Keynote Speech 1: Integrating Machine Learning and Multi-Agent Systems for Fully Enabling Device-Edge-Cloud Continuum in Complex IoT Worlds

Abstract

Recently the device-edge-cloud paradigm is gaining momentum due to the benefits it could provide for the development of highly effective, efficient, and complex IoT ecosystems of diversified scale. However, there are many issues related to unsupervised control aspects that need to be addressed in order to fully realize the approach and make it fully operative in real complex environments. In order to address such issues, in this talk, we propose an holistic integration of machine learning and multi-agent systems to create a data-driven control architecture capable to autonomically monitor and control the device-edge-cloud continuum. This objective is being developed in the context of the Horizon Europe project named MLSysOps (https://mlsysops.eu/). Some use cases will be proposed to elucidate our current findings.