The goal of PrEstoCloud is to make substantial research contributions in the Cloud computing and real-time Big Data technologies in order to provide a dynamic, distributed architecture for proactive cloud resources management reaching the extreme edge of the network for efficient real-time big data processing and to deploy and validate it in several challenging, complementary and commercially-very promising use cases.
In particular, PrEstoCloud aims to combine real-time Big Data, Cloud computing and Fog computing research in a unique way in order to provide an innovative solution for, as above elaborated, very complex problem of cloud-based adaptive real-time Big Data processing.
“Changes” as the first class citizen
- Changes in the incoming data streams causes changes in the provided services (real-time processing, Storm-like, geolocation);
- Changes in the quality of services causes changes in processing architecture (selfadaptation);
- Speed of changes in the incoming data streams and deterioration of the processing nodes status causes distribution and deployment changes in the processing infrastructure (proactive).
- Adaptivity in an ad-hoc manner in order to cope with the extreme dynamics of Big Data;
- Processing on the edge, i.e. mobile processing nodes, in order to exploit the full potential of Big real-time data streams;
- Efficient and reliable orchestration of distributed processing nodes in order to cope with sudden changes in the Big Data streams;
- Proactivity in order to enhance anticipation of need for changes in the processing architecture and support reactions ahead of time, in complex Big Data-driven application scenarios.