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This paper proposes a new prediction process to explain and predict popularity evolution of YouTube videos. We exploit our recent study on the classification of YouTube videos in order to predict the evolution of videos' view-count. This classification allows to identify important factors of the observed popularity dynamics. Our experimental results show that our prediction process is able to reduce the average prediction errors compared to a state-of-the-art baseline model. We also evaluate the impact of adding popularity criteria in our classification., Paper withdrawn due to conflict of interest in conference call for paper

The goal of this paper is to study the behaviour of view-count in YouTube. We first propose several bio-inspired models for the evolution of the view-count of YouTube videos. We show, using a large set of empirical data, that the view-count for 90% of videos in YouTube can indeed be associated to at least one of these models, with a Mean Error which does not exceed 5%. We derive automatic ways of classifying the view-count curve into one of these models and of extracting the most suitable parameters of the model. We study empirically the impact of videos' popularity and category on the evolution of its view-count. We finally use the above classification along with the automatic parameters extraction in order to predict the evolution of videos' view-count., Technical report, 10 pages. Added MER definition analysis. Added interval confidence intervals. Added prediction results

In this paper we study the capacity of wireless cellular network, in particular the uplink of WCDMA system by using the two dimensional continuous-time Markov chain (CTMC) technique. Considering two types of calls: real-time (RT) calls that characterized by a quasi fixed transmission rate, and best-effort (BE) calls which do not require strict demand but need some reliability conditions. We develop an approach based on the spectral analysis for evaluating the cell capacity. We explicitly obtain the simultaneous distribution of the number of RT connections and the number of BE connections in the steady-state. This analysis allows us to simplify the computation of the performance measures including expected delay and throughput of BE traffic. These performances are obtained explicitly in both cases (finite and infinite) of BE calls as function of system parameters like arrival rate of BE and RT calls, service rate of BE and RT calls. These results allow the operator to evaluate the cell capacity by varying these parameters independently of the number of BE calls according to its policy to manage the network. Note that this analysis can be applied to various systems such as WiMAX/HSPA, and for both uplink and downlink scenarios, so our spectral analysis approach is not only applicable to the uplink of WCDMA system. We further propose some CAC (Call admission control) policies for BE traffic. We finally conclude this work by some numerical and simulation results. The simulation results obtained by the network simulator (NS2) are closely to the numerical results of our analytical results which validate our theoretical model.

International audience; The first version of WiMAX, for fixed broadband access in the 10-66 GHz range, began in 1998 and was completed in October 2001. It was amended in version 802.16a for the 2-11 GHz bandwidth in January 2004, brought some enhancements in the uplink. Version 802.16e mainly concerns mobility and asymmetric links

International audience; We consider a WCDMA system with two types of calls: real time (RT) calls that have dedicated resources, and data on real time (BE) calls (i.e. best effort) that share system capacity. We consider reservation of some capacity resources for the BE traffic as well as any capacity left over from RT calls. Our analysis approach is based on modeling of the system as a two dimensional Markov chain, where the first correspond to the number of RT calls and the second to the number of BE calls in the system. In order obtain the steady state distribution of this system, we use a singular perturbation solution approach for approximating the steady state. Our approach gives a good approximation and relatively faster computation in comparison with our exact methods like spectral analysis [17]. Based on this analysis, we derive performance evaluation results regarding blocking of RT calls and sojourn time of BE calls, under different traffic characteristics. Finally, we extend our result to cover BE admission control. Here, we find the maximum BE arrival rate such that the sojourn time of BE calls not exceed a threshold.