A self-stabilizing algorithm for coloring bipartite graphs
Information Sciences: an International Journal
Self-stabilizing Neighborhood Unique Naming under Unfair Scheduler
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Linear time self-stabilizing colorings
Information Processing Letters
A self-stabilizing algorithm for coloring planar graphs
Distributed Computing - Special issue: Self-stabilization
A self-stabilizing (Δ+4)-edge-coloring algorithm for planar graphs in anonymous uniform systems
Information Processing Letters
Optimal deterministic self-stabilizing vertex coloring in unidirectional anonymous networks
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Self-stabilizing coloration in anonymous planar networks
Information Processing Letters
A self-stabilizing algorithm for the minimum color sum of a graph
ICDCN'08 Proceedings of the 9th international conference on Distributed computing and networking
Probabilistic self-stabilizing vertex coloring in unidirectional anonymous networks
ICDCN'10 Proceedings of the 11th international conference on Distributed computing and networking
Self-stabilizing algorithms for graph coloring with improved performance guarantees
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Efficient self-stabilizing algorithms for minimal total k-dominating sets in graphs
Information Processing Letters
| Hi-index | 5.23 |
The problem of assigning frequencies to processes so as to avoid interference can in many instances be modeled as a graph coloring problem on the processor graph where no two processes that are sufficiently close are assigned the same color. One version of this problem requires that processes within distance two of each other have different colors. This is known as the distance-2 coloring problem. We present a self-stabilizing algorithm for this problem that uses O(log@D) memory on each node and that stabilizes in O(@D^2m) time steps for any scheduler (synchronous or asynchronous) using at most @D^2+1 colors, where @D is the maximum degree in the graph and m is the number of edges in the graph. The analysis holds true for both the sequential and distributed adversarial daemon models. This should be compared with the previous best self-stabilizing algorithm for this problem which stabilizes in O(nm) moves under the sequential adversarial daemon and in O(n^3m) time steps for the distributed adversarial daemon and which uses O(@d"ilog@D) memory on each node i, where n is the number of nodes in the graph and @d"i is the degree of node i.