Resource-aware Federated Data Analytics in Edge-Enabled IoT Systems

Abstract

In a resource constrained environment like Internet-of-Things (IoT) systems, it is critical to make optimal decisions on how much resources to allocate pre-processing and how much to allocate to model training, and which specific combination of preprocessing and learning should be selected. This talk first, provides an overview of some initial steps we took towards developing federated data pre-processing in IoT environments, and then a visionary overview of potential research problems related to developing an integrated resource-aware and Quality-of-Service (QoS)-aware data pre-processing and model training system is provided.