Computation is becoming cheaper and cheper, with a lot of dedicated core capacity. Because of this, we are plugging in components in our control systems, like anomaly detector and predictive mainteinance algorithms, that can help us take better advantage of the computational power for something useful. However, this additional load may come at the cost of problems and bugs, that manifest themselves as deadline misses. The controller that should regolate the plant does not manage to compute a fresh control signal on time.
The paper “Stability and Performance Analysis of Control Systems Subject to Bursts of Deadline Misses“, that received the best paper award at ECRTS 2021 sets off to try to answer the question: should we worry about this? Control systems are designed to be robust to a large set of disturbances, ranging from noise to unmodelled dynamics. Are computational delays and faults a problem?
Recent work on the weakly hard model – applied to controllers – has shown that control tasks can also be inherently robust to deadline misses. However, existing exact analyses are limited to the stability of the closed-loop system. In the paper, we show that stability is important but cannot be the only factor to determine whether the behaviour of a system is acceptable also under deadline misses. We focus on systems that experience bursts of deadline misses and on their recovery to normal operation. We apply the resulting comprehensive analysis (that includes both stability and performance) to a Furuta pendulum, comparing simulated data and data obtained with the real plant.
We further evaluate our analysis using a benchmark set composed of 133 systems, which is considered representative of industrial control plants. Our results show the handling of the control signal is an extremely important factor in the performance degradation that the controller experiences, a clear indication that only a stability test does not give enough indication about the robustness to deadline misses.
Cristiana Bolchini is a Professor at the Dipartimento di Elettronica, Informazione e Bioningegneria of Politecnico di Milano, where she received a PhD in Automation and Computer Science Engineering in 1997. Her research interests are in methodologies for the design and analysis of computing/embedded systems with a particular focus on dependability aspects. She coordinates and has been involved in several EU research projects. She is the General Chair for DATE 2022.
Why did you choose to pursue a career in computer science and engineering?
I actually enrolled and got a degree in Electronics Engineering (Control and Automation specifically) and moved to Computer Science Engineering with the PhD since the area of research I was pursuing fell under that specialization when established in our department. My dad was an electronic design technician, able to fix most electronic appliances at home, and had a small lab with instruments. I saw how passionate he was with his job and thought it was something that could be right for me as well. My career took a very different path, I am not able fix any electronic appliance, but the passion is the same.
Being a women working in STEM, which has traditionally been a mail dominated area, did you felt this could be a disadvantage?
Being one of the few women (I think we were around 5% in my class at the university) made me aware of being noticeable but it never felt as an advantage or disadvantage; I think I simply perceived it as a statistical data… less women were interested in that kind of things.
Sometimes being one of the few women made the others wonder why I was there, and question my competence or abilities, but I guess I did not really see it or feel it as a problem.
As the years went by and emphasis increased on diversity and female access to STEM studies and careers, I realized that I was very lucky for growing up in a context where I could have chosen any path based on my preferences and ability, encouraged and not stopped to avoid being a different item in a set. However this is not true for everybody, and encouragement and promotion are key factors to enable females to understand that they should pursuit their preferred path, because there is nothing they wouldn’t be able to do.
Your research is very much focused on dependability aspects, in particular considering reconfigurable systems. Is this the reason why you came aware of the ADMORPH project? Would you like to mention any particularly interesting aspects in the project?
To be honest I did not came aware of the project, since I have been contacted. So, if you rephrase the question by omitting that part, I can provide the following answer wr.t. what I find interesting in the project.
My area of expertise is indeed dependability, having also carried out research in the area of adaptivity and self-awareness, so I find most aspects of the ADMORPH project of great interest, and I will monitor the project outcomes and results through the years.
You are the General Chair for DATE 2022, so we wish you all the success in your mission! Do you have any plans to foster more female researchers to submit their work and participate in the conference? (we hope this interview might help advertising and contributing to that goal)
DATE and DAC foster a “Diversity in EDA” activity to promote female (and underepresented in general) professionals and researchers; when I served as Program Chair for DATE 2020 I put a lot of effort in bringing diversity in the Technical Program Committee and I am trying to do the same this year. However, it was a tough objective, as female scientists in our field are numerically less than male ones… so it would be great to be able to see a growth in female presence.
I think one effective way to encourage this trend is by providing an example, by showing them that everything is possible.
As a computer science teacher, what would you say to young female students to convince them to pursue a career in computer science?
I encourage them to ignore the statistics and to pursue whatever they like… a computer science degree is an enabling ticket for several interesting careers, independently of the gender.
ADMORPH had a strong presence in the organization of a panel session at the ASD Autonomous Systems Design initiative, in the scope of the DATE 2021 conference. The session, under the theme “Self-adaptive safety- and mission-critical CPS: wishful thinking or absolute necessity?” was organized by ADMORPH researchers Martina Maggio and Andy Pimentel. It took place on the 5th of February, by video-conference, and attracted the attention of about 60 participants. Speakers (or panelist) on the program were Stefanos Skalistis (Raytheon Technologies, Ireland), talking about “Certification challenges of adaptive avionics systems”, and Clemens Grelck (University of Amsterdam, Netherlands), presenting “The TeamPlay Coordination Language for Dependable Systems”. The third speaker in the panel was Sasa Misailovic (from UIUC), talking about “Programming Systems for Helping Developers Cope with Uncertainty”. The panel session resulted in a lively discussion about what adaptation can do, how to test it, and how to certify the results.
In ADMORPH, we look at the guarantees that we can provide for embedded systems that do not behave as we expect them to do. One of this unexpected behaviour manifests itself as deadline misses. In particular, control tasks that miss their deadlines can be dangerous and potentially create trouble (think about the controller that prompts a car to hold a lane not computing regularly – the car could then deviate and cross to another lane, with potential for accidents).
Some of our research focuses on designing controllers that do not miss their deadlines, but in somecases we wonder what we can guarantee when we have a controller that might just misbehave occasionally. In a paper (co-authored by Paolo Pazzaglia, Arne Hamann, Dirk Ziegenbein and Martina Maggio) that will be presented next week at the Design, Automation and Test in Europe Conference (and won the paper award in the embedded and cyber-physical systems track – Thanks! We are really humbled and excited!) we look at how to modify existing controllers in a viable way.
When a controller is already in production phase, only small modifications will be allowed (changing some constants here and there)but this can potentially go a long way to enforce some robustness. In the paper we describe one of such small modifications to an existing control architecture and implementation and show that using the knowledge of past misses can improve the controller performance.
With the realisation of the ADMORPH vision embedded systems will gain the ability to change their behaviour. These systems will learn how to counteract specific threats. A robot may learn that a given path is not traversable and will look for alternatives to reach its objective. A radar may use more or less power to detect objects. A controller may learn not to trust sensor data because they have likely been compromised. However, one hard question to answer is: “how can we test that the software that these systems execute behave in the way we expect”? Even more: “are we really able to determine what we expect”?
Testing software in the presence of learning and adaptation is an extremely complex problem. Should we let the system learn for a while before starting the testing procedure? If we had learn something different, would we then be better or worse? Suppose for example that we have a camera that is trying to detect people in the video images. Imagine we never feed it with an image that contains people. Can we really say that we had enough data for the camera to start working in the way it is supposed to work?
We try to find an answer to some of these questions in our publication “Testing Self-Adaptive Software with Probabilistic Guarantees on Performance Metrics” that has received an ACM SIGSOFT Distinguished Paper Award at the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 2020.
In the paper we talk about how the testing of adaptive software should switch paradigm and go from being deterministic to providing probabilistic guarantees and we argue about why it is not possible to do anything different. We use a tool called scenario theory to perform software testing for adaptive systems with probabilistic guarantees. We apply the theory to two case studies (an adaptive video encoder, and and tele-assistance service).
The HiPEAC Info magazine is a quarterly publication providing the latest news on the activities within the European HiPEAC network, as well as activities on high-performance embedded architectures and compilers at large.
The April issue includes an article introducing the ADMORPH project and describing the project objectives and the addressed challenges.