2023 Call


Requirements: students enrolled at the first semester of the second year of the MSc track, with 50 CFUs and 28 GPA



Research topics in Automation and Control Engineering

Proposer: Matteo Corno, Lorenzo Fagiano, Simone Formentin, Luigi Piroddi, Maria Prandini, Sergio Savaresi, Riccardo Scattolini, Mara Tanelli.
Topic: Theory and application of control systems
The research area includes all the topics related to the theory and application of modeling, control, identification and learning methods for dynamic systems. Applications include, but are not limited to, energy systems, smart grids, vehicles, finance.
Compatible tracks: ATM, CSE
Positions available: 3
Proposer: Renato Casagrandi, Patrizio Colaneri, Gian Paolo Incremona, Lorenzo Mari, Maria Pradini, Fabio Dercole
Topic: Modelling, optimization and control of complex systems
The research area includes all topics related to modelling, optimization and control for complex systems possibly interacting over a network or involving hybrid dynamics. Examples include social, biological, epidemiological, transportation and power networks.
Compatible tracks: ATM, CSE
Positions available: 3

Research topics in Electric Engineering

Proposer: Luca Di Rienzo
Topic: Electromagnetic modeling of submarine power cables
The transition towards renewable energy sources is tightly tied to the capability to transmit and dispatch energy from the production places to where it is consumed. Within this framework, underground and submarine cables for power transmission and distribution are an essential component of the global energy transition. The proper design of these power cables must take into account several different and often contrasting requirements and constraints and their accurate electromagnetic modeling is crucial. Computation of electric and magnetic losses, modeling of the electric field in the insulation material, and evaluation of the per unit length parameters are challenging tasks. The research work will contribute to the numerical implementation of new formulations that can model the involved electromagnetic phenomena.
Proposer: Flavia Grassi
Topic: Prediction models and test procedures to assure electromagnetic compatibility in the automotive sector
Assuring electromagnetic compatibility (EMC) performance of electronic components and communications systems installed on board hybrid and electric vehicles represents a great challenge for electrical/electronics engineers. For this reason, the development of prediction models and test procedures to provide reliable estimates (also in statistical terms) of the expected levels of interference is desirable in order to support the design of electrical and electronic components and subsystems starting from the early design stages. The research activity that will be proposed to the student will contribute to the research activities currently carried out by the EMC group in this field, and will be focused more on modeling/simulation rather than on experimental activity depending on the specific student interests.

Research topics in Electronic Engineering

Proposers: Giuseppe Bertuccio
Topic: Semiconductor Radiation Detectors and Integrated Circuits for Scientific Applications
Semiconductor Radiation Detectors (SRD) are widely employed in fundamental sciences and have numerous medical and industrial applications. The continuous increase in complexity and performance of new SRD require advances in Application Specific Integrated Circuits (ASIC) for signal readout and processing. The research activity can be directed through one of these two paths: 1) the theoretical and experimental study of the most advanced semiconductor radiation detectors in Silicon and in Compound Semiconductors (GaAs, CdTe, CdZnTe, SiC) or b) the design of low-noise and low-power CMOS ASIC for SRD. Both topics are oriented to applications toward Synchrotron X-ray sources and Space Telescopes for Astrophysics or to non-destructive material analysis in Industries. The research activities are made in collaboration with the National Institute for Nuclear Physics (INFN), the National Institute for Astrophysics (INAF), the Italian Space Agency (ASI), the European Space Agency (ESA), Elettra Synchrotron in Trieste and some Companies.
Proposers: Marco Carminati, Carlo Fiorini
Topic: Development of innovative detection systems and readout ASICs for fundamental physics and medical imaging applications
The student will be involved in stimulating team activity carried out within international collaborations and concerning the development of innovative detection systems and readout ASICs to be used in experiments for both fundamental physics (nuclear physics, neutrinos search, X-ray astronomy) and applied physics (analytical instrumentation for material analysis, industrial applications). Projects of the team regard also the development of sensors and electronics for medical imaging applications. During the program, the student will have the opportunity to contribute to the development of a broad range of components, circuits and systems, from radiation sensors, to low-noise integrated circuits, to data acquisition systems, to a complete instrument ans its use in the target application.
Positions available: 2
Proposers: Andrea Castoldi
Topic: Developement of novel Germanium Drift Detectors
The study and development of Germanium detectors with 'drift' topology is a research topic that can give a break-through in the field of imaging and spectroscopy of X- and gamma-rays. Germanium is one of the purest semiconductor crystals available today with excellent carrier transport properties and high detection efficiency of X and gamma rays that makes it the ideal candidate for such task. The design of novel 'drift' topologies, i.e. based on 3D shaping of the electric field inside the semiconductor volume, combined with the unique material properties has the potential of unprecedented low-noise performance on a wide energy range. The student will be involved in the team work in the development of prototypes of Germanium drift detectors and of the low-noise readout electronics with a broad range of activities from device simulation, experimental characterization as well as data analysis.
Proposers: Giorgio Ferrari
Topic: Neuromorphic hardware for an energy-efficient brain-inspired computation
Many recent successes of artificial intelligence have been achieved using artificial neural networks that are loosely inspired by the brain's functioning and implemented as software on high-performance computers with a traditional architecture. However, their energy-intensive nature hinders their use in portable and compact autonomous systems. To overcome this challenge, the research explores radically different hardware architectures inspired by biological models, particularly focusing on energy-efficient neuromorphic systems employing physical neurons for computation. In this context, the research at the I3N laboratory of the Politecnico di Milano is dedicated to developing neuromorphic circuits in CMOS technology. These circuits feature neurons and synapses implemented through compact analog circuits, targeting very low power consumption and long-term memory. The research encompasses both the electronic design of the chip and the learning methodologies more suitable for these neural networks, taking into account the constraints imposed by their physical implementation and exploring potential enhancements given by the electronic noise inherent in analog approaches.
Proposers: Chiara Guazzoni
Topic: Development of an innovative high-rate tagging system for radioactive beams
The activity proposed to the candidates frames in the upgrade of the superconducting cyclotron of INFN (Istituto Nazionale di Fisica Nucleare), at Laboratori Nazionali del Sud, in Catania (Italy) towards high-luminosity radioactive beams for nuclear physics experiments. Politecnico di Milano research staff, in collaboration with INFN, Sezione di Milano, Sezione di Catania and Laboratori Nazionali del Sud, is in charge of the development of a high-rate radiation-tolerant tagging system, equipped with a dedicated frontend. The research project is going on and will last till 2025-2026, therefore there is adequate time span for a M.Sc. and also a following PhD activity or just a M.Sc activity. The student(s) will collaborate in the detector qualification, frontend design and qualification, interconnection and mechanical assembly design and in the full detection system modeling. Last but not least the student(s) will take part in the beam tests. The first one is already scheduled for March 2024 at GSI in Darmstadt and others will follow. Aside the experimental activity a full position is available dedicated to detector simulation. The system will also have biomedical interest as it will be used to qualify radioactive beams for combined diagnosis and treatment in radiotherapy. The students (up to 3) will have the possibility to shape the focus of the research activity according to their skills and interests and to work independently on different aspects of the project or jointly collaborate. The student(s) will have the possibility to work in a real research lab, with hands-on approach combined with a strong theoretical background in the field of radiation detectors and low-noise frontend electronics, sharing the daily lab life with PhD students, junior and experienced researchers.
Proposers: Angelo Gulinatti, Ivan Rech
Topic: Single-photon detectors and applications
Recently, the field of single-photon detection has experienced an exponential growth due to the emergence of a large number of scientific and industrial applications that require the capability of detecting the light down to the single-photon level. Among them are laser ranging, single-molecules analysis, and optical quantum computing, which are regarded as key enabling technologies to address some of today?s most challenging problems like the development of new drugs, the study of climatic changes and the autonomous driving. The Single-Photon Avalanche Diode (SPAD) has emerged as the detector of choice for these applications thanks to its remarkable performance. However, many progresses are still needed to bring these applications in everyday life. The research activity is aimed at addressing these limitations by developing innovative solutions for the detection of single photons with unprecedented capabilities in terms of photon detections efficiency, timing jitter, spectral sensitivity, and integrability into large arrays of detectors. The activity will involve one or more of these fields: design and simulation of new detector structures, study and modeling of unexplored detector properties, development of new experimental characterization techniques, design of new front-end circuitry, development of application specific architectures.
Positions available: 2
Proposers: Daniele Ielmini, Christian Monzio Compagnoni, Alessandro Spinelli
Topic: Emerging memory devices and in-memory computing
The future evolution of integrated electronictechnologies will see a closer interaction of logic and memory devices, overcoming the traditional design schemes in the attempt to constantly reduce power consumptions and improve system performance. This is today triggering the research both on new, fast and energy-efficient memory devices that could be integrated directly in logic processes and on new computational forms that could be directly performed inside memory arrays. The proposed projects for the Honours Program will make contributions to these two research lines. In the former, activities will be focused on the experimental, numerical and theoretical investigation of the basic physics, the working principles and the performance of emerging memory devices, such as nanoscale ferroelectric memories and magnetoresistive memories. In the second, in-memory computing will be investigated both theoretically and experimentally, focusing on hardware neuromorphic systems exploiting different types of memory arrays, e.g., floating-gate, resistive and phase-change arrays, as artificial synaptic arrays. The results of the projects will pave the way to the future evolution of micro and nanoelectronics.
Positions available: 3
Proposers: Dario Natali
Topic: Plastic Electronics
Organic semiconductors are carbon-based compounds that can be conveniently processed from solution at almost room temperature. As a consequence, it is possible to manufacture devices, circuits and systems by means of non-lithographic techniques, such as inkjet printing, screen printing, flexography to cite but a few. The benefits of printed electronics include: low cost, mechanical flexibility, ease of production and integration, and the possibility of addressing a variety of non-conventional applications: flexible displays, image sensors, bio-sensors, smart labels, RF-ID tags, edible electronics, wearable electronics, and more. The research encompasses all the aspects, issues and challenges of plastic electronics: the fundamentals of charge carrier transport related to the energetically disordered landscape sampled by carriers; device modeling and simulation through innovative ad-hoc developed codes; printing process engineering; logic, analog, optoelectronic circuits and systems design, realization and characterization.
Proposers: Marco Sampietro
Topic: Integrated electronic systems for the control of optical computers
: Integrated electronic systems for the control of optical computers Manipulation of light in waveguides produced on a silicon layer with the same microelectronic technology used for electronic chips opens the realm of optical computing. For the scenario to be realistic, many difficulties should be overcome, the principal being the strong thermoptic coefficient of Silicon that prevent Silicon Photonics to be operated in open loop. Our research targets this aspect by designing and operating electronic systems for the control of Photonic chips in a close loop configuration. To this goal non-invasive monitoring devices to inspect the light inside optical waveguides will be developed as well as integrated electronic architectures that detect these signals and perform feedback control. The electronics will be mixed-signal integrated chips tailored to the photonic chips for the stabilization and setting of its operation. Flip-chip mounting will be explored as well as direct integration of electronic functionalities into the same photonic chip, in a truly integrated optical computer system.
Proposers: Alberto Tosi, Federica VillaFranco Zappa
Topic: Microelectronics, devices, and electronic systems for LiDAR, quantum physics and bioimaging
1. "ELECTRON DEVICES: design, simulation, and fabrication of single-photon detectors in Si, InGaAs/InP and Ge". The research aims at conceiving new microelectronic sensors for detecting single photons in the 200nm-1,700nm range, with picosecond-timing precision. Different semiconductors (Si, Ge, InGaAs, InP, GaAs) and novel processing (planar, three-dimensional stacking, wafer-to-wafer bonding, vertically-grown micro-crystals) will be pioneered. Funding from European Commission “Horizon 2020”, “Horizon Europe” and “European Defense Fund” programmes, European Space Agency (ESA), USA DARPA agency, national funds.
2. MICROELECTRONICS: schematics, layout, fabrication and validation of ASIC chips for systems-on-chips". The research aims at integrating detector arrays, in-pixel mixed-signal electronics and on-chip digital processing into one single chip, for imagers providing 2D movies at high (>100,000 frames/s) rates, single-photon sensitivity, time resolved imaging for LiDAR and functional bioimaging, and photon coincidence for quantum physics applications. Different microelectronic technologies (CMOS, BCD, Si-Ge and 3D-stacked) and foundries will be exploited. Funding from “Horizon2020”, “Horizon Europe” and “European Defense Fund” EC programmes, NATO “Safety for Peace” programme, European Space Agency (ESA), JPL-NASA agency.
3. "ELECTRONIC SYSTEMS: development and system integration of advanced electronic systems for sensing and imaging". The research aims at prototyping electronic products with FPGA, µC, and DSP devices, for different applications (e.g., time-of-flight 3D automotive vision, quantum optics experiments, quantum computing chips, non-invasive biomedical parameter acquisitions). Various methodologies, hw/fw/sw co-partitions, devices (Xilinx, Altera, ARM-Cortex) and high-level languages will be exploited. Funding from JPL-NASA agency, European Southern Observatory, and European Space Agency).
Positions available: 3

Research topics in Computer Science and Engineering

Proposer: Francesco Amigoni
Topic: Multirobot Systems
Teams of cooperative robots can provide effective and efficient solutions for performing tasks in warehouses and in applications like environmental monitoring, search and rescue, and patrolling. Such multirobot systems present challenges in the development and learning of decision-theoretic planning tools to accomplish tasks with the appropriate level of autonomy.
Proposer: Salvatore Andolina
Topic: AI-driven Web Search
The AI revolution is redefining the way we acquire information. This thesis examines the potential of incorporating large language models (e.g., GPT-4/Bard) into modern search interfaces. It will involve designing, implementing, and evaluating novel human-centered AI tools that aim to boost search effectiveness while ensuring high levels of user control, safety, and trust.
Proposer: Danilo Ardagna
Topic: AI Application Management through Reinforcement Learning in Computing Continua
Reinforcement learning (RL) is promising to optimize AI applications running in edge systems. However, RL agents perform poorly during initial exploratory interactions with the environment.T he project goal is to develop a new framework leveraging prior knowledge to address this issue.
Proposer: Federica Arrigoni
Topic: Quantum Computer Vision
Many problems in Computer Vision can be solved with an adiabatic quantum computer (AQC) since they are natively combinatorial (NP-Hard). Examples include motion segmentation or matching features in multiple images. The aim of this thesis is to bring new vision tasks into an AQC while exploring its advantages and current challenges.
Proposer: Luciano Baresi
Topic: LLM for Requirements Elicitation
The first part of the work will comprise an exploratory study to discover how LLMs are used in the context of requirements elicitation. The second part will focus on the use of general-purpose LLMs to help analysts identify, ameliorate, and complete requirements properly.
Proposer: Anna Bernasconi
Topic: Data Science for Genomic Surveillance
Unprecedented availability of viral genomes on public databases makes it possible to explore viruses' evolution with data-driven methods. This thesis aims to develop data science workflows to support genomic surveillance of viral species (e.g., Ebola, Monkeypox, or Influenza).
Proposer: Andrea Bonarini
Topic: Physical metaverse
We would like to explore the limits of neuroplasticity to map sensor data, collected in the real world by a robotic avatar, into a virtual world based on VR and haptic devices. The aim is to reach the embodiment of the subject into a body with different interaction possibilities. The work is part of a multidisciplinary project including researchers and students from Design, Art and Psychology.
Additional team members: Federico Espositi
Proposer: Giacomo Boracchi
Topic: Object Detection Networks for Multiple Images and Point Clouds.
While object detection networks are meant for single images, most vision systems in medicine, security, and autonomous vehicles are multiview or multimodal. Let's design new deep NN and training procedures to boost object detection in these systems.
Proposer: Matteo Castiglioni
Topic: Online Learning in Economic Settings
Online learning is a powerful tool for the design of algorithms for sequential decision making. Recently, it has been successfully applied to many economic settings on the Web, such as advertising, information markets, and online auctions. This thesis aims at exploring new frontiers of online learning applications in such settings.
Proposer: Stefano Ceri
Topic: Automatic generation of reasoning tasks on knowledge graphs
The thesis aims to develop a pipeline that leverages and combines logic programming (Datalog) and NLP techniques to build a user-friendly interface that will allow non-technical users to perform reasoning tasks on a knowledge graph, starting from questions in natural language, using state-of art AI translation models.
Additional team members: Andrea Colombo, Pietro Pinoli
Proposer: Paolo Cremonesi
Topic: Off-Policy Evaluation and Learning from Bandit Feedback
Many real-world decision-making problems (e.g., recommender systems) can be viewed through the multi-armed bandit framework. While online learning has been extensively researched, there is a growing need to leverage offline data for evaluating and learning new policies. The project aims to explore approaches that exploit offline bandit feedback to improve decision-making in real-world scenarios.
Additional team members: Nicolò Felicioni
Proposer: Pietro Crovari
Topic: Data Science ChatBot
The project combines LLM, human-in-the-loop and interactive ML to create a human-computer interface, for trustworthy data analyses, involving users in requirements elicitation and decision process, benefiting users with limited computational skills.
Additional team members: Pietro Pinoli, Franca Garzotto
Proposer: Maurizio Ferrari Dacrema
Topic: Machine Learning for Quantum Computing
Quantum Computing (QC) has the potential to shape the future of high performance computing and Machine Learning (ML) applications thanks to the speed-ups it promises for certain tasks. However, ML techniques can also help to overcome some of QC's current technological limitations. This research aims to study how QC and ML can be best combined in practice and how they can be of help to each other.
Additional team members: Riccardo Nembrini
Proposer: Leandro Fiorin
Topic: In-Memory Computing for Deep Learning Accelerators
Digital In-Memory Computing (D-IMC) is a new paradigm to improve performance and energy efficiency of DL workloads by reducing the processor-to-memory data traffic. The thesis investigates the problem of system-level modeling and design space exploration of hardware accelerators based on D-IMC.
Proposer: Franca Garzotto
Topic: Large Language Models (LLMs) and Generative AI (GenAI) for persons with cognitive impairments
LLMs and and GenAI offer immense potential but pose a digital divide risk, one that separates those proficient in safely harnessing these technologies from those who cannot due to factors such as cognitive impairments. This thesis explores how LLMs and GenAI can aid the cognitively impaired. It develops innovative techniques and platforms for generating tailored, accessible conversations and multimedia content and for creating inclusive multimodal applications that enhance autonomy and learning.
Additional team members: Mattia Gianotti, Pietro Crovari
Proposer: Daniele Loiacono
Topic: Artificial Creativity: AI-powered Creative Content Generation
This thesis will explore the fusion of deep learning generative models and interactive evolutionary computation to generate creative content. The research will involve developing hybrid algorithms, optimizing human-computer interaction, and evaluating the quality and originality of generated artifacts. The aim is to advance creative content generation, with applications in games, art, music, desig
Additional team members: Pier Luca Lanzi
Proposer: Luca Magri
Topic: Computer Vision and Pattern Recognition
One of the long-term goals of Computer Vision is to design algorithms for perceiving and understanding the world acquired by imaging sensors. The aim of this thesis is to design new methodologies that exploit pattern recognition and geometric techniques to address relevant Computer Vision tasks, such as 3D reconstruction, motion segmentation, template detection, just to name a few examples.
Additional team members: Andrea Porfiri Dal Cin
Proposer: Alberto Marchesi
Topic: Multi-Agent Learning
Recently, machine learning techniques for multi-agent settings have received a growing attention. This lead to several breakthroughs in AI research, such as the development of superhuman bots for games like poker, go, and Starcraft. This thesis aims at designing multi-agent learning algorithms in new settings, with a particular focus on convergence guarantees and computationally efficiency.
Proposer: Alessandro Margara
Topic: Efficient Execution of Data-Intensive Applications in the Compute Continuum
Today, most software applications are data-intensive: they need to manage, analyze, and distribute large volumes of data in large-scale environments. The goal of this thesis is to contribute to the development of an efficient and scalable platform for the execution of data-intensive applications in Cloud-to-Edge Compute Continuum environments.
Additional team members: Gianpaolo Cugola, Luca De Martini
Proposer: Davide Martinenghi
Topic: Ranking Systems
The simultaneous optimization of different criteria (e.g., attributes of a database) is a ranking problem naturally arising in many scenarios, including recommender systems, machine learning, and meta-search. The aim of this study is to use ranking techniques to discover potentially interesting data and measure relevant properties of the result, such as bias and distribution.
Proposer: Marco Masseroli
Topic: AI and Data Science for Bioinformatics and Computational Genomics
Bioinformatics research focuses on life science big heterogeneous data and information, increasingly available in many different sources, and their best integration, mining and analysis with machine learning and deep learning techniques for knowledge discovery, to better understand complex biological phenomena and improve patient stratification for best diagnosis, prognosis and clinical treatment.
Additional team members: Silvia Cascianelli
Proposer: Maristella Matera
Topic: Large Language Models for a Conversational Web
Large Language Models (LLMs) can potentially improve Web access. Recent studies have proposed conversational AI to support Web browsing (https://tinyurl.com/ConWeb-CHI2023). This thesis will investigate the adoption of LLMs, e.g., OpenAI, to enhance dynamic dialog generation in conversational agents for Web browsing, with a focus on the transparency and explainability of Web content manipulation.
Additional team members: Emanuele Pucci, Ludovica Piro
Proposer: Alberto Maria Metelli
Topic: Learning from Demonstrations
Learning from Demonstrations (LfD) is a learning paradigm in which an agent acquires abilities by observing an expert (e.g., a human) acting in an environment. LfD has been successfully applied in real-world problems where devising a reward function is challenging (e.g., autonomous driving) or when expert demonstrations are easily available (e.g., human-in-the-loop).
Proposer: Antonio Miele
Topic: Combined Runtime resource management and application autotuning in heterogeneous multicore systems
Performance/energy-efficient execution of a multiprogrammed workload on heterogeneous multicore systems requires the adoption on runtime resource management approaches. This thesis studies runtime policies to tune both hardware and software knobs.
Proposer: Luca Mottola
Topic: The Battery-less Internet of Things
Energy harvesting is redefining the energy constraints of traditional battery-powered IoT devices. However, such sources of energy are generally erratic, causing systems to shutdown unpredictably. We devise new software techniques to render IoT software immune to periods of energy unavailability.
Proposer: Gianluca Palermo
Topic: High Performance Virtual Screening for Drug Discovery in Urgent Computing Scenario
The project wants to find solutions to accelerate the virtual screening process in drug discovery. The project considers the urgent computing scenario, similar to COVID-19, where the computation has to rely on HPC resources. Possible research directions are on code optimization strategies, exploitation of heterogeneous resources (e.g., GPUs) or quantum computers, and machine learning techniques.
Proposer: Matteo Papini
Topic: Hybrid Online/Offline Reinforcement Learning
Online Reinforcement Learning (RL) methods are powerful, but need to collect huge amounts of data in real time. Offline RL can learn from historical data, but sacrifices adaptivity. The idea of hybrid RL is to use data to accelerate the progress of online RL algorithms.
Proposer: Francesco Pierri
Topic: Large Language Models for (mis)information credibility evaluation
The problem of online mis/disinformation is of global concern. The proposed research aims to employ state-of-the-art Large Language Models to build agents that can verify and/or provide contextual information for unverified stories and rumors circulating online.
Proposer: Pietro Pinoli
Topic: Generative AI for genomic data augmentation
Data scarcity and privacy constraints hinder critical decision-making support tools for personalized medicine. This thesis explores using generative AI to create synthetic genomic data, fostering AI adoption in clinical settings.
Additional team members: Sofia Mongardi
Proposers: Giovanni Quattrocchi
Topic: Data Management for Edge Computing
Since edge nodes have limited capabilities, data management requires us to conceive novel solutions to distribute data, anticipate bottlenecks, ensure eventual consistency, and exploit available resources as much as we can. This work is intended to develop a novel solution to address these problems.
Proposers: Marcello Restelli
Topic: Reinforcement Learning
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. Reinforcement learning is rapidly gaining attention both from academic and industrial communities due to recent successes in a variety of sequential decision-making problems.
Additional team members: Alberto Maria Metelli
Proposers: Manuel Roveri
Topic: Tiny Machine Learning
Technological progress in Internet-of-Things has opened the way to a pervasive presence of distributed intelligent applications in our everyday lives. The research will focus on Tiny Machine Learning for the on-the-device training and recall of machine/deep learning models taking into account the constraints on computation, memory, and energy characterizing the hardware platforms.
Additional team members: Ing. Massimo Pavan
Proposers: Cristina Silvano
Topic: Mappings of DNNs to Hardware Accelerators
Recent trends in Deep Neural Networks imposed hardware accelerators for high-performance computing (HPC) applications. The thesis investigates the problem of the automatic exploration of mapping of DNN layers across the huge space of design parameters of DNN accelerators.
Proposers: Monica Vitali
Topic: Energy-aware design and deployment of cloud-native applications in fog computing
Cloud-native applications are a collection of independent microservices that interact in a workflow. This project aims to propose a novel approach for reducing the environmental impact of cloud-native applications in distributed fog environments by designing an adaptive scheduler capable of dynamically redesigning the execution workflow considering the currently available energy mix.