PSI (Pervasive Self-Optimizing Computing Infrastructures) aims to provide a fabric of software components able to dynamically optimize the behaviour of the cloud and IoT infrastructures. PSI targets an improved usage of resources at the systems’ edge via continuous and distributed system-wide optimizations.
This project covers both theoretical and practical aspects, and it combines different research areas including self-adaptive software, control theory, optimization, distributed and real-time systems. The main goal of the project is to develop new methodologies for the efficient usage of computational resources while providing guarantees on different key performance indicators, like, for example, response time and throughput of the system.
Optimal Reference Tracking for Sampled-Data Control Systems (Dec 2022) Enrico Bini , Alessandro Papadopoulos, Jacob Higgins , Nicola Bezzo 61st IEEE Conference on Decision and Control (CDC 2022)
Analytical Approximations in Probabilistic Analysis of Real-Time Systems (Dec 2022) Filip Markovic, Thomas Nolte, Alessandro Papadopoulos 43rd IEEE Real-Time Systems Symposium 2022 (RTSS2022)
Ethics of Autonomous Collective Decision-Making: the CAESAR Framework (Nov 2022) Mirgita Frasheri , Václav Struhár, Alessandro Papadopoulos, Aida Causevic Science and Engineering Ethics (JSEE'22)
Designing Self-Adaptive Software Systems with Control Theory: An Overview (Nov 2022) Alessandro Papadopoulos 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) (ACSOS-C 2022)
Kubernetes Orchestration of High Availability Distributed Control Systems (Aug 2022) Bjarne Johansson, Mats Rågberger , Thomas Nolte, Alessandro Papadopoulos 23rd IEEE International Conference on Industrial Technology (ICIT 2022)
RT-SCALER: Adaptive Resource Allocation Framework for Real-Time Containers (Jul 2022) Václav Struhár, Silviu Craciunas , Mohammad Ashjaei, Moris Behnam, Alessandro Papadopoulos Real-time And intelliGent Edge computing workshop (RAGE2022)