Online decision-making using edge resources for content-driven stream processing

Eduard Renart, Daniel Balouek-Thomert, Xuan Hu, Jie Gong, Manish Parashar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

The Internet of Things (IoT) describes the emerging paradigm that connects sensors, often located at the edge of the network, to stream processing engines located at the core of the network to enable online data-driven monitoring, management, and control. As IoT applications require increasing volumes of streaming data to be processed by complex workflows in a timely manner, it is becoming important to also leverage resources closer to the edge. Furthermore, the topology of these workflows and where theyare executed is determined not only by application objectives and available resources, but also by the content of the data streams, however, current stream processing engines do not provide this flexibility. In this paper, we present a programming framework that enables applications to specify data-driven, location- and resource-aware processing of data streams. Specifically, it provides abstractions for specifying where and how a data stream is processed based on its content, spatial and temporal characteristics. We also present an implementation of the framework using an event-driven runtime, where events are associatively described. Finally, we demonstrate the effectiveness of the solution by an evaluation of scalability and performance using a disaster response application usecase.

Original languageEnglish (US)
Title of host publicationProceedings - 13th IEEE International Conference on eScience, eScience 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages384-392
Number of pages9
ISBN (Electronic)9781538626863
DOIs
StatePublished - Nov 14 2017
Event13th IEEE International Conference on eScience, eScience 2017 - Auckland, New Zealand
Duration: Oct 24 2017Oct 27 2017

Publication series

NameProceedings - 13th IEEE International Conference on eScience, eScience 2017

Other

Other13th IEEE International Conference on eScience, eScience 2017
Country/TerritoryNew Zealand
CityAuckland
Period10/24/1710/27/17

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences (miscellaneous)
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computer Networks and Communications
  • Computer Science Applications
  • Computers in Earth Sciences
  • Social Sciences (miscellaneous)

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