1,720,999 research outputs found

    GTVS: Boosting the Collection of Application Traffic Ground Truth

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    Interesting research in the areas of traffic classification, network monitoring, and application-oriented analysis can not proceed without real traffic traces, labeled with actual application information. However, hand-labeled traces are an extremely valuable but scarce resource in the traffic monitoring and analysis community, as a result of both privacy concerns and technical difficulties. Hardly any possibility exists for payloaded data to be released, while the impossibility of obtaining certain ground-truth application information from non-payloaded data has severely constrained the value of anonymized public traces. The usual way to obtain the ground truth is fragile, inefficient and not directly comparable from one,s work to another. This paper proposes a methodology and details the design of a technical framework that significantly boosts the efficiency in compiling the application traffic ground truth. Further, a case study on a 30 minute real data trace is presented. In contrast with past work, this is an easy hands-on tool suite dedicated to save user,s time and labor and is freely available to the publi

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

    Characterizing the network behavior of P2P traffic

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    Nowadays the majority of Internet traffic is generated by peer-to-peer (P2P) file sharing applications. As the popularity of these applications has been increasing dramatically over the past few years, it becomes increasingly important to analyze their behavior and to understand their effects on the network. The ability to quantify their impact on the network is fundamental to a number of network operations, including traffic engineering, capacity planning, quality of service, forecasting for long-term provisioning, etc. We present here a measurement study on the characteristics of the traffic associated with two different P2P applications. Our aim is to provide useful insight into the nature of P2P traffic from the point of view of the network. To achieve this, we introduce a novel meauserement, Content Transfer Index (CTI), to distinguish two classes of behavior associated with P2P traffic: the download and the signaling traffic profile. Next we apply the CTI to our data sets and show that it effectively offers a general characterization of P2P traffic. Finally, we present a number of statistical measurements that are significantly unbiased due to having considered the distinction between the two classes. To the best of our knowledge, this is the first study to follow this approach. We believe such a study will help researchers better understand the impact of P2P applications on the network and how to improve their performance

    Efficient application identification and the temporaland spatial stability of classification schema

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    Motivated by the importance of accurate identification for a range of applications, this paper compares and contrasts the effective and efficient classification of network-based applications using behavioral observations of network-traffic and those using deep-packet inspection. Importantly, throughout our work we are able to make comparison with data possessing an accurate, independently determined ground-truth that describes the actual applications causing the network-traffic observed. In a unique study in both the spatial-domain: comparing across different network-locations and in the temporal-domain: comparing across a number of years of data, we illustrate the decay in classification accuracy across a range of application–classification mechanisms. Further, we document the accuracy of spatial classification without training data possessing spatial diversity. Finally, we illustrate the classification of UDP traffic. We use the same classification approach for both stateful flows (TCP) and stateless flows based upon UDP. Importantly, we demonstrate high levels of accuracy: greater than 92% for the worst circumstance regardless of the application

    Variations on the Author

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    “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

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    We 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

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    We 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

    Author Index

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