We are proud to announce that the DisCoTec 2018 keynotes will be delivered by:
Paolo Romano, IST, Lisbon University & INESC-ID, Portugal
Title of Talk:
Self-tuning of complex computing systems: reconciling analytical modelling and machine-learning approaches.
Since the inception of Autonomic Computing concept by IBM, back in 2001, self-tuning has been advocated as a crucial tool to tame the complexity of managing modern parallel and distributed systems. The later advent of cloud’s elastic computing paradigm, in which efficiency equates cost reductions, has further amplified the urge for self-tuning mechanisms aimed at optimizing the myriad of configuration parameters that affect the performance of complex modern applications in subtle, and often non-linear, ways.
This talk focuses on a key challenge that arises whenever building a self-tuning mechanism for a computing system: how to model its behavior, i.e., how to predict the response of its Key Performance Indicators (e.g., throughput or energy consumption) to variations of its input workload characteristics or configuration options. Existing approaches to modelling performance of parallel and distributed systems address this problem by employing two alternative methodologies: on the one hand, analytical models (AM), which take a white approach and encode expert knowledge on the dynamics of the target system in a mathematical model (e.g., based on queuing theory); on the other hand, Machine Learning (ML) techniques, which take a black-box approach and infer a predictive model based on the observation of the system’s performance under different settings.
Existing literature has typically regarded AM and ML as antagonistic techniques based on antithetic performance modelling methodologies. Yet, as I will advocate in this talk, the two approaches can, and should, be used in synergy, by leveraging hybrid, gray-box techniques that combine AM and ML to mutually compensate their shortcomings and achieve the best of both worlds. I will illustrate the potential of this approach by overviewing recent techniques that couple, in different ways, AM and ML, and conclude by identifying open questions in the design space of gray-box performance modelling techniques.
Paolo Romano is associate professor at Lisbon University and senior researcher at INESC-ID, Lisbon (Portugal). He received his Ph.D in 2007, from Rome University Sapienza.
His research interests include parallel and distributed computing, dependability, autonomic systems, data management, cloud and high performance computing. In these areas, Paolo published more than 100 papers, winning 3 best awards, and has coordinated several national and European projects, including a COST Action bringing together researchers from 60 institutions and 17 countries. Paolo has been awarded the Best INESC-ID young researcher award in 2011 and the Best INESC-ID researcher award in 2016.
Title of Talk:
Electronic voting: how logic can help
Electronic voting should offer at least the same guarantees than
traditional paper-based voting systems. In order to achieve this,
electronic voting protocols make use of cryptographic primitives, as in
the more traditional case of authentication or key exchange protocols.
All these protocols are notoriously difficult to design and flaws may be
found years after their first release. Formal models, such as process
algebra, Horn clauses, or constraint systems, have been successfully
applied to automatically analyze traditional protocols and discover
flaws. Electronic voting protocols however significantly increase the
difficulty of the analysis task. Indeed, they involve for example new
and sophisticated cryptographic primitives, new dedicated security
properties, and new execution structures.
After an introduction to electronic voting, we will describe the current
techniques for e-voting protocols analysis and review the key challenges
towards a fully automated verification.
Véronique Cortier is CNRS research director at Loria (Nancy, France). In
2003, she received her Ph.D. degree in Computer Science from the École
Normale Supérieure de Cachan, from which she graduated.
Her research focuses on formal verification of security protocols, in
using formal techniques such as first order logic or rewriting.
She has co-authored more than 80 publications on these topics.
In 2010, she was awarded an ERC starting grant and in 2015, she received
the INRIA - Académie des Sciences young researcher award.
Franco Zambonelli, Università di Modena e Reggio Emilia, Italy
Title of Talk:
New Challenges of Coordination in the IoT and Autonomous Systems Era
Myriads of smart IoT devices are already pervading our everyday environments and cities, and we will assist very soon to the appearance of large populations of autonomous goal-oriented devices, from personal assistants to autonomous vehicles. Such emerging scenario introduces peculiar software engineering and coordination challenges that cannot be easily addressed by current paradigms and tools. These include for example: the need of coordinating components that exhibit different levels of autonomy; the need to account for multiple and possibly conflicting goals; the need to dynamically formulate a coordination strategy to respond to contingencies and dynamic situations; the need to modulate the autonomy of components to ensure the right outcome of a coordination act; the need to account for societal norms, other than possibly ethical principles. In this talk I will overview such peculiar issues and, without the ambition of proposing fully-fledged solutions (which I don’t have), I will try at least to sketch some promising research directions.
Franco Zambonelli is full professor of Computer Science at the University of Modena and Reggio Emilia. He got his PhD in Computer Science and Engineering from the University of Bologna in 1997. His research interests include: pervasive computing, multi-agent systems, self-adaptive and self-organizing systems. He has published over 100 papers in peer-reviews journals, and has been invited speaker at many conferences and workshops. He is in the editorial board of the ACM Transactions on Autonomous and Adaptive Systems, Elsevier Journal of Pervasive and Mobile Computing, IEEE Society & Technology Magazine, the BCS Computer Journal, and he is in the Steering Committee of the IEEE SASO Conference. He has been scientific manager of the EU FP6 Project CASCADAS and coordinator of the EU FP7 Project SAPERE. He is ACM Distinguished Scientist, member of the Academia Europaea, and IEEE Fellow.