An incremental linear-time algorithm for recognizing interval graphs
SIAM Journal on Computing
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Variable Heavy Tailed Durations in Internet Traffic, Part I: Understanding Heavy Tails
MASCOTS '02 Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Interval Completion Is Fixed Parameter Tractable
SIAM Journal on Computing
Subexponential interval graphs generated by immigration–death processes
Probability in the Engineering and Informational Sciences
| Hi-index | 5.23 |
Scale free graphs have attracted attention by their non-uniform structure that can be used as a model for various social and physical networks. In this paper, we propose a natural and simple random model for generating scale free interval graphs. The model generates a set of intervals randomly under a certain distribution, which defines a random interval graph. The main advantage of the model is its simpleness. The structure/properties of generated graphs are analyzable by relatively simple probabilistic and/or combinatorial arguments, which is different from many other models. Based on such arguments, we show for our random interval graph that its degree distribution follows a power law, and that it has a large average clustering coefficient.