1,721,254 research outputs found
Joint source and sending rate modeling in adaptive video streaming
No full textThis work addresses the modeling of traffic generated by a video source operating in the context of adaptive streaming services. Traffic modeling is a key in several network design issues, such as dimensioning of core and access network resources, developing pricing procedures, carrying out cost-revenue studies. The actual traffic generated during a video streaming session depends on both the video source and the bandwidth variations imposed by lower communication layers. We propose a new traffic model that jointly encompasses these two effects. Specifically, we consider the modeling of the sequence of frame sizes generated by a video streaming source that dynamically adapts its rate to the available communication channel bandwidth using bitstream switching techniques. In order to represent the source rate adaptation to the random network bandwidth variations on the communication channel, we resort to a framework based on Hidden Markov Processes (HMPs). Our HMP model represents the first joint source and sending rate model in adaptive streaming literature. Thanks to effective modeling assumptions on the frame size probability density function (pdf), the HMP parameters can be estimated by means of the Expectation Maximization algorithm. The traffic model is validated by numerical simulations of a mobile adaptive video streaming scenario. We study the model's ability to predict several traffic statistics, including the traffic load of a video streaming source in different network points. Besides, we evaluate the model accuracy in characterizing aggregate video traffic resulting from multiplexing various video sources. In all experiments, we show that the proposed model is able to accurately capture the traffic characteristics. (c) 2013 Elsevier B.V. All rights reserved
A NON-STATIONARY HIDDEN MARKOV MODEL OF MULTIVIEW VIDEO TRAFFIC
No full textMultiview video is increasingly getting attention due to emerging applications such as 3DTV and immersive teleconferencing. In this paper, we present a non-stationary Hidden Markov Model (HMM) for characterizing the data rate of compressed multiview content. The states of the model correspond to different video activity levels and exhibit a Poisson state duration distribution. We derive a stable maximum likelihood algorithm for estimating the parameters of our multiview traffic model. Synthetic data generated by the model exhibits statistics that closely match those of actual multiview data. In addition, we demonstrate the high accuracy of the model in two multiview streaming applications by evaluating the frame loss rate of a constrained network buffer fed by actual and synthetic data. © 2010 IEEE
A Poisson hidden Markov model for multiview video traffic
Full text linkMultiview video has recently emerged as a means to improve user experience in novel multimedia services. We propose a new stochastic model to characterize the traffic generated by a Multiview Video Coding (MVC) variable bit-rate source. To this aim, we resort to a Poisson hidden Markov model (P-HMM), in which the first (hidden) layer represents the evolution of the video activity and the second layer represents the frame sizes of the multiple encoded views. We propose a method for estimating the model parameters in long MVC sequences. We then present extensive numerical simulations assessing the model's ability to produce traffic with realistic characteristics for a general class of MVC sequences. We then extend our framework to network applications where we show that our model is able to accurately describe the sender and receiver buffers behavior in MVC transmission. Finally, we derive a model of user behavior for interactive view selection, which, in conjunction with our traffic model, is able to accurately predict actual network load in interactive multiview services
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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