Venue:
SR1
Lecturer:
Juan Aznar-Poveda - researcher at DPS
Abstract:
There is a visible trend to efficiently compute specific tasks on the edge before resorting to the Cloud. This compute continuum is notoriously complex due to the heterogeneity of data, resources, and latencies. In this context, applications are usually built based on distributed micro-services that are connected by control- and data-flow. Some of them are stateless and can be re-run without side-effects. However, the number of applications that require shared state, synchronization, and low latency among distributed micro-services is rapidly increasing, while existing solutions do not fully satisfy such needs. In this talk, I will present our novel data management layer to support stateful applications distributed across the cloud-edge continuum. The proposed data layer (SDML) is language independent, highly scalable, and it is expected to offer different levels of consistency and seamlessly collaborate with existing runtime systems to intelligently manage data placement for improved latency and performance.