IoT Workload Distribution Impact Between Edge and Cloud Computing in a Smart Grid Application

  • Otávio CarvalhoEmail author
  • Manuel Garcia
  • Eduardo Roloff
  • Emmanuell Diaz Carreño
  • Philippe O. A. Navaux
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 796)


The advent of Internet of Things is now part of our reality. Increasing amounts of data are being continuously generated and monitored through widespread sensing technologies such as personal smartphones, large scale smart cities sensor deployments and smart electrical grids.

However, the ability to aggregate and act upon such data gathered by sensors is still a significant research and industrial challenge. Devices that are able to collect and act on data at network edges are bounded by the amount of data that can be sent over networks.

In this paper, we analyze the impact of workload distribution in a smart grid application, evaluating how we can increase processing rates by leveraging each time more powerful edge node processors.

Our results show that our test bed application, leveraging cloud nodes processing and processing windows, is able to achieve processing rates of approximately 800k measurements per second using four edge node processors and a single cloud node.



This research received partial funding from CYTED for the RICAP Project.

It has also received partial funding from the EU H2020 Programme and from MCTI/RNPBrazil under the HPC4E project, grant agreement no. 689772.

Additional funding was provided by FAPERGS in the context of the GreenCloud Project.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Otávio Carvalho
    • 1
    Email author
  • Manuel Garcia
    • 1
  • Eduardo Roloff
    • 1
  • Emmanuell Diaz Carreño
    • 1
  • Philippe O. A. Navaux
    • 1
  1. 1.Informatics InstituteFederal University of Rio Grande do Sul (UFRGS)Porto AlegreBrazil

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