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Window-Slicing Techniques Extended to Spanning-Event Streams

Authors: Aurélie Suzanne, Guillaume Raschia, José Martinez, and Damien Tassetti

Published in: LIPIcs, Volume 178, 27th International Symposium on Temporal Representation and Reasoning (TIME 2020)


Abstract
Streaming systems often use slices to share computation costs among overlapping windows. However they are limited to instantaneous events where only one point represents the event. Here, we extend streams to events that come with a duration, denoted as spanning events. After a short review of the new constraints ensued by event lifespan in a temporal sliding-window context, we propose a new structure for dealing with slices in such an environment, and prove that our technique is both correct and effective to deal with such spanning events.

Cite as

Aurélie Suzanne, Guillaume Raschia, José Martinez, and Damien Tassetti. Window-Slicing Techniques Extended to Spanning-Event Streams. In 27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 10:1-10:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{suzanne_et_al:LIPIcs.TIME.2020.10,
  author =	{Suzanne, Aur\'{e}lie and Raschia, Guillaume and Martinez, Jos\'{e} and Tassetti, Damien},
  title =	{{Window-Slicing Techniques Extended to Spanning-Event Streams}},
  booktitle =	{27th International Symposium on Temporal Representation and Reasoning (TIME 2020)},
  pages =	{10:1--10:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-167-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{178},
  editor =	{Mu\~{n}oz-Velasco, Emilio and Ozaki, Ana and Theobald, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2020.10},
  URN =		{urn:nbn:de:0030-drops-129783},
  doi =		{10.4230/LIPIcs.TIME.2020.10},
  annote =	{Keywords: Data Stream, Spanning-events, Temporal Aggregates, Sliding Windows}
}
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