In the rapidly evolving landscape of IoT-Edge-Cloud continuum (IECC), effective management of computational tasks offloaded from mobile devices to edge nodes is crucial.

The term ‘Dynamic Heterogeneous Computing Sphere’ is used to describe a computing paradigm that is heterogeneous, volatile and highly dynamic.

Data scientists spend much time with data cleaning tasks, and this is especially important when dealing with data gathered from sensors, as finding failures is not unusual (there is an abundance of research on anomaly detection in sensor data).

The report “NEM Vision 2030 Towards a future media ecosystem” describes the NEM approach about the European media and creative industries sectors for the next decade.

In the field of plant disease protection, many approaches exist, but all acknowledge the necessity of fast and accurate identification of the source in order to make the most efficient applications.

In general, one of the complexities of large simulations is related to the usage of the heterogeneous computational resources that are needed to execute them. The definition of workflows, usually linked to concrete orchestrations solutions, has reduced most of that complexity.

Accurate digital twinning of the global challenges (GC) leads to computationally expensive coupled simulations.