What is REDS?
The “Real time Events and Decision Support” Laboratory is hosted by the Department of Informatics, Systems and Communication (DISCo) of the University of Milano-Bicocca, building U14, room T1009, ground floor.
The lab is dedicated to the research in the field of software systems, aimed at understanding and controlling the behavior of complex environments evolving in real time. We explore the technologies needed to deal with the massive streams of events generated by such environments.
This kind of problems arises in a wide variety of application areas, which range from innovative recommendations systems to the integration of physical and logical security, from urban traffic management to the realization of smart environments providing advanced caring services. The importance of these scenarios is growing at a very fast pace, thanks to the diffusion of technologies enabling the collection of event streams from people (wearables) and objects (IoT sensors).
The laboratory also includes a soul devoted to communication networks, which must evolve towards more flexible solutions in support to the collection of massive data coming from IoT sensors.
The technical solutions we are working on include, among others:
– Layered Knowledge Artifacts for domains and problems understanding, which integrate ontologies, probabilistic models and knowledge based systems;
– Bayesian networks and machine learning algorithms;
– Methods for event collection from wearables and other kinds of sensors;
– Special purpose (virtualized) network platforms for the collection of real time data, based on the SDN paradigm and on virtualization technologies.
If you are a student and you are interested on Bachelor and Master Theses, check the dedicated section of the website.
We are involved in several research topics, among which:
The research on Context-Aware Data Analysis exploits the data coming from multiple sources of information in order to characterize the context where events occur. Among these sources we can quote ambient sensors, wearables, smartphones and videocameras. Some of the most important applications pertain to the realm of Smart Environments and eHealth.
The research on Time-Dependent Decision Support Systems deals with those cases where the observed system and its reference environment change in time, passing through a series of macroscopic states, each one characterized by a specific information model. Moving from one state to another, the meaning and importance of some events can change drastically, therefore the applicable inferences and decisions must change accordingly.
for Society and Economy
AI can significantly support societal and economic development due to the rapidly emerging demand for innovative technologies in many application areas. The main aim of this research topic is to bring together heterogeneous competencies from different research fields, offering a wide picture of the best practices, of the challenges, and of the expertise that can be shared among researches and practitioners, exploiting case-based reasoning, ontologies, rule-based systems as conceptual paradigms and/or enabling technologies.
Our research on communication networks deals with innovative approaches that massively rely on Virtualization, on Edge Computing and on Artificial Intelligence capabilities. We explore technologies and paradigms such as Multi-Access Edge Computing (MEC), Network Function Virtualization (NFV), Software-Defined Networking (SDN) and SD-WAN, also in conjunction with Machine Learning, for an increased network flexibility and automation. We deal with scenarios related to the optimization of data flow management, security and, in general, application awareness in Smart City/IoT environments.
Dr. Fabio Sartori
Fabio Sartori is an Assistant Professor at the Department of Informatics, Systems and Communication of the University of Milano-Bicocca. He teaches “Algorithms and Programming” and “Laboratory of Mathematics and Informatics” courses at the Department of Mathematics and its Applications of the University of Milano-Bicocca.
His research activity mainly concerns knowledge-based systems and knowledge management. In these contexts, he has taken care of both methodological and computational aspects in the development of decision support systems, exploiting the Case-Based Reasoning (CBR) paradigm. Recently, he has applied the CBR paradigm in Artificial Intelligence for Society and Economy research field, taking part in the many research projects, funded from both public and private institutions, and studying how the CBR problem solving method can be used in forecasting and, possibly, avoiding, enterprise bankruptcy.
He is involved, as Programme Committee Member, in the organization of many International Conferences in the Knowledge Management and related research areas: in particular, he is one of the founders of the Metadata and Semantics Research Conference Series (MTSR) which aims to bring together scholars and practitioners that share a common interest in the interdisciplinary field of metadata, semantics, linked data and ontologies. He is Associate Editor of Program, an inter-disciplinary journal covering Computing and Information Science and also the Social Sciences in general and any other discipline that is concerned with digital data. Moreover, he serves as reviewer for many journals related to different topics of Computer Science.
He belongs to the Committee of International Experts of the doctoral programme “Knowledge and Information Engineering” of the Computer Science Department at the University of Alcalà (Spain).
Dr. Marco Savi
Marco Savi is a Tenure-Track Assistant Professor (RTD-B) at University of Milano-Bicocca (Milano, Italy).
He received my BSc (2010) and MSc (2012, summa cum laude) in Telecommunications Engineering (Networking area) both from Politecnico di Milano (Milano, Italy). His master thesis investigated users’ privacy concerns in a Smart Grid scenario.
In June 2016 he pursued a PhD degree in Information Technology at Politecnico di Milano. During his PhD studies he worked on Content Delivery and on the emerging Network Function Virtualization (NFV) paradigm.
From March 2016 to March 2020 he worked with Fondazione Bruno Kessler (Trento, Italy) initially as Postdoc Researcher, being promoted to Expert Researcher in 2018. He was involved on several research topics including Fog Computing, Network Monitoring, SDN Multi-layer Networks and NFV.
In April 2020 He joined the Department of Informatics, Systems and Communication (DISCo) of University of Milano-Bicocca as Non-Tenured Assistant Professor (RTD-A), becoming Tenure-Track Assistant Professor (RTD-B) in November 2022. He is currently working on various topics related to computer networking, including Serverless Computing applied to NFV, Programmable Data Planes for Network Monitoring and Machine Learning applied to Network Security. He also carries on teaching activities.
He has published more than 50 peer-reviewed papers in reputed international journals and conferences.
Dr. Giulia Cisotto
Giulia Cisotto is a Non-Tenured track Assistant Professor (RTD-A) at University of Milano-Bicocca (Milano, Italy).
She received her BSc (2007) in Information Engineering and MSc (2010) in Telecommunications Engineering (Signal Processing area) both from the University of Padova (Padova, Italy). Her master thesis was focused on the development of algorithms to process and classify electroencephalographic (EEG) signals in ALS patients.
In January 2014, she pursued a PhD degree in Information Engineering at the University of Padova. During her PhD, she was also research fellow of the IRCCS “San Camillo” Hospital Foundation of Lido of Venice (Venice, Italy), and worked on the development of algorithms for EEG processing for different neurological patients with cognitive and motor impairments, and particularly for a brain-computer interface (BCI) system for stroke patients.
From April 2014 to March 2015 she was Research Associate at Keio University (Tokyo, Japan) and research fellow of the NCNP research hospital of Tokyo, where she developed a system to simultaneously record EEG and EMG signals and software tools to jointly analyze these data in healthy individuals and patients.
In March 2015, she joined the Department of Information Engineering of the University of Padova as post-doc research fellow, becoming Non-Tenured Assistant Professor (RTD-A) in March 2019. During that period she continued her investigations on signal processing and machine learning methods to analyze EEG and EMG signals for different applications, mainly for neuroscience and motor rehabilitation.
In January 2022, she joined the Department of Informatics, Systems and Communication of the University of Milano-Bicocca as Non-Tenured Assistant Professor (RTD-A), under the PON Initiative 2014-2020 action IV.6 funded by the Italian Ministry of University and Research.
She has published about 50 peer-reviewed papers in reputed international journals and conferences.Since 2018, she has belonged to the “E-Health” Technical Committee of the IEEE Communication Society.
In 2022, she was elevated to the IEEE Senior member grade. Since 2022, she also joined the Milan Center for Neuroscience (NeuroMI).Her current research interests include the development of machine learning models for EEG, EMG, and near-infrared spectroscopy (NIRS) data to detect and predict anomalies in complex systems, e.g., neuroscience and smart agrifood.
Since 2015, she has been intensively involved in teaching and educational activities, having supervised about 50 BSc/MSc theses and taught several BSc/MSc courses.
Since 2017 she has been Professor of the “E-Health” MSc course at one of the Master programs of the Dept. of Information Engineering at the University of Padova. She also teaches other courses at the Dept. of Informatics, Systems and Communication of the University of Milano-Bicocca.
Prof. Riccardo Melen
Riccardo Melen was a Full Professor of Computer Science at Università di Milano Bicocca (formerly he was at Politecnico di Milano and Università dell’Insubria). His research interests include mobile applications and services, event management, security and authentication systems. He is the author of more than 60 papers published on international journals or conference proceedings.
In 2000, as a consultant for the Italian Regulation Authority for Telecommunications (AGCOM), he defined the technical specifications for the local loop unbundling regulation in the Italian network.
In 2003, as a consultant for the Ministry of Innovation, he has been responsible for the definition of the architecture of the new network for the interconnection of Italian Public Administrations (SPC).
In 2009 he was the co-founder of NFC Alias, a university spinoff company dedicated to the development of NFC applications.
He has been working as a consultant for various companies: among others for Telecom Italia, Fastweb, Cisco Systems and HP. He has also performed evaluations of start-up companies for venture capital funds and other investors.
In his previous experience in the industry, as a researcher and laboratory head at CSELT (the former research unit of Telecom Italia) he was involved in the design and performance evaluation of multiprocessors and was the main system designer of an experimental broadband packet switching systems realized in CSELT in the period 1987-90.
Jacopo Talpini is a PhD student in Computer Science at “Università degli Studi di Milano-Bicocca”.
He received his BSc in Physics from “Università degli Studi di Milano” in 2018. Then, he obtained a MSc in Astrophysics at “Università degli studi di Milano-Bicocca” with a grade of 110/110. His master thesis project was focused on applying deep learning methods to characterize transient noise in gravitational-wave detectors.
His research interests include machine learning and its applications to solve real-world problems, in particular related to cyber-security.
We have a number of available theses for both Bachelor and Master students.
Check them out and contact us!
Dynamic Decision Networks for Modelling and Supporting Training Programs
Responsible: Fabio Sartori
Analysis of Data Collected from Wearables
Responsible: Fabio Sartori
Serverless Computing Applied to Networking
Serverless Computing is a novel cloud computing method where code is executed in a virtual environment and triggered by events. The advantages of adopting it for the execution of network functions (NFs) has not been thoroughly investigated yet, even though it is well-suited for those control-plane functions requiring the execution of simple and repetitive tasks (e.g. users’ authentication). The student will explore the feasibility of such an approach to some existing NFs.
Responsible: Marco Savi
Privacy-preserving Artificial Intelligence in Multi-access Edge Computing
Multi-access edge computing (MEC) is a recent architecture pushing cloud computing capabilities to the edge of the network. Availability of computation at the edge enables the possibility to execute many Artificial Intelligence tasks in a distributed and privacy-preserving fashion, thanks to a paradigm called Federated Learning. The student will investigate the possibility to exploit Federated Learning in such a scenario to support innovative services while preserving users’ privacy.
On these topics it is possible to do a stage and prepare the Master thesis in collaboration with Inria, in the group of Dr. Giovanni Neglia (http://www-sop.inria.fr/members/Giovanni.Neglia/) and at their premises at Sophia-Antipolis
(France). The period will last at least 6 months and a partial reimbursement of expenses will be granted.
Responsible: Marco Savi
Automated Service Provisioning in SD-WAN
SD-WAN is a very promising technology to establish reliable and cost-effective connectivity across the different sites of a company, in substitution of existing (and expensive) MPLS tunnels. Many SD-WAN products are currently available on the market, but they rely on very simple strategies with respect to service creation and differentiation. The student will investigate novel approaches to improve existing SD-WAN solutions, with the goal of making them more flexible in the provisioning of heterogeneous services, by also exploiting techniques such as Network Tomography (i.e., ability to infer an underlay topology by collecting metrics from an overlay network).
Responsible: Marco Savi
Programmable Data Planes for Advanced Network Monitoring
In Software-Defined Networking, programmable data planes enable switches to perform complex operations on packet headers and to collect advanced statistics on the network traffic, going beyond simple frame forwarding. One of the most adopted domain-specific programming languages in this context is the P4 language, which can be adopted to program the switches’ data plane behavior to support novel protocols and features. The student will investigate novel strategies for an enhanced collection of network monitoring metrics (e.g. latency, packet loss, number of active network flows, etc.) in data-plane programmable networks, using the P4 language.
Responsible: Marco Savi
AI-based Commodity Cost Forecasting for Price Fixing (in collaboration with Energy Saving)
The student will create an Artificial Intelligence (AI)-based system for short-term commodity (e.g. energy, gas, etc.) cost forecasting, with the goal of identifying the most opportune time window where to buy the commodity at fixed price, and alerting the system operator(s). The thesis will be done in collaboration with Energy Savings (Monza). The student will have the opportunity to spend some time in the Energy Savings’ headquarter, and will have the chance to access real data, made available by the company.
Responsible: Marco Savi
Research on 5G Networks and Beyond (in collaboration with Athonet)
Athonet (Vicenza) is a leading company on virtualized mobile network solutions. A bunch of thesis/stages is available. Especially, depending on the student’s skills and interest, we can offer:
– The possibility to experiment (hands on) with industry leading products (e.g. virtualized Evolved Packet Core, virtualized 5G Core, AWSm etc.)
– The possibility to perform industrial and standardization-oriented research (e.g. 3GPP, ETSI MEC, ETSI MANO, etc.)
Responsible: Marco Savi
Applied Research on Internet of Things and Multi-access Edge Computing (in collaboration with Storm Reply)
A wide set of theses and stages (Bachelor and Master) is available. The student will have the opportunity to closely work with Storm Reply employees on projects related to the application of Internet of Things and Multi-access Edge Computing concepts to real-world innovative use cases, while experimenting on production-grade technologies (e.g. AWS Wavelength). Especially, we can offer theses and stages on use cases such as:
– Smart buildings (e.g. definition of algorithms for energy provisioning balancing)
– Connected vehicles (e.g. definition of algorithms for smart energy exchange between charging points and vehicles to increase battery life, application of Multi-access Edge Computing for urban georeference alerting, collision prevention, traffic enhancement, autonomous driving, etc.)
Responsible: Marco Savi
Here you can find the courses we teach.
Related to the area of Communication Networks: “Telecommunications Systems and Services”, Master Degree in Computer Science, 1st year
Related to the area of Communication Networks: “Networks and Operating Systems”, Bachelor Degree in Computer Science, 2nd year (Teacher: Marco Savi)
Here you can find the list of our papers.
J. Talpini, F. Sartori, M. Savi, “A Clustering Strategy for Enhanced FL-Based Intrusion Detection in IoT Networks”, to appear in International Conference on Agents and Artificial Intelligence (ICAART), Feb. 2023
F. Sartori, M. Savi, K. Shala, A. Moglia and J. Talpini, “Knowledge Artifacts to Support Dietary: the Diet Module of the PERCIVAL Project”, in International Conference on Metadata and Semantics Research (MTSR), Nov. 2022
Damu Ding, Marco Savi, Domenico Siracusa, “Tracking Normalized Network Traffic Entropy to Detect DDoS Attacks in P4”, in IEEE Transactions on Dependable and Secure Computing, vol. 19, no. 6, pp. 4019-4031, Nov. 2022
Sebastian Troia, Marco Mazzara, Marco Savi, Ligia Maria Moreira Zorello, Guido Maier, “Resilience of Delay-sensitive Services with Transport-based Monitoring in SD-WAN”, in IEEE Transactions on Network and Service Management, vol. 19, no. 3, pp. 2652-2663, Sept. 2022
Laura Galluccio, Christian Grasso, Guido Maier, Raoul Raftopoulos, Marco Savi, Giovanni Schembra, S. Troia, “Reinforcement Learning for Resource Planning in Drone-Based Softwarized Networks”, in Mediterranean Communication and Computer Networking Conference (MedComNet), Jun. 2022
Fabio Sartori, Marco Savi, Jacopo Talpini, “Tailoring mHealth Apps on Users to Support Behavior Change Interventions: Conceptual and Computational Considerations”, in Applied Sciences, vol. 12, no. 8, pp. 1-19, Apr. 2022
Damu Ding, Marco Savi, Federico Pederzolli, Domenico Siracusa, “Design and Development of Network Monitoring Strategies in P4-enabled Programmable Switches”, in IEEE/IFIP Network Operations and Management Symposium (NOMS), Apr. 2022
Marco Savi, Alessandro Banfi, Alessandro Tundo, Michele Ciavotta, “Serverless Computing for NFV: Is it Worth it? A Performance Comparison Analysis”, in IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Mar. 2022
Michele Ciavotta, Davide Motterlini, Marco Savi, Alessandro Tundo, “DFaaS: Decentralized Function-as-a-Service for Federated Edge Computing”, in IEEE International Conference on Cloud Networking (CloudNet), Nov. 202Damu Ding, Marco Savi, Domenico Siracusa, “Tracking Normalized Network Traffic Entropy to Detect DDoS Attacks in P4”, to appear in IEEE Transactions on Dependable and Secure Computing, Sept. 2021
Marco Savi, Fabrizio Olivadese, “Short-Term Energy Consumption Forecasting at the Edge: A Federated Learning Approach”, in IEEE Access, vol. 9, pp. 95949-95969, Jul. 2021
Riccardo Berto, Paolo Napoletano, Marco Savi, “A LoRa-Based Mesh Network for Peer-to-Peer Long-Range Communication“, in Sensors, vol. 21, no. 13, pp. 1-12, Jun. 2021
Damu Ding, Marco Savi, Federico Pederzolli, Mauro Campanella, Domenico Siracusa, “In-Network DDoS Victim Identification Using Programmable Commodity Switches”, in IEEE Transactions on Network and Service Management, vol. 17, no. 2, pp. 1191-1202, Jun. 2021
Damu Ding, Marco Savi, Federico Pederzolli, Domenico Siracusa, “INVEST: Flow-based Traffic Volume Estimation in Data-plane Programmable Networks”, in IFIP Networking Conference, Jun. 2021
Joaquin Alvarez-Horcajo, Isaias Martinez-Yelmo, Diego Lopez-Parajes, Juan Antonio Carral, Marco Savi, “A Hybrid SDN Switch Based on Portable P4 Code”, in IEEE Communications Letters, vol. 25, no. 5, pp. 1482-1485, May 2021
Fabio Sartori, Marco Savi, Riccardo Melen, “The Role of Data Storage in the Design of Wearable Expert Systems”, in International Conference on Metadata and Semantics Research (MTSR), Dec. 2020
Petar Kochovski, Vlado Stankovski, Sandi Gec, Francescomaria Faticanti, Marco Savi, Domenico Siracusa, Seung Woo Kum, “Smart Contracts for Service-Level Agreements in Edge-to-Cloud Computing”, in Journal of Grid Computing, vol. 18, no. 4, pp. 673-690, Dec. 2020
Marco Savi, Fabio Sartori, Riccardo Melen, “Rethinking the Design of Wearable Expert Systems: The Role of Network Infrastructures”, in IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Aug. 2020
Antonio Marsico, Marco Savi, Domenico Siracusa, Elio Salvadori, “An Automated Negotiation Framework for Application-Aware Transport Network Services, in Elsevier Optical Switching and Networking”, vol. 38, pp. 1-13, 2020
Francescomaria Faticanti, Marco Savi, Francesco De Pellegrini, Petar Kochovski, Vlado Stankovski, Domenico Siracusa, “Deployment of Application Microservices in Multi-Domain Federated Fog Environments”, in IEEE International Conference on Omni-layer Intelligent Systems (COINS), 2020
Joaquin Alvarez-Horcajo, Elisa Rojas, Isaias Martinez-Yelmo, Marco Savi, Diego Lopez-Parajes, “HDDP: Hybrid Domain Discovery Protocol for Heterogeneous Devices in SDN”, in IEEE Communications Letters, vol. 24, no. 8, pp. 1655-1659, 2020
Damu Ding, Marco Savi, Domenico Siracusa, “Estimating Logarithmic and Exponential Functions to Track Network Traffic Entropy in P4”, in IEEE/IFIP Network Operations and Management Symposium (NOMS), 2020
Fabio Sartori, Riccardo Melen, “Wearable expert system development: definitions, models and challenges for the future”, Program 51(3), 235-258, 2017
Fabio Sartori, Alice Mazzucchelli, Angelo Di Gregorio, “Bankruptcy forecasting using case-based reasoning: The CRePERIE approach”, Expert Syst. Appl. 64, pp. 400-411, 2016
Dario Baretta, Fabio Sartori, Andrea Greco, Riccardo Melen, Fabio Stella, Letizia Bollini, Marco D’addario, Patrizia Steca, “Wearable devices and AI techniques integration to promote physical
activity”, MobileHCI Adjunct 2016, pp.1105-1108, 2016
Riccardo Melen, Fabio Sartori, “Employing Knowledge Artifacts to Develop Time-depending Expert Systems”, Communications in Computer and Information Science, Springer-Verlag, 2015
Riccardo Melen, Fabio Sartori, “Time Evolving Expert Systems Design and Implementation: the KAFKA Approach”, KEOD 2015, Lisbona (Portugal), 2015
Riccardo Melen, Fabio Sartori, Luca Grazioli, “Modeling and Understanding Time-Evolving Scenarios”, Journal on Systemics, Cybernetics and Informatics, Vol. 13, No. 5, 2015
Alice Mazzucchelli, Fabio Sartori, “String Similarity in CBR Platforms: A Preliminary Study”. MTSR 2014, pp. 22-29, 2014
Elisabetta Fersini, Fabio Sartori, “Semantic storyboard of judicial debates: a novel multimedia summarization environment”, Program 46(2), pp.199-219, 2012
Elisabetta Fersini, Fabio Sartori, “Improving the Effectiveness of Multimedia Summarization of Judicial Debates through Ontological Query Expansion”, CAiSE Workshops 2011, pp.450-463, 2011
Fabio Sartori, Matteo Palmonari, “Query Expansion for the Legal Domain: A Case Study from the JUMAS Project”, ONTOSE 2010, pp.107-122, 2010
Stefania Bandini, Federica Petraglia, Fabio Sartori, “Using knowledge artifacts to support work and learning: a case study”, IJKL 5(5/6), pp. 389-403, 2009
Fabio Sartori, Federica Petraglia, Stefania Bandini, “Knowledge Artifacts Modeling to Support Work and Learning in the Knowledge Society”, WSKS (1), pp.564-573, 2009
Stefania Bandini, Paolo Mereghetti, Esther Merino, Fabio Sartori, “Case-Based Support to Small-Medium Enterprises: The Symphony Project”, AI*IA, pp.483-494, 2007
For further information you can contact us at the following email addresses.
Fabio Sartori: fabio[dot]sartori[at]unimib[dot]it
Marco Savi: marco[dot]savi[at]unimib[dot]it
Riccardo Melen: riccardo[dot]melen[at]unimib[dot]it