Searched for: author%3A%22Van+de+Bovenkamp%2C+R.%22
(1 - 16 of 16)
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Jia, L. (author), Shen, S. (author), van de Bovenkamp, R. (author), Iosup, A. (author), Kuipers, F.A. (author), Epema, D.H.J. (author)
Multiplayer Online Games (MOGs) like Defense of the Ancients and StarCraft II have attracted hundreds of millions of users who communicate, interact, and socialize with each other through gaming. In MOGs, rich social relationships emerge and can be used to improve gaming services such as match recommendation and game population retention, which...
journal article 2015
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Van de Bovenkamp, R. (author), Van Mieghem, P. (author)
The survival time T is the longest time that a virus, a meme, or a failure can propagate in a network. Using the hitting time of the absorbing state in an uniformized embedded Markov chain of the continuous-time susceptible-infected-susceptible (SIS) Markov process, we derive an exact expression for the average survival time E[T ] of a virus in...
journal article 2015
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Van Mieghem, P.F.A. (author), Van de Bovenkamp, R. (author)
Mean-field approximations (MFAs) are frequently used in physics. When a process (such as an epidemic or a synchronization) on a network is approximated by MFA, a major hurdle is the determination of those graphs for which MFA is reasonably accurate. Here, we present an accuracy criterion for Markovian susceptible-infected-susceptible (SIS)...
journal article 2015
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Van de Bovenkamp, R. (author)
Local interactions on a graph will lead to global dynamic behaviour. In this thesis we focus on two types of dynamic processes on graphs: the Susceptible-Infected-Susceptilbe (SIS) virus spreading model, and gossip style epidemic algorithms. The largest part of this thesis is devoted to the SIS model. We first introduce the SIS model in chapter...
doctoral thesis 2015
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Van de Bovenkamp, R. (author), Kuipers, F.A. (author), Van Mieghem, P.F.A. (author)
When two viruses compete for healthy nodes in a simple network and both spreading rates are above the epidemic threshold, only one virus will survive. However, if we prevent the viruses from dying out, rich dynamics emerge. When both viruses are identical, one virus always dominates the other, but the dominating and dominated virus alternate. We...
journal article 2014
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Iosup, A. (author), van de Bovenkamp, R. (author), Shen, S. (author), Jia, L. (author), Kuipers, F.A. (author)
journal article 2014
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van de Bovenkamp, R. (author), Kuipers, F.A. (author), Van Mieghem, P.F.A. (author)
journal article 2014
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Guo, D. (author), Trajanovski, S. (author), Van de Bovenkamp, R. (author), Wang, H. (author), Van Mieghem, P.F.A. (author)
The interplay between disease dynamics on a network and the dynamics of the structure of that network characterizes many real-world systems of contacts. A continuous-time adaptive susceptible-infectious-susceptible (ASIS) model is introduced in order to investigate this interaction, where a susceptible node avoids infections by breaking its...
journal article 2013
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Cator, E. (author), Van de Bovenkamp, R. (author), Van Mieghem, P.F.A. (author)
The classical, continuous-time susceptible-infected-susceptible (SIS) Markov epidemic model on an arbitrary network is extended to incorporate infection and curing or recovery times each characterized by a general distribution (rather than an exponential distribution as in Markov processes). This extension, called the generalized SIS (GSIS)...
journal article 2013
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Van Mieghem, P.F.A. (author), Van de Bovenkamp, R. (author)
Most studies on susceptible-infected-susceptible epidemics in networks implicitly assume Markovian behavior: the time to infect a direct neighbor is exponentially distributed. Much effort so far has been devoted to characterize and precisely compute the epidemic threshold in susceptible-infected-susceptible Markovian epidemics on networks. Here,...
journal article 2013
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van de Bovenkamp, R. (author), Kuipers, F.A. (author)
conference paper 2013
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van de Bovenkamp, R. (author), Shen, J. (author), Iosup, A. (author), Kuipers, F.A. (author)
conference paper 2013
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Li, C. (author), Van de Bovenkamp, R. (author), Van Mieghem, P.F.A. (author)
We introduce the ?-susceptible-infected-susceptible (SIS) spreading model, which is taken as a benchmark for the comparison between the N-intertwined approximation and the Pastor-Satorras and Vespignani heterogeneous mean-field (HMF) approximation of the SIS model. The N-intertwined approximation, the HMF approximation, and the ?-SIS spreading...
journal article 2012
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Van de Bovenkamp, R. (author), Kuipers, F. (author), Van Mieghem, P. (author)
We propose Gossipico, a gossip algorithm to average, sum or find minima and maxima over node values in a large, distributed, and dynamic network. Unlike previous work, Gossipico provides a continuous estimate of, for example, the number of nodes, even when the network becomes disconnected. Gossipico converges quickly due to the introduction of a...
conference paper 2012
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Van Mieghem, P. (author), Stevanovi?, D. (author), Kuipers, F. (author), Li, C. (author), Van de Bovenkamp, R. (author), Liu, D. (author), Wang, H. (author)
The decrease of the spectral radius, an important characterizer of network dynamics, by removing links is investigated. The minimization of the spectral radius by removing m links is shown to be an NP-complete problem, which suggests considering heuristic strategies. Several greedy strategies are compared, and several bounds on the decrease of...
journal article 2011
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Van Mieghem, P.F.A. (author), Stevanovic, D (author), Kuipers, F.A. (author), Li, C. (author), van de Bovenkamp, R. (author), Liu, D. (author), Wang, H. (author)
journal article 2011
Searched for: author%3A%22Van+de+Bovenkamp%2C+R.%22
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