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Quality matters: supporting quality-aware pervasive applications by probabilistic data stream management

Authors:

Christian Kuka,

Daniela NicklasAuthors Info & Claims

DEBS '14: Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems

Pages 1 - 12

https://doi.org/10.1145/2611286.2611292

Published: 26 May 2014 Publication History

Abstract

Many pervasive computing applications need sensor data streams, which can vary significantly in accuracy. Depending on the application, deriving information (e.g., higher-level context) from low-quality sensor data might lead to wrong decisions or even critical situations. Thus, it is important to control the quality throughout the whole data stream processing, from the raw sensor data up to the derived information, e.g., a complex event. In this paper, we present a uniform meta data model to represent sensor data and information quality at all levels of processing; we show how this meta data model can be integrated in a data stream processing engine to ease the development of quality-aware applications; and we present an approach to learn probability distributions of incoming sensor data which needs no prior knowledge. We demonstrate and evaluate our approach in a real-world scenario.

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Cited By

Henrich ANicklas D(2018)Datenbanken und Information Retrieval an der Universität BambergDatenbank-Spektrum10.1007/s13222-018-0298-518:3(195-202)Online publication date: 24-Oct-2018
https://doi.org/10.1007/s13222-018-0298-5
Surm HRussmeier NGrawunder MNicklas DZielinski O(2016)Experiences with Sensor-Based Research for Critical, Socio-technical Systems2016 17th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2016.41(214-219)Online publication date: Jun-2016
https://doi.org/10.1109/MDM.2016.41
Fagúndez SFleitas JMarotta A(2015)Data Stream Quality Evaluation for the Generation of Alarms in the Health DomainJournal of Intelligent Systems10.1515/jisys-2014-016624:3(361-369)Online publication date: 5-Mar-2015
https://doi.org/10.1515/jisys-2014-0166
Show More Cited By

Index Terms

Quality matters: supporting quality-aware pervasive applications by probabilistic data stream management
1. Information systems
  1. Information systems applications

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Published In

cover image ACM Conferences

DEBS '14: Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems

May 2014

371 pages

ISBN:9781450327374

DOI:10.1145/2611286

General Chairs:
Umesh Bellur
IIT Bombay, India
,
Ravi Kothari
IBM India Research Labs

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 26 May 2014

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DEBS '14

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DEBS '14: The 8th ACM International Conference on Distributed Event-Based Systems

May 26 - 29, 2014

Mumbai, India

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DEBS '14 Paper Acceptance Rate 16 of 174 submissions, 9%;

Overall Acceptance Rate 145 of 583 submissions, 25%

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Cited By

Henrich ANicklas D(2018)Datenbanken und Information Retrieval an der Universität BambergDatenbank-Spektrum10.1007/s13222-018-0298-518:3(195-202)Online publication date: 24-Oct-2018
https://doi.org/10.1007/s13222-018-0298-5
Surm HRussmeier NGrawunder MNicklas DZielinski O(2016)Experiences with Sensor-Based Research for Critical, Socio-technical Systems2016 17th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2016.41(214-219)Online publication date: Jun-2016
https://doi.org/10.1109/MDM.2016.41
Fagúndez SFleitas JMarotta A(2015)Data Stream Quality Evaluation for the Generation of Alarms in the Health DomainJournal of Intelligent Systems10.1515/jisys-2014-016624:3(361-369)Online publication date: 5-Mar-2015
https://doi.org/10.1515/jisys-2014-0166
Lim LMarie PConan DChabridon SDesprats TManzoor A(2015)Enhancing context data distribution for the internet of things using qoc-awareness and attribute-based access controlAnnals of Telecommunications10.1007/s12243-015-0480-971:3-4(121-132)Online publication date: 13-Oct-2015
https://doi.org/10.1007/s12243-015-0480-9
Cugola GMargara A(2015)The Complex Event Processing ParadigmData Management in Pervasive Systems10.1007/978-3-319-20062-0_6(113-133)Online publication date: 2015
https://doi.org/10.1007/978-3-319-20062-0_6
Marie PLim LManzoor AChabridon SConan DDesprats THughes DTaconet CLeriche S(2014)QoC-aware context data distribution in the internet of thingsProceedings of the 1st ACM Workshop on Middleware for Context-Aware Applications in the IoT10.1145/2676743.2676746(13-18)Online publication date: 9-Dec-2014
https://dl.acm.org/doi/10.1145/2676743.2676746

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