Issue No. 04 - July-Aug. (2017 vol. 21)
Stefan Nastic , TU Wien
Thomas Rausch , TU Wien
Ognjen Scekic , TU Wien
Schahram Dustdar , TU Wien
Marjan Gusev , Ss. Cyril and Methodius University
Bojana Koteska , Ss. Cyril and Methodius University
Magdalena Kostoska , Ss. Cyril and Methodius University
Boro Jakimovski , Ss. Cyril and Methodius University
Sasko Ristov , University of Innsbruck
Radu Prodan , University of Innsbruck
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.
Internet/Web technologies, real-time data analysis, cloud computing, IoT, edge computing, Internet of Things, security and privacy
S. Nastic et al., "A Serverless Real-Time Data Analytics Platform for Edge Computing," in IEEE Internet Computing, vol. 21, no. 4, pp. 64-71, 2017.