Robert E. Kooij

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The influence of the network characteristics on the virus spread is analyzed in a new--the <i>N</i>-intertwined Markov chain--model, whose only approximation lies in the application of mean field theory. The mean field approximation is quantified in detail. The <i>N</i>-intertwined model has been compared with the exact 2<sup><i>N</i></sup>-state Markov(More)
This paper describes the development of an end-to-end quality measurement method that allows us to quantify the perceived quality of Interactive Gaming, with an emphasis on the so-called First Person Shooter (FPS) game Quake IV. We conducted a number of subjective experiments to quantify the impact of network parameters on the perceived quality of this(More)
Quality of Experience (QoE) relates to how users perceive the quality of an application. To capture such a subjective measure, either by subjective tests or via objective tools, is an art on its own. Given the importance of measuring users’ satisfaction to service providers, research on QoE took flight in recent years. In this paper we present an overview(More)
The end user experience of service quality is critical to the success of a service provider’s IPTV deployment program. A key element involved in validating IPTV quality of experience (QoE) is how quickly and reliably users can change TV channels, often referred to as channel zapping. Currently there is no knowledge about the explicit relation between(More)
The robustness of smart grids is challenged by unpredictable power peaks or temporal demand oscillations that can cause blackouts and increase supply costs. Planning of demand can mitigate these effects and increase robustness. However, the impact on consumers in regards to the discomfort they experience as a result of improving robustness is usually(More)
Network robustness research aims at finding a measure to quantify network robustness. Once such a measure has been established, we will be able to compare networks, to improve existing networks and to design new networks that are able to continue to perform well when it is subject to failures or attacks. In this paper we survey a large amount of robustness(More)
The robustness of a network is depending on the type of attack we are considering. In this paper we focus on the spread of viruses on networks. It is common practice to use the epidemic threshold as a measure for robustness. Because the epidemic threshold is inversely proportional to the largest eigenvalue of the adjacency matrix, it seems easy to compare(More)