Big Data Analytics for Smart Cities: The H2020 CLASS Project

Applying big-data technologies to field applications has resulted in several new needs. First, processing data across a compute continuum spanning from cloud to edge to devices, with varying capacity, architecture etc. Second, some computations need to be made predictable (real-time response), thus supporting both data-in-motion processing and larger-scale data-at-rest processing. Last, employing an event-driven programming model that supports mixing different APIs and models, such as Map/Reduce, CEP, sequential code, etc.