A resource-aware and time-critical IoT framework

Laszlio Toka, Balazs Lajtha, Eva Hosszu, Bence Formanek, Daniel Gehberger, Janos Tapolcai

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

10 Citations (Scopus)


Internet of Things (IoT) systems produce great amount of data, but usually have insufficient resources to process them in the edge. Several time-critical IoT scenarios have emerged and created a challenge of supporting low latency applications. At the same time cloud computing became a success in delivering computing as a service at affordable price with great scalability and high reliability. We propose an intelligent resource allocation system that optimally selects the important IoT data streams to transfer to the cloud for processing. The optimization runs on utility functions computed by predictor algorithms that forecast future events with some probabilistic confidence based on a dynamically recalculated data model. We investigate ways of reducing specifically the upload bandwidth of IoT video streams and propose techniques to compute the corresponding utility functions. We built a prototype for a smart squash court and simulated multiple courts to measure the efficiency of dynamic allocation of network and cloud resources for event detection during squash games. By continuously adapting to the observed system state and maximizing the expected quality of detection within the resource constraints our system can save up to 70% of the resources compared to the naive solution.

Original languageEnglish
Title of host publicationINFOCOM 2017 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509053360
Publication statusPublished - Oct 2 2017
Event2017 IEEE Conference on Computer Communications, INFOCOM 2017 - Atlanta, United States
Duration: May 1 2017May 4 2017

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Other2017 IEEE Conference on Computer Communications, INFOCOM 2017
CountryUnited States


  • Adaptive
  • Cloud computing
  • Cloud control
  • Dynamic
  • Internet of Things
  • QoE
  • QoS
  • Resource provisioning

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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  • Cite this

    Toka, L., Lajtha, B., Hosszu, E., Formanek, B., Gehberger, D., & Tapolcai, J. (2017). A resource-aware and time-critical IoT framework. In INFOCOM 2017 - IEEE Conference on Computer Communications [8057143] (Proceedings - IEEE INFOCOM). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFOCOM.2017.8057143