Algorithms for MAX k-CUT and MAX BISECTION
Proceedings of the 4th International IPCO Conference on Integer Programming and Combinatorial Optimization
The Evolution of Customer Middleware Requirements
PDIS '94 Proceedings of the Third International Conference on Parallel and Distributed Information Systems
Distributed Soft Path Coloring
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Proceedings of the 11th annual international conference on Mobile computing and networking
Approximate graph coloring by semidefinite programming
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
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We consider the following channel assignment problem arising in wireless networks. We are given a graph G= (V, E), and the number of wireless cards Cvfor all v, which limit the number of colors that edges incident to vcan use. We also have the total number of channels CGavailable in the network. For a pair of edges incident to a vertex, they are said to be conflictingif the colors assigned to them are the same. Our goal is to color edges (assign channels) so that the number of conflicts is minimized. We first consider the homogeneous network where Cv= kand CG茂戮驴 Cvfor all nodes v. The problem is NP-hard by a reduction from Edge coloringand we present two combinatorial algorithms for this case. The first algorithm is a distributed greedy method, which gives a solution with at most $(1 - \frac{1}{k})|E|$ more conflicts than the optimal solution. We also present an algorithm yielding at most |V| more conflicts than the optimal solution. The algorithm generalizes Vizing's algorithm in the sense that it gives the same result as Vizing's algorithm when k= Δ+ 1. Moreover, we show that this approximation result is best possible unless P= NP. For the case where Cv= 1 or k, we show that the problem is NP-hard even when Cv= 1 or 2, and CG= 2, and present two algorithms. The first algorithm is completely combinatorial and produces a solution with at most $(2-\frac{1}{k}) OPT + (1 - \frac{1}{k}) |E|$ conflicts. We also develop an SDP-based algorithm, producing a solution with at most 1.122 OPT+ 0.122 |E| conflicts for k= 2, and $(2-\Theta(\frac{\ln k}{k})) OPT + (1 - \Theta(\frac{\ln k}{k}))|E|$ conflicts in general.