Name
Title | ||
|---|---|---|
Epidemic survivability: Characterizing networks under epidemic-like failure propagation scenarios |
Abstract | ||
|---|---|---|
Epidemics theory has been used in different contexts in order to describe the propagation of diseases, human interactions or natural phenomena. In computer science, virus spreading has been also characterized using epidemic models. Although in the past the use of epidemic models in telecommunication networks has not been extensively considered, nowadays, with the increasing computation capacity and complexity of operating systems of modern network devices (routers, switches, etc.), the study of possible epidemic-like failure scenarios must be taken into account. When epidemics occur, such as in other multiple failure scenarios, identifying the level of vulnerability offered by a network is one of the main challenges. In this paper, we present epidemic survivability, a new network measure that describes the vulnerability of each node of a network under a specific epidemic intensity. Moreover, this metric is able to identify the set of nodes which are more vulnerable under an epidemic attack. In addition, two applications of epidemic survivability are provided. First, we introduce epidemic criticality, a novel robustness metric for epidemic failure scenarios. A case study shows the utility of this new metric comparing several network topologies and epidemic intensities. Then, two immunization strategies are proposed: high epidemic survivability (HES) and high epidemic survivability adaptive (HESA). The presented results show that network vulnerability can be significantly reduced by using our proposals, compared to other well-known existing methods. |
Year | Venue | Keywords |
|---|---|---|
2013 | DRCN | epidemic attack,operating systems,immunization strategy,epidemic criticality,telecommunication networks,epidemic failure scenarios,robustness metric,telecommunication network reliability,network topology,network vulnerability,natural phenomena,telecommunication network topology,immunization,epidemics theory,computation complexity,human interactions,disease propagation,epidemic intensity,network characterization,robustness metrics,computation capacity,epidemic models,epidemics,epidemic-like failure propagation scenarios,virus spreading,multiple failures,network devices,computer science,high epidemic survivability adaptive,hesa,epidemic-like failure scenarios,robustness,topology,measurement,mathematical model |
Field | DocType | ISSN |
Survivability,Computer science,Networking hardware,Computer network,Network topology,Robustness (computer science),Telecommunication network reliability,Distributed computing,Vulnerability | Conference | 2639-2313 |
ISBN | Citations | PageRank |
978-1-4799-0049-7 | 3 | 0.40 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Manzano | 1 | 68 | 9.45 |
| Eusebi Calle | 2 | 127 | 15.59 |
| Jordi Ripoll | 3 | 13 | 1.84 |
| Anna Manolova Fagertun | 4 | 17 | 5.15 |
| victor torrespadrosa | 5 | 13 | 4.59 |