Prof. Giancarlo Fortino gave a keynote lecture titled “Integrating Machine Learning and Multi-Agent Systems for Fully Enabling Device-Edge-Cloud Continuum in Complex IoT Worlds” at the 8th International Conference on Internet of Things, Big Data and Security (IoTBDS 2023), April 21-23, 2023 – Prague.
We are pleased to announce the 1st International Workshop on Machine Learning for Autonomic System Operations in the Device-Edge-Cloud Continuum, taking place on September 25, 2023 at Rende, Italy, in conjunction with the International Conference on Embedded Wireless Systems and Networks (EWSN 2023).
The goal of the workshop is to bring together a community of researchers and practitioners who study problems at the intersection of AI/ML, autonomic and cognitive computing, D-E-C continuum, distributed system operation, and resilient application deployment.
For more information, please visit https://events.dimes.unical.it/mlsysops2023/
UNICAL’s latest paper on Edge Intelligence (EI) titled “Disclosing Edge Intelligence: a systematic meta-survey” has been published in Big Data and Cognitive Computing. It offers valuable insights of EI systems. A must-read for anyone interested in the topic!
UNICAL’s latest paper titled “Compressed Sensing Approach for Physiological Signals: A Review” has been published in the IEEE Sensors Journal.
A review of edge computing-based applications and a discussion of future research directions related to AI and edge computing convergence, titled “At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives“, has been published in Sensors. The work is a collaboration between researchers at LabSTIC Laboratory, ICAR-CNR and UNICAL.
The Computer Systems Lab (CSL) at the University of Thessaly is coordinating MLSysOps, a large Horizon Europe project on “Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum”.
MLSysOps proposes a hierarchical AI architecture to optimize the underlying resource management and application orchestration mechanisms of the continuum.
Adaptivity will be achieved through continual ML model learning and intelligent retraining concurrently to application execution, while openness and extensibility will be supported through explainable ML methods and an API for pluggable ML models.
CSL is joined by 11 EU-based partners: University of Calabria, University College Dublin, Delft University of Technology, Fraunhofer Portugal, Inria (Lille, FR), NTT DATA Italia, Mellanox/NVIDIA (Israel), Nubis PC (Greece), Chocolate Cloud ApS (Denmark), Ubiwhere(Portugal), and Augmenta (Greece).
The project kickoff took place this week in the beautiful city of Volos and was hosted by the University of Thessaly. Project coordinator is Prof. Spyros Lalis.
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