Quality of Service Aware Orchestration for Cloud–Edge Continuum Applications

Adrián Orive*, Aitor Agirre, Hong Linh Truong, Isabel Sarachaga, Marga Marcos

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
113 Downloads (Pure)

Abstract

The fast growth in the amount of connected devices with computing capabilities in the past years has enabled the emergence of a new computing layer at the Edge. Despite being resource-constrained if compared with cloud servers, they offer lower latencies than those achievable by Cloud computing. The combination of both Cloud and Edge computing paradigms can provide a suitable infrastructure for complex applications’ quality of service requirements that cannot easily be achieved with either of these paradigms alone. These requirements can be very different for each application, from achieving time sensitivity or assuring data privacy to storing and processing large amounts of data. Therefore, orchestrating these applications in the Cloud–Edge computing raises new challenges that need to be solved in order to fully take advantage of this layered infrastructure. This paper proposes an architecture that enables the dynamic orchestration of applications in the Cloud– Edge continuum. It focuses on the application’s quality of service by providing the scheduler with input that is commonly used by modern scheduling algorithms. The architecture uses a distributed scheduling approach that can be customized in a per-application basis, which ensures that it can scale properly even in setups with high number of nodes and complex scheduling algorithms. This architecture has been implemented on top of Kubernetes and evaluated in order to asses its viability to enable more complex scheduling algorithms that take into account the quality of service of applications.

Original languageEnglish
Article number1755
Pages (from-to)1-21
Number of pages21
JournalSensors
Volume22
Issue number5
DOIs
Publication statusPublished - 1 Mar 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • Cloud–Edge continuum
  • Edge computing
  • Fog computing
  • Orchestration
  • Quality of service

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