A Serverless Real-Time Data Analytics Platform for Edge Computing

Contemporary solutions for cloud-supported, edge-data analytics mostly apply analytics techniques in a rigid bottom-up approach, regardless of the data's origin. Typically, data are generated at the edge of the infrastructure and transmitted to the cloud, where traditional data analytics techni...

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Bibliographic Details
Published inIEEE internet computing Vol. 21; no. 4; pp. 64 - 71
Main Authors Nastic, Stefan, Rausch, Thomas, Scekic, Ognjen, Dustdar, Schahram, Gusev, Marjan, Koteska, Bojana, Kostoska, Magdalena, Jakimovski, Boro, Ristov, Sasko, Prodan, Radu
Format Journal Article
LanguageEnglish
Published IEEE 2017
Subjects
Analytical models
Cloud computing
Computational modeling
Data analysis
Data models
edge computing
Internet of Things
Internet/Web technologies
IoT
Quality of service
real-time data analysis
Real-time systems
security and privacy
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Summary:Contemporary solutions for cloud-supported, edge-data analytics mostly apply analytics techniques in a rigid bottom-up approach, regardless of the data's origin. Typically, data are generated at the edge of the infrastructure and transmitted to the cloud, where traditional data analytics techniques are applied. Currently, developers are forced to resort to ad hoc solutions specifically tailored for the available infrastructure (for example, edge devices) when designing, developing, and operating the data analytics applications. Here, a novel approach implements cloud-supported, real-time data analytics in edge-computing applications. The authors introduce their serverless edge-data analytics platform and application model and discuss their main design requirements and challenges, based on real-life healthcare use case scenarios.
ISSN:1089-7801
1941-0131
DOI:10.1109/MIC.2017.2911430