A critical point for random graphs with a given degree sequence
Random Graphs 93 Proceedings of the sixth international seminar on Random graphs and probabilistic methods in combinatorics and computer science
Inferring Web communities from link topology
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Trawling the Web for emerging cyber-communities
WWW '99 Proceedings of the eighth international conference on World Wide Web
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Efficient identification of Web communities
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Analysis of the autonomous system network topology
ACM SIGCOMM Computer Communication Review
Network topologies, power laws, and hierarchy
ACM SIGCOMM Computer Communication Review
The Size of the Giant Component of a Random Graph with a Given Degree Sequence
Combinatorics, Probability and Computing
A first-principles approach to understanding the internet's router-level topology
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Does AS size determine degree in as topology?
ACM SIGCOMM Computer Communication Review - Special issue on wireless extensions to the internet
Handling cascading failures: the case for topology-aware fault-tolerance
HotDep'05 Proceedings of the First conference on Hot topics in system dependability
Theoretical Computer Science - Complex networks
Critical Infrastructure Protection
| Hi-index | 0.00 |
It has appeared recently that the underlying degree distribution of networks may play a crucial role concerning their robustness. Previous work insisted on the fact that power-law degree distributions induce high resilience to random failures but high sensitivity to attack strategies, while Poisson degree distributions are quite sensitive in both cases. Then much work has been done to extend these results. We aim here at studying in depth these results, their origin, and limitations. We review in detail previous contributions in a unified framework, and identify the approximations on which these results rely. We then present new results aimed at clarifying some important aspects. We also provide extensive rigorous experiments which help evaluate the relevance of the analytic results. We reach the conclusion that, even if the basic results are clearly important, they are in practice much less striking than generally thought. The differences between random failures and attacks are not so huge and can be explained with simple facts. Likewise, the differences in the behaviors induced by power-law and Poisson distributions are not as striking as often claimed.