Modeling the effects of timing parameters on virus propagation
Proceedings of the 2003 ACM workshop on Rapid malcode
Evolution and Structure of the Internet: A Statistical Physics Approach
Evolution and Structure of the Internet: A Statistical Physics Approach
Performance Analysis of Communications Networks and Systems
Performance Analysis of Communications Networks and Systems
A New Metric for Robustness with Respect to Virus Spread
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
Comparing two newly proposed immunization strategies in networks
APCC'09 Proceedings of the 15th Asia-Pacific conference on Communications
Modeling gossip-based content dissemination and search in distributed networking
Computer Communications
Does more connectivity help groups to solve social problems
Proceedings of the 12th ACM conference on Electronic commerce
Epidemic spread in mobile Ad Hoc networks: determining the tipping point
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
The viral conductance of a network
Computer Communications
Degree and principal eigenvectors in complex networks
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part I
Bio-inspired strategy for control of viral spreading in networks
Proceedings of the 2nd ACM international conference on High confidence networked systems
Moment-based spectral analysis of large-scale networks using local structural information
IEEE/ACM Transactions on Networking (TON)
Generalized epidemic mean-field model for spreading processes over multilayer complex networks
IEEE/ACM Transactions on Networking (TON)
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The influence of the network characteristics on the virus spread is analyzed in a new--the N-intertwined Markov chain--model, whose only approximation lies in the application of mean field theory. The mean field approximation is quantified in detail. The N-intertwined model has been compared with the exact 2N-state Markov model and with previously proposed "homogeneous" or "local" models. The sharp epidemic threshold τc, which is a consequence of mean field theory, is rigorously shown to be equal to τc = 1/(λmax (A)), where λmax (A) is the largest eigenvalue--the spectral radius--of the adjacency matrix A. A continued fraction expansion of the steady-state infection probability at node j is presented as well as several upper bounds.