An elastic software architecture for extreme-scale big data analytics
Document typePart of book or chapter of book
Rights accessOpen Access
ProjectELASTIC - A Software Architecture for Extreme-ScaLe Big-Data AnalyticS in Fog CompuTIng ECosystems (EC-H2020-825473)
This chapter describes a software architecture for processing big-data analytics considering the complete compute continuum, from the edge to the cloud. The new generation of smart systems requires processing a vast amount of diverse information from distributed data sources. The software architecture presented in this chapter addresses two main challenges. On the one hand, a new elasticity concept enables smart systems to satisfy the performance requirements of extreme-scale analytics workloads. By extending the elasticity concept (known at cloud side) across the compute continuum in a fog computing environment, combined with the usage of advanced heterogeneous hardware architectures at the edge side, the capabilities of the extreme-scale analytics can significantly increase, integrating both responsive data-in-motion and latent data-at-rest analytics into a single solution. On the other hand, the software architecture also focuses on the fulfilment of the non-functional properties inherited from smart systems, such as real-time, energy-efficiency, communication quality and security, that are of paramount importance for many application domains such as smart cities, smart mobility and smart manufacturing.
CitationSerrano, M. [et al.]. An elastic software architecture for extreme-scale big data analytics. A: "Technologies and applications for big data value". Berlín: Springer, 2022, p. 89-110.