1,721,157 research outputs found

    QoE for Interactive Services in 5G Networks: Data-driven Analysis and ML-based Prediction

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    Nowadays, the focus in 5G networks has shifted from Quality of Service (QoS) to Quality of Experience (QoE) characterisation and prediction. As a matter of fact, mobile operators are increasingly interested in measuring and/or predicting QoE Key Performance Indicators (KPIs) on their 5G networks. In this context, a recent methodology by the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) allows to characterize the level of interactivity achievable by real-time services on 5G networks, by computing a synthetic QoE KPI referred to as interactivity score (i-score). The i-score, defined as the measurable latency, continuity, and reliability of a given service, is computed by using a model that takes into account three QoS KPIs, i.e., packet trip time, jitter, and loss rate. In this paper, aiming at assessing the effectiveness of the ITU-T methodology in characterizing 5G network performance, we analyze a large-scale measurement campaign executed over two commercial 5G Non-Standalone (NSA) deployments in the city of Rome, Italy. During this campaign, traces related to radio coverage and service performance (i.e., the i-score and corresponding KPIs needed to compute it) were collected in parallel. Therefore, we use the dataset to characterize the observed i-score performance, and demonstrate that it is possible to successfully predict this KPI with machine learning techniques, using radio layer parameters and power measurements. Mobile operators could take advantage of our findings, minimizing the need for time/resource-consuming QoE tests. Ensemble methods in fact achieve an accuracy spanning from 0.79 to 0.83, with Random Forest as one of the best algorithm to predict the i-score from radio layer parameters.</p

    How Ready is DNS for an IPv6-Only World?

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    DNS is one of the core building blocks of the Internet. In this paper, we investigate DNS resolution in a strict IPv6-only scenario and find that a substantial fraction of zones cannot be resolved. We point out, that the presence of an AAAA resource record for a zone’s nameserver does not necessarily imply that it is resolvable in an IPv6-only environment since the full DNS delegation chain must resolve via IPv6 as well. Hence, in an IPv6-only setting zones may experience an effect similar to what is commonly referred to as lame delegation. Our longitudinal study shows that the continuing centralization of the Internet has a large impact on IPv6 readiness, i.e., a small number of large DNS providers has, and still can, influence IPv6 readiness for a large number of zones. A single operator that enabled IPv6 DNS resolution–by adding IPv6 glue records–was responsible for around 20.3% of all zones in our dataset not resolving over IPv6 until January 2017. Even today, 10% of DNS operators are responsible for more than 97.5% of all zones that do not resolve using IPv6.Organisation & Governanc

    Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets

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    Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our ‘Back-to-the-Future whois’ service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.Organisation & GovernanceInformation and Communication Technolog

    Intercept and Inject: DNS Response Manipulation in the Wild

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    DNS is a protocol responsible for translating human-readable domain names into IP addresses. Despite being essential for many Internet services to work properly, it is inherently vulnerable to manipulation. In November 2021, users from Mexico received bogus DNS responses when resolving whatsapp.net. It appeared that a BGP route leak diverged DNS queries to the local instance of the k-root located in China. Those queries, in turn, encountered middleboxes that injected fake DNS responses. In this paper, we analyze that event from the RIPE Atlas point of view and observe that its impact was more significant than initially thought—the Chinese root server instance was reachable from at least 15 countries several months before being reported. We then launch a nine-month longitudinal measurement campaign using RIPE Atlas probes and locate 11 probes outside China reaching the same instance, although this time over IPv6. More broadly, motivated by the November 2021 event, we study the extent of DNS response injection when contacting root servers. While only less than 1% of queries are impacted, they originate from 7% of RIPE Atlas probes in 66 countries. We conclude by discussing several countermeasures that limit the probability of DNS manipulation.Organisation & GovernanceCyber Securit

    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

    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

    Range-free positioning in NB-IoT networks by machine learning

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    Existing proposals for positioning in NB-IoT networks based on range estimation are characterized by either low accuracy or lack of compliance with 3GPP standards. While range-free approaches taking advantage of Machine Learning (ML) have been recently proposed as a potential way forward, their evaluation has been carried out only in simulated environments, with the exception of Weighted k Nearest Neighbours (WkNN), recently tested on experimental data. This work inves-tigates four ML strategies for range-free positioning in NB-IoT networks, based on WkNN and its combination with preprocessing and classification algorithms as well as on Artificial Neural Networks (ANNs). The strategies are evaluated on experimental data and are compared based on a set of Key Performance Indicators (KPIs) measuring both positioning performance and computational complexity. Results show that range-free positioning using ML is a viable solution in commercial NB-IoT networks, and that WkNN and ANNs are at the two extremes in terms of a performance/complexity trade-off; intermediate trade-offs can be achieved by combining WkNN with preprocessing techniques and classification models

    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
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