K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases

@misc{citeulike:2829595, abstract = {We consider the \$k\$-core decomposition of network models and Internet graphs at the autonomous system (AS) level. The \$k\$-core analysis allows to characterize networks beyond the degree distribution and uncover structural properties and hierarchies due to the specific architecture of the system. We compare the \$k\$-core structure obtained for AS graphs with those of several network models and discuss the differences and similarities with the real Internet architecture. The presence of biases and the incompleteness of the real maps are discussed and their effect on the \$k\$-core analysis is assessed with numerical experiments simulating biased exploration on a wide range of network models. We find that the \$k\$-core analysis provides an interesting characterization of the fluctuations and incompleteness of maps as well as information helping to discriminate the original underlying structure.}, author = {Alvarez-Hamelin, Jos\&\#xe9; I. and Dall\&\#x27;asta, Luca and Barrat, Alain and Vespignani, Alessandro }, citeulike-article-id = {2829595}, eprint = {cs/0511007}, month = {Apr}, posted-at = {2008-05-30 12:36:26}, priority = {2}, title = {K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases}, url = {http://arxiv.org/abs/cs/0511007}, year = {2008} }

TY - ELEC ID - citeulike:2829595 L3 - citeulike-article-id:2829595 TI - K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases N2 - We consider the $k$-core decomposition of network models and Internet graphs at the autonomous system (AS) level. The $k$-core analysis allows to characterize networks beyond the degree distribution and uncover structural properties and hierarchies due to the specific architecture of the system. We compare the $k$-core structure obtained for AS graphs with those of several network models and discuss the differences and similarities with the real Internet architecture. The presence of biases and the incompleteness of the real maps are discussed and their effect on the $k$-core analysis is assessed with numerical experiments simulating biased exploration on a wide range of network models. We find that the $k$-core analysis provides an interesting characterization of the fluctuations and incompleteness of maps as well as information helping to discriminate the original underlying structure. AU - Alvarez-Hamelin, José AU - Dall'asta, Luca AU - Barrat, Alain AU - Vespignani, Alessandro PY - 2008/Apr/16/ UR - http://arxiv.org/abs/cs/0511007 ER -