Artikel in Tagungsband INPROC-2013-29

Bibliograph.
Daten
Hong, Kirak; Lillethun, David; Ramachandran, Umakishore; Ottenwälder, Beate; Koldehofe, Boris: Opportunistic Spatio-temporal Event Processing for Mobile Situation Awareness.
In: Proceedings of the 7th ACM International Conference on Distributed Event-Based Systems (DEBS).
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 195-206, englisch.
Arlington, Texas, USA: ACM Press, 27. Juni 2013.
DOI: 10.1145/2488222.2488266.
Artikel in Tagungsband (Konferenz-Beitrag).
CR-Klassif.C.2.1 (Network Architecture and Design)
C.2.4 (Distributed Systems)
Keywordsmobility; complex event processing; situation awareness
Kurzfassung

With the proliferation of mobile devices and sensors, mobile situation awareness is becoming an important class of applications. The key requirement of this class of applications is low-latency processing of events stemming from sensordata in order to provide timely situational information to mobile users.To satisfy the latency requirement, we propose a spatio-temporal event processing system that uses prediction-based continuous query handling. Our system predicts future query regions for moving consumers and starts processing events early so that the live situational information is available when the consumer reaches the future location. In contrast to existing systems, our system provides timely information about a consumer's current position by hiding computation latency for processing recent events. To evaluate our system, we measure the quality of results and timeliness of live situational information with various query parameters. Our evaluation shows that we can achieve highly meaningful query results with near-zero latency in most cases.

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Copyright© ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 7th ACM International Conference on Distributed Event-Based Systems, Arlington, Texas, USA, 2013. http://doi.acm.org/10.1145/2488222.2488266
Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Verteilte Systeme
Projekt(e)CEPiL
Eingabedatum5. Juni 2013
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