Computer engineering

Security in networked computing systems (9 cfu)

• The objective of this course is to introduce the theorethical background and the basic methodologies and solutions to develop secure distributed applications. The course enables the students to design and implement secure distributed applications in several application domains including electronic payments, enterprise and e-health.
  This course is organized in three parts addressing different issues . Part 1 (algorithms). Part 2 (protocols). Part 3 (applications).
  
  
  
  

Concurrent and distributed systems (9 cfu)

• The objective of this course is to teach the theoretical background and the basic methodologies for developing time sensitive applications with high degree of concurrency and a set of performance requirements. The course enables the students to design and analyze real-time software in several application domains, as sensory monitoring, robotics, avionics, automotive, multimedia, and biomedical systems.

Intelligent Systems (6 cfu)

• This course aims to offer students with the opportunity to learn the basic concepts and models of computational intelligence, to have a thorough understanding of the associated computational techniques, such as artificial neural networks, fuzzy systems and genetic algorithms, and to know how to apply them to a wide variety of application areas.
  The major focus of the course will be on the use of intelligent systems to tackle problems not well solved by traditional approaches to computing.
  

Performance evaluation of Computer Systems and networks (9 cfu)

• Main aim: modelling and analysis of queuing systems, with applications in networking, computers, and services. Topics include discrete-time and discrete-state Markov chains, birth-death processes and simple Markovian queues, networks of queues and product form networks, single and multi-server queues. The course will cover state of the art results leading to research opportunities. Discrete-time simulation will be also thoroughly developed as a technique for assessing the performance of computers, networks and services.
  The course is in three parts.
  Part 1: review of all the prerequisites from applied probability that are needed for a basic course in queuing systems.
  Part 2: Explores both the theory and application of fundamental and advanced queuing models.
  Part 3: The basic principles of discrete-event simulations, covering simulation workflow, data structures used in simulation, random variable generation, transient elimination and output data analysis.
  

Electronics and communications Systems (9 cfu)

• The aim of the course is twofold, as it is organized in two modules.
  In the first module, the objective is to enable students to master digital integrated circuit design trade-offs. Experience state-of-the-art electronic design automation tools and high-level design methodologies for FPGA and semi-custom technologies. Understand sensor based electronic systems including sensor measurements, conditioning and sensor data fusion.
  In the second module, the objective is to describe the main architectural features and the underlying technology of the communication systems and equipment that is used in the field of networking, and to provide specific examples of communication systems using such technologies. In particular, the students i) will build-up a general knowledge of the basic technologies that enable the design of wired (copper, fiber) and wireless communication systems; ii) will bear a specific knowledge of the main standard for communications in the transport and access network, and iii) will evaluate the relevance of such standards and technologies in the general context of a wide-area digital communications and computing network.
  

Advanced topics in computer systems and networks (9 cfu)

• The course has two objectives. First, it covers theoretical and practical aspects related to data structures and algorithms, data compression, networking and operating systems. Second, it aims to give students a significant hands-on experience in application and system programming, through lab experiments and by requiring the submission of 2-3 group projects, including the modification of some existing application.
  The course is organized in three main parts: Part 1 deals with data compression, covering fundamental algorithms for lossless compression .
  Part 2 deals with systems programming.
  Part 3 covers advanced networking topics.
  Finally, the lab part covers a number of tools to help in the development and performance evaluation of efficient and portable software.
  

Computer architecture (9 cfu)

• Il corso presenta l’organizzazione dei sistemi informatici ad alte prestazioni e le metodologie utilizzate per progettare e valutare tali sistemi. In particolare, vengono descritti i processori ad alte prestazioni, i sistemi multiprocessore, sia in modalità on chip che distribuita (DSM, Cluster, Grid, Cloud), e le necessarie infrastrutture di supporto (memorizzazione, storage, interconnessione, e virtualizzazione). L’applicazione di tali sistemi viene mostrata nella realizzazione di varie tipologie di servizi Enterprise, con accento sulle architetture e le metodologie di valutazione. Le tecniche per realizzare e valutare l’usabilità di sistemi e servizi informatici completano il programma.

Advanced Network Architectures and Wireless Systems (9 cfu)

• a) Scheduling algorithms, protocols and architectures to handle Quality of Service in the Internet; b) Multihop wireless systems with specific emphasis on mesh wireless networks and LTE; c) The Internet as a complex system;
  The course is in four parts.
  Part 1: Protocol and architectural issues.
  Part 2: Issues related to a wireless multi-hop environment and how they are reflected in the design of mesh network systems and long term evolution systems. .
  Part 3: Internet of Things.
  Part 4: The Internet as a complex network.
  

Free activity (9 cfu)

Final examination (18 cfu)

Mobile and Pervasive Systems (6 cfu)

• The course enables the students to understand the properties, architectures and application areas of mobile and pervasive distributed systems, and to learn the basic methodologies for designing applications using different mobile and pervasive platforms.
  The course is organized in lectures and laboratory sessions.
  In laboratory sessions students will exercise with mainstream technologies for designing smartphones-based client applications and wireless sensing applications. Mobile applications and their integration with the back-end servers will be developed using different platforms (e.g., JME, Android, iOS).
  

Information systems and Software systems engineering (12 cfu)

• The aim is to show advanced techniques for designing database management systems and software systems. This course is organized in two sections addressing different issues in the design of software systems.
  The first section provides advanced databases management systems topics to be used in the context of information systems. The second part addresses software system development issues taking account the quality of both the development process and the produced system.

Automated systems and robotics (6 cfu)

• The objective of this course is to introduce the basic control theories for digital systems. The course introduces to physical modeling problems and reviews typical architectures for the control of electro-mechanical systems. The course will enable students to understand electronic circuits and design the related control software for the control of mechanical systems.

Concurrent and distributed systems (9 cfu)

• The objective of this course is to teach the theoretical background and the basic methodologies for developing time sensitive applications with high degree of concurrency and a set of performance requirements. The course enables the students to design and analyze real-time software in several application domains, as sensory monitoring, robotics, avionics, automotive, multimedia, and biomedical systems.

Electronics and communications Systems (9 cfu)

• The aim of the course is twofold, as it is organized in two modules.
  In the first module, the objective is to enable students to master digital integrated circuit design trade-offs. Experience state-of-the-art electronic design automation tools and high-level design methodologies for FPGA and semi-custom technologies. Understand sensor based electronic systems including sensor measurements, conditioning and sensor data fusion.
  In the second module, the objective is to describe the main architectural features and the underlying technology of the communication systems and equipment that is used in the field of networking, and to provide specific examples of communication systems using such technologies. In particular, the students i) will build-up a general knowledge of the basic technologies that enable the design of wired (copper, fiber) and wireless communication systems; ii) will bear a specific knowledge of the main standard for communications in the transport and access network, and iii) will evaluate the relevance of such standards and technologies in the general context of a wide-area digital communications and computing network.
  

Intelligent Systems (6 cfu)

• This course aims to offer students with the opportunity to learn the basic concepts and models of computational intelligence, to have a thorough understanding of the associated computational techniques, such as artificial neural networks, fuzzy systems and genetic algorithms, and to know how to apply them to a wide variety of application areas.
  The major focus of the course will be on the use of intelligent systems to tackle problems not well solved by traditional approaches to computing.
  

Security in networked computing systems (9 cfu)

• The objective of this course is to introduce the theorethical background and the basic methodologies and solutions to develop secure distributed applications. The course enables the students to design and implement secure distributed applications in several application domains including electronic payments, enterprise and e-health.
  This course is organized in three parts addressing different issues . Part 1 (algorithms). Part 2 (protocols). Part 3 (applications).
  
  
  
  

Supply chain and operations management (9 cfu)

• The course aim is to make the students able to
  a) Perform the correct choice to develop a suitable management system into a organization
  b) Use main methods for analyzing and sizing productive and logistic systems
  c) Use BPMN tools to model and simulate processes
  
  The main topics are the characteristics of different management system models. The critical analysis of the process approach management system. The main concepts concerning operations management (production, logistics, etc.).
  

Computer architecture (9 cfu)

• Il corso presenta l’organizzazione dei sistemi informatici ad alte prestazioni e le metodologie utilizzate per progettare e valutare tali sistemi. In particolare, vengono descritti i processori ad alte prestazioni, i sistemi multiprocessore, sia in modalità on chip che distribuita (DSM, Cluster, Grid, Cloud), e le necessarie infrastrutture di supporto (memorizzazione, storage, interconnessione, e virtualizzazione). L’applicazione di tali sistemi viene mostrata nella realizzazione di varie tipologie di servizi Enterprise, con accento sulle architetture e le metodologie di valutazione. Le tecniche per realizzare e valutare l’usabilità di sistemi e servizi informatici completano il programma.

Performance evaluation of Computer Systems and networks (9 cfu)

• Main aim: modelling and analysis of queuing systems, with applications in networking, computers, and services. Topics include discrete-time and discrete-state Markov chains, birth-death processes and simple Markovian queues, networks of queues and product form networks, single and multi-server queues. The course will cover state of the art results leading to research opportunities. Discrete-time simulation will be also thoroughly developed as a technique for assessing the performance of computers, networks and services.
  The course is in three parts.
  Part 1: review of all the prerequisites from applied probability that are needed for a basic course in queuing systems.
  Part 2: Explores both the theory and application of fundamental and advanced queuing models.
  Part 3: The basic principles of discrete-event simulations, covering simulation workflow, data structures used in simulation, random variable generation, transient elimination and output data analysis.
  

Final examination (18 cfu)

Information systems and Software systems engineering (12 cfu)

• The aim is to show advanced techniques for designing database management systems and software systems. This course is organized in two sections addressing different issues in the design of software systems.
  The first section provides advanced databases management systems topics to be used in the context of information systems. The second part addresses software system development issues taking account the quality of both the development process and the produced system.

Mobile and Pervasive Systems (6 cfu)

• The course enables the students to understand the properties, architectures and application areas of mobile and pervasive distributed systems, and to learn the basic methodologies for designing applications using different mobile and pervasive platforms.
  The course is organized in lectures and laboratory sessions.
  In laboratory sessions students will exercise with mainstream technologies for designing smartphones-based client applications and wireless sensing applications. Mobile applications and their integration with the back-end servers will be developed using different platforms (e.g., JME, Android, iOS).
  

Process-driven Information Systems (6 cfu)

• the course aims at providing knowledge and experience essential for designing and deploying enterprise information systems that are driven by process models. Students are trained on how to model and implement non-trivial software applications in a specific business process management system. The main topics are advanced process modeling and simulation: methods, notations and tools. Data models connected to workflow models. The model-driven approach and the business process execution. The evolution of enterprise systems architectures. Different languages are studied, showing how standards can fit into the picture.

Free activity (9 cfu)

Business Intelligence (9 cfu)

• The course aims to introduce the main concepts and techniques used in business intelligence for extracting and analyzing business data. In particular, the course will focus on the main aspects of data mining: data preprocessing, data warehouse, frequent pattern mining, classification, prediction, clustering and outlier detection.
  The course will deal in sequence with the following aspects related to data mining.
  Preliminary data analysis.
  Data Preprocessing.
  Data warehouse.
  Frequent pattern mining.
  Classification.
  Clustering.
  Outlier detection.