Alessandro Vittorio Papadopoulos

On the Edge of the Cloud: Making Smart Systems Predictable When Time Matters

2026-02-25T00:00:00+01:00

Seminar overview ☁️⚙️

Edge-to-cloud systems connect devices and cloud computing to deliver fast and efficient services.

This seminar explores how these systems work, why predictability is critical when timing matters, and the main challenges and solutions in making smart systems dependable.

Event details 📍🗓️

Date: 27 May 2026
Time: 17:30–19:00
Location: AULA Q, via Beniamino Andreatta 8 (“aule Belmeloro”)
Format: In person and online
Type: Lectures

Speaker 👤

Prof. Alessandro Vittorio Papadopoulos

ISA Visiting Fellow

Full Professor, Mälardalen University (MDU), Sweden 🇸🇪

Prof. Papadopoulos works in control, robotics, and real-time embedded systems. At MDU, he leads the Complex Real-Time Embedded Systems group, with research focused on reliable, adaptive, and intelligent automation and cloud–edge systems using control-theoretic approaches.

Speaker website: Visit Prof. Papadopoulos’s website 🔗

Attendance

Online (Microsoft Teams): Join on Microsoft Teams
In person: Book your seat

Source

Official event page: ISA – Institute of Advanced Studies

The Twin-in-the-loop approach for vehicle dynamics estimation and control

2023-03-21T00:00:00+01:00

Presenter Simone Formentin, Politecnico di Milano, Italy
Slides

Abstract In the automation of vehicle dynamics, engineering a suitable filter or controller is a long and costly process. The starting point is usually the design of the digital system of interest, based on a simple model of the vehicle, and its testing on a full-fledged multibody simulator. Then, many driving hours are required during the End-of-Line (EoL) tuning phase to calibrate the system to be used with the real vehicle. In this talk, we will discuss the methodological and practical advances offered in case the full-fledged multibody simulator can be run on-board in the electronic control unit, so as to have an accurate estimate of both vehicle states and nominal controls in real time. Within this framework, we will show that in the EoL phase we only need to design simple compensators of the mismatches between the expected and the measured outputs, whereas no fine tuning of (possibly complex) systems is required. The resulting approach not only exploits the - usually available - simulator and significantly simplifies the design process, but also outperforms the state-of-the-art techniques in terms of tracking accuracy and robustness within challenging vehicle dynamics problems. Several case studies will be discussed to illustrate the potential of the proposed approach as compared to traditional vehicle dynamics estimation and control solutions.

Dettù et al. “The Twin-in-the-Loop approach for vehicle dynamics control”
Riva et al. “Twin-in-the-loop state estimation for vehicle dynamics control: theory and experiments”

ACSOS 2022 Special Event Tutorial @ Cesena, Italy

2022-05-05T00:00:00+02:00

Organizer

Danilo Pianini, University of Bologna, Italy

Speakers & Talks

Ivana Dusparic: “Reinforcement Learning for self-adaptive city-scale infrastructures”

Alessandro Papadopoulos: “Designing self-adaptive software systems with control theory: an overview”

Lukas Esterle: “Digital Twins - from Development to deployment in intelligent systems”

Using physics for monitoring autonomous rigid-wing sailing robots

2021-11-02T00:00:00+01:00

Presenter Matias Waller, Arcada, Finland
Slides

Abstract The basic physics behind sailing is presented. The basic model is explored numerically and used as a tool for monitoring performance of rigid-wing sailing robots. Using measurements from two different autonomous sailing robots, it is shown how the approach can be used for assessing pilot experiments and detecting unreliable sensors.

ESWeek 2021: Tutorial on Fog Computing for Industrial IoT

2021-10-07T00:00:00+02:00

Organizers

Alessandro V. Papadopoulos, Mälardalen University, Sweden
Wilfried Steiner, TTTech Computertechnik AG, Austria

Speakers

Fog Computing – Industrial Use Cases and Open Issues by Wilfried Steiner (TTTech, Austria)
Control over the edge cloud: Possibilities and Challenges by Karl-Erik Årzén (Lund U., Sweden)
Data-driven techniques for fault tolerance in Edge Computing systems – theory by Ivona Brandic (TU Wien, Austria)
Data-driven techniques for fault tolerance in Edge Computing systems – hands on! by Atakan Aral (Uni Wien, Austria)

More details: https://esweek.org/tutorial-2-fog-computing-for-industrial-io/

Methodological Principles for Reproducible Performance Evaluation in Cloud Computing (ICSE 2020)

2020-07-07T00:00:00+02:00

Presenter Alessandro Papadopoulos, MDH, Sweden

Abstract The rapid adoption and the diversification of cloud computing technology exacerbate the importance of a sound experimental methodology for this domain. It has been a decade since the first commercial cloud has opened for a general public (Amazon AWS, in 2007). Cloud computing systems are now in much demand, and command significant industrial and scientific interest. Although scientific progress and industry growth depend on using sound principles for measuring and reporting cloud-system performance, this process remains complex. This work investigates how to measure and report performance in the cloud, and how well the cloud research community is already doing it. There are several difficulties, including controlling the time-accuracy trade-off, deciding which data to collect and to report, and using the right summarization statistics in the report. We propose a set of eight important methodological principles that combine best-practices from nearby fields with concepts applicable only to clouds, and with new ideas about the time-accuracy trade-off. We show how these principles are applicable using a practical use-case experiment. To this end, we analyze the ability of the newly released SPEC Cloud IaaS benchmark to follow the principles, and showcase real-world experimental studies in common cloud environments that meet the principles. Last, we report on a systematic literature review including top conferences and journals in the field, from 2012 to 2017, analyzing if the practice of reporting cloud performance measurements follows the proposed eight principles. Worryingly, this systematic survey and the subsequent two-round human reviews, reveal that few of the published studies follow the eight experimental principles. We conclude that, although these important principles are simple and basic, the cloud community is yet to adopt them broadly to deliver sound measurement of cloud environments.

More details

Towards Bridging the Gap between Control and Self-Adaptive System Properties

2020-06-30T00:00:00+02:00

Presenter Javier Camara, University of York, UK

Abstract Two of the main paradigms used to build adaptive software employ different types of properties to capture relevant aspects of the system’s run-time behavior. On the one hand, control systems consider properties that concern static aspects like stability, as well as dynamic properties that capture the transient evolution of variables such as settling time. On the other hand, self-adaptive systems consider mostly non-functional properties that capture concerns such as performance, reliability, and cost. In general, it is not easy to reconcile these two types of properties or identify under which conditions they constitute a good fit to provide run-time guarantees. There is a need of identifying the key properties in the areas of control and self-adaptation, as well as of characterizing and mapping them to better understand how they relate and possibly complement each other. In this paper, we take a first step to tackle this problem by: (1) identifying a set of key properties in control theory, (2) illustrating the formalization of some of these properties employing temporal logic languages commonly used to engineer self-adaptive software systems, and (3) illustrating how to map key properties that characterize self-adaptive software systems into control properties, leveraging their formalization in temporal logics. We illustrate the different steps of the mapping on an exemplar case in the cloud computing domain and conclude with identifying open challenges in the area.

More details

Concurrency defect localization in embedded systems using static code analysis: an evaluation

2019-10-24T00:00:00+02:00

Presenter Bjarne Johansson, ABB AB & Mälardalen University, Sweden

Abstract Defects with low manifestation probability, such as concurrency defects, are difficult to find during testing. When such a defect manifests into an error, the low likelihood can make it time-consuming to reproduce the error and find the root cause. Static Code Analysis (SCA) tools have been used in the industry for decades, mostly for compliance checking towards guidelines such as MISRA. Today, these tools are capable of sophisticated data and execution flow analysis. Our work, presented in this paper, evaluates the feasibility of using SCA tools for concurrency defect detection and localization. Earlier research has categorized concurrency defects. We use this categorization and develop an object-oriented C++ based test suite containing defects from each category. Secondly, we use known and real defects in existing products’ source code. With these two approaches, we perform the evaluation, using tools from some of the largest commercial actors in the field. Based on our results, we provide a discussion about how to use static code analysis tools for concurrency defect detection in complex embedded real-time systems.

Automatica.it 2018 - Tavola rotonda (in Italian)

2018-09-14T00:00:00+02:00

Moderators

Laura Giarré (Università di Modena e Reggio Emilia)
Pietro Tesi (Università degli Studi di Firenze)

Speakers

Paolo Frasca (CNRS, France) “Opinion dynamics, Social Networks, Systems and Control”
Giulia Giordano (Delft University of Technology, The Netherlands) “Systems Biology, Decentralized Control, Network Systems”
Alessandro Papadopoulos (Mälardalen University, Sweden) “Cloud Computing, Feedback Computing, Real-time and embedded systems, Control Theory”
Mattia Zorzi (Università degli Studi di Padova, Italy) “Machine Learning, Robust Estimation, Graphical Models, Identification Theory”

Alessandro Vittorio Papadopoulos

On the Edge of the Cloud: Making Smart Systems Predictable When Time Matters

Seminar overview ☁️⚙️

Event details 📍🗓️

Speaker 👤

Prof. Alessandro Vittorio Papadopoulos

Attendance

Source

The Twin-in-the-loop approach for vehicle dynamics estimation and control

Additional related references

ACSOS 2022 Special Event Tutorial @ Cesena, Italy

Organizer

Speakers & Talks

Using physics for monitoring autonomous rigid-wing sailing robots

ESWeek 2021: Tutorial on Fog Computing for Industrial IoT

Organizers

Speakers

Methodological Principles for Reproducible Performance Evaluation in Cloud Computing (ICSE 2020)

Towards Bridging the Gap between Control and Self-Adaptive System Properties

Concurrency defect localization in embedded systems using static code analysis: an evaluation

Automatica.it 2018 - Tavola rotonda (in Italian)

Moderators

Speakers