Coordinating Edge and Cloud for Big Data Analytics
Using OpenWhisk as a Polyglot Real-Time Event-Driven Programming Model in CLASS
Cloud Computing QoS for Real-Time Data Applications
CLASS will develop a software architecture to design, deploy and execute distributed big data analytics with real-time constraints.
Featuring a heavy sensor infrastructure to collect and process in real-time a vast amount of data across a wide urban area.
Connected cars equipped with heterogeneous sensors and V2X connectivity to enhance the driving experience by giving
further information about the urban environment.
Deploying advanced urban mobility applications based on a combination of data-in-motion and data-at-rest analytics to efficiently coordinate traffic-flow through city computing resources.