TY - JOUR
T1 - Towards a computing continuum
T2 - Enabling edge-to-cloud integration for data-driven workflows
AU - Balouek-Thomert, Daniel
AU - Renart, Eduard Gibert
AU - Zamani, Ali Reza
AU - Simonet, Anthony
AU - Parashar, Manish
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by NSF via grant numbers ACI 1339036, ACI 1441376, OCI 1339036, OCI 1441376, and ACI 1640834.
Publisher Copyright:
© The Author(s) 2019.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - 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.
AB - 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.
KW - Continuum computing
KW - data-driven workflows
KW - edge-to-cloud integration
KW - programming systems
KW - streaming data-analytics
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U2 - 10.1177/1094342019877383
DO - 10.1177/1094342019877383
M3 - Article
AN - SCOPUS:85073224715
SN - 1094-3420
VL - 33
SP - 1159
EP - 1174
JO - International Journal of High Performance Computing Applications
JF - International Journal of High Performance Computing Applications
IS - 6
ER -