Auflistung Band 42 - Heft 4 (August 2019) nach Titel
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- ZeitschriftenartikelAnmerkungen zum Editorial des Informatik Spektrums 2/2019(Informatik Spektrum: Vol. 42, No. 4, 2019) Hellmig, Lutz; Hartmann, Werner
- ZeitschriftenartikelAuftragsdatenverarbeitung(Informatik Spektrum: Vol. 42, No. 4, 2019) Sury, Ursula
- ZeitschriftenartikelFog Computing(Informatik Spektrum: Vol. 42, No. 4, 2019) Pagel, Peter; Schulte, Stefan
- ZeitschriftenartikelFPGAs im Rechenzentrum(Informatik Spektrum: Vol. 42, No. 4, 2019) Platzner, Marco; Plessl, Christian
- ZeitschriftenartikelGewissensbits – wie würden Sie urteilen?(Informatik Spektrum: Vol. 42, No. 4, 2019) Schmautzer, Jennifer; Trinitis, Carsten
- ZeitschriftenartikelLetzte Rätsel(Informatik Spektrum: Vol. 42, No. 4, 2019) Wilhelm, Reinhard
- ZeitschriftenartikelMitteilungen der Gesellschaft für Informatik / 257. Folge(Informatik Spektrum: Vol. 42, No. 4, 2019) Gesellschaft für Informatik e.V. (GI)
- ZeitschriftenartikelSame-Same But Different: On Understanding Duplicates in Stack Overflow(Informatik Spektrum: Vol. 42, No. 4, 2019) Ellmann, MathiasStack Overflow (SO) is one of the most popular online sites for asking and answering developers’ questions. New posts that cover exactly the same knowledge as previously posted questions get closed and deleted by the community. However, new posts that are very similar to previous questions but which are phrased slightly different are kept and tagged as duplicates: since they might include additional information, hints, or keywords. In this paper, we study exact duplicates and similar duplicates in SO in order to get insights about their properties and content and to understand how the community distinguishes useful from useless (i. e. to be deleted) redundant knowledge. We identified several interesting trends. Unique questions are significantly longer than others. Original questions get answered faster, include more answers, and get more frequently viewed than exact and similar duplicates. When comparing the overlapped text in duplicate pairs, we found almost no difference between exact and similar duplicates. In both cases, about 20–25 % of the question text and 40 % of the tags are identical in an original and its duplicate. However, the answers of the duplicates seem much more diverse with only 5–6 % repeated text.
- ZeitschriftenartikelSituativer Datenschutz im Fog-Computing(Informatik Spektrum: Vol. 42, No. 4, 2019) Mann, Zoltán Ádám; Metzger, Andreas; Pohl, KlausFog-Computing erlaubt, Software-Code oder Daten dynamisch von ressourcenschwachen Endgeräten an leistungsstärkere Geräte am Rande des Netzwerks und in der Cloud auszulagern. Eine solche dynamische Auslagerung ermöglicht eine performante Ausführung rechenintensiver Aufgaben, bei gleichzeitig geringer Latenzzeit für die Datenübertragung. Beim Datenschutz ergeben sich im Fog-Computing jedoch spezifische Herausforderungen. Wir beschreiben die wesentlichen Herausforderungen des Datenschutzes im Fog-Computing und diskutieren, wie diese Herausforderungen durch die situative Kombination verschiedener Datenschutztechniken zur Laufzeit adressiert werden können.
- ZeitschriftenartikelTowards a Framework for Data Stream Processing in the Fog(Informatik Spektrum: Vol. 42, No. 4, 2019) Hießl, Thomas; Hochreiner, Christoph; Schulte, StefanIn volatile data streams as encountered in the Internet of Things (IoT), the data volume to be processed changes permanently. Hence, to ensure timely data processing, there is a need to reconfigure the computational resources used for processing data streams. Up to now, mostly cloud-based computational resources have been utilized for this. However, cloud data centers are usually located far away from IoT data sources, which leads to an increase in latency since data needs to be sent from the data sources to the cloud and back. With the advent of fog computing, it is possible to perform data processing in the cloud as well as at the edge of the network, i. e., by exploiting the computational resources offered by networked devices. This leads to decreased latency and a lower communication overhead. Despite this, there is currently a lack of approaches to data stream processing which explicitly exploit the computational resources available in the fog.