ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-12192016-101401


Tipo di tesi
Tesi di dottorato di ricerca
Autore
BIONDI, ELISABETTA
URN
etd-12192016-101401
Titolo
Optimization of smart city critical infrastructures: the case of communication network and transportation system
Settore scientifico disciplinare
ING-INF/05
Corso di studi
INGEGNERIA DELL'INFORMAZIONE
Relatori
tutor Prof. Mingozzi, Enzo
tutor Dott. Passarella, Andrea
tutor Dott.ssa Boldrini, Chiara
Parole chiave
  • electric vehicles
  • carsharing
  • intercontact times
  • duty cycle
  • smart city
  • optimization
Data inizio appello
21/01/2017
Consultabilità
Completa
Riassunto
Urban population growth and technological advancements have stimulated researchers to investigate innovative solutions that could improve the quality of life of people living in urban areas. All these research efforts strive towards a "smart city", i.e., a city that exploits information technology to address its problems, that values its human capital, and in which citizens and stakeholders collaborate to boost economic development. A smart city can be seen as a system of systems, meaning that it can integrate and optimize different interdependent elements (transportation system, communication networks, energy grid, etc.). This can be achieved through the development of an ICT platform, the Smart City Operating System, that allows the monitoring and managing of the different infrastructures. A key component of the Smart City Operating System will be a set of optimization tools that could assist the manager of the smart cities infrastructures in the monitoring and management. Within this framework, the focus of my thesis is the definition of models and optimisation tools for two critical infrastructures of a smart city: the communication network and the transportation system.

The communication network of a smart city will move from the current fourth-generation (4G) systems to a new generation (5G) better equipped for addressing a huge demand for mobile data. The growth in mobile traffic is already an on-going trend but it is expected to explode with the capillary diffusion of the Internet of Things (a strategical asset for turning cities into smart cities). 5G networks aim at addressing the exponential growth in mobile traffic using a blend of different strategies, among which mobile data offloading is one of the most promising. One approach to mobile data offloading is to exploit device-to-device WiFi or Bluetooth communications between the users of the network to disseminate popular content without relying exclusively on the cellular infrastructure. Unfortunately, these device-to-device communications tend to consume a lot of battery, and this would discourage users from cooperating in the offloading process. For this reason, energy saving scheme are often implemented on the devices, to preserve their battery power and hence network lifetime. However, energy saving schemes have the net effect of reducing contact opportunities (because the network interface may be turned off when two users are in radio range) and thus increasing message delay. With the aim of striking the right balance between energy saving and delay performances, in the first part of this thesis I discuss how to design a model that accurately describes how the measured contact process between users is modified by the duty cycle. Then, building upon the results obtained, I introduce a tool for optimizing the duty cycle in order to provide guarantees on message delay.

In the second part of this thesis, I consider smart transportation systems, with a specific focus on the electric carsharing systems. Electric carsharing is considered now one of the key elements of a smart city, since it holds the promise of reducing both gas emissions and traffic congestion. Electric carsharing is typically station-based, i.e., customers are required to pick up and drop off vehicles at special locations called stations, which are also equipped with one or more charging poles. Since deploying the station infrastructure and running the service is costly for the carsharing operator, defining a set of tools for optimal deployment and operational efficiency becomes crucial to guarantee the economic viability of such a system. First, I focus on station deployment, and introduce an optimization problem that allows minimizing the costs for the operator while at the same time maintaining a quality of service that is satisfactory to customers. Secondly, I investigate the opportunity offered by power sharing technologies (which allow multiple vehicles to share the same power), and I develop an optimal power sharing strategy that again takes into account both costs and customer satisfaction. Finally, since the impact of the electric carsharing system on the power distribution grid is expected to be significant, I investigate the energy demands of electric carsharing under different deployment scenarios and charging technologies (including power sharing) in order to verify the effective sustainability of such a system for the power grid.
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