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

被引:76
作者
Balouek-Thomert, Daniel [1 ]
Renart, Eduard Gibert [1 ]
Zamani, Ali Reza [1 ]
Simonet, Anthony [1 ]
Parashar, Manish [1 ]
机构
[1] Rutgers State Univ, Rutgers Discovery Informat Inst, Piscataway, NJ USA
基金
美国国家科学基金会;
关键词
Continuum computing; edge-to-cloud integration; data-driven workflows; streaming data-analytics; programming systems; CONNECTED VEHICLES;
D O I
10.1177/1094342019877383
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1159 / 1174
页数:16
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