Towards a computing continuum: Enabling edge-to-cloud integration for data-driven workflows

Daniel Balouek-Thomert, Eduard Gibert Renart, Ali Reza Zamani, Anthony Simonet, Manish Parashar

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Dramatic changes in the technology landscape marked by increasing scales and pervasiveness of compute and data have resulted in the proliferation of edge applications aimed at effectively processing data in a timely manner. As the levels and fidelity of instrumentation increases and the types and volumes of available data grow, new classes of applications are being explored that seamlessly combine real-time data with complex models and data analytics to monitor and manage systems of interest. However, these applications require a fluid integration of resources at the edge, the core, and along the data path to support dynamic and data-driven application workflows, that is, they need to leverage a computing continuum. In this article, we present our vision for enabling such a computing continuum and specifically focus on enabling edge-to-cloud integration to support data-driven workflows. The research is driven by an online data-driven tsunami warning use case that is supported by the deployment of large-scale national environment observation systems. This article presents our overall approach as well as current status and next steps.

Original languageEnglish (US)
Pages (from-to)1159-1174
Number of pages16
JournalInternational Journal of High Performance Computing Applications
Volume33
Issue number6
DOIs
StatePublished - Nov 1 2019

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

Keywords

  • Continuum computing
  • data-driven workflows
  • edge-to-cloud integration
  • programming systems
  • streaming data-analytics

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