Name
Title | ||
|---|---|---|
An accurate generic model to measure of robustness and fragility of networks to random breakdowns. |
Abstract | ||
|---|---|---|
Previous attentions on the resilience of random graphs, P2P, and real-life networks have been restricted to approximately find the disconnection probability or they required the computation of NP-complete metrics and also no closed-form solution was available even for the basic networks. Our objective, in this paper, is to highlight the disconnection probability which can arise in such networks. We study the resilience of exponential and real-life networks to the random removal of individual nodes, using an accurate analytical model calculating the exact probability of various networks disconnection facing the malfunctions or local failures which lead to the loss of the global information-carrying ability of these networks. This model is generic and can provide more complete characterisation of the networks robustness. To validate our model and method, we performed sufficient results of Monte-Carlo simulation method and presented an analysis of the effects of the disconnection phenomenon on the overall ne... |
Year | Venue | Field |
|---|---|---|
2016 | IJMNO | Graph theory,Psychological resilience,Mathematical optimization,Random graph,Computer science,Robustness (computer science),Fault tolerance,Artificial intelligence,Reliability (computer networking),Disconnection,Machine learning,Computation |
DocType | Volume | Issue |
Journal | 7 | 2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farshad Safaei | 1 | 95 | 19.37 |
| Hamidreza Sotoodeh | 2 | 1 | 1.36 |