Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers��� requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes��� strategy point of view. Initial tests with a simple Prisoners��� Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.

Technologies for Ambient intelligence: from Smart Objects to Sensor Networks

n the last few years, the vision of our connected and intelligent information society has evolved to embrace novel technological and research trends. The diffusion of ubiquitous mobile connectivity and advanced handheld portable devices, amplified the importance of the Internet as the communication backbone for the fruition of services and data. The diffusion of mobile and pervasive computing devices, featuring advanced sensing technologies and processing capabilities, triggered the adoption of innovative interaction paradigms: touch responsive surfaces, tangible interfaces and gesture or voice recognition are finally entering our homes and workplaces. We are experiencing the proliferation of smart objects and sensor networks, embedded in our daily living and interconnected through the Internet. This ubiquitous network of always available interconnected devices is enabling new applications and services, ranging from enhancements to home and office environments, to remote healthcare assistance and the birth of a smart environment. This work will present some evolutions in the hardware and software development of embedded systems and sensor networks. Different hardware solutions will be introduced, ranging from smart objects for interaction to advanced inertial sensor nodes for motion tracking, focusing on system-level design. They will be accompanied by the study of innovative data processing algorithms developed and optimized to run on-board of the embedded devices. Gesture recognition, orientation estimation and data reconstruction techniques for sensor networks will be introduced and implemented, with the goal to maximize the tradeoff between performance and energy efficiency. Experimental results will provide an evaluation of the accuracy of the presented methods and validate the efficiency of the proposed embedded systems.

Planning and flexible operation of storage systems in power grids: from transmission to distribution networks

The first part of the thesis has been devoted to the transmission planning with high penetration of renewable energy sources. Both stationary and transportable battery energy storage (BES, BEST) systems have been considered in the planning model, so to obtain the optimal set of BES, BEST and transmission lines that minimizes the total cost in a power network. First, a coordinated expansion planning model with fixed transportation cost for BEST devices has been presented; then, the model has been extended to a planning formulation with a distance-dependent transportation cost for the BEST units, and its tractability has been proved through a case study based on a 190-bus test system. The second part of this thesis is then devoted to the analysis of planning and management of renewable energy communities (RECs). Initially, the planning of photovoltaic and BES systems in a REC with an incentive-based remuneration scheme according to the Italian regulatory framework has been analysed, and two planning models, according to a single-stage, or a multi-stage approach, have been proposed in order to provide the optimal set of BES and PV systems allowing to achieve the minimum energy procurement cost in a given REC. Further, the second part of this thesis is devoted to the study of the day-ahead scheduling of resources in renewable energy communities, by considering two types of REC. The first one, which we will refer to as ���cooperative community���, allows direct energy transactions between members of the REC; the second type of REC considered, which we shall refer to as ���incentive-based���, does not allow direct transactions between members but includes economic revenues for the community shared energy, according to the Italian regulation framework. Moreover, dispatchable renewable energy generation has been considered by including producers equipped with biogas power plants in the community.

Indagini forensi in tema di scambio di file pedopornografici mediante software di file sharing a mezzo peer-to-peer

La prova informatica richiede l���adozione di precauzioni come in un qualsiasi altro accertamento scientifico. Si fornisce una panoramica sugli aspetti metodologici e applicativi dell���informatica forense alla luce del recente standard ISO/IEC 27037:2012 in tema di trattamento del reperto informatico nelle fasi di identificazione, raccolta, acquisizione e conservazione del dato digitale. Tali metodologie si attengono scrupolosamente alle esigenze di integrit�� e autenticit�� richieste dalle norme in materia di informatica forense, in particolare della Legge 48/2008 di ratifica della Convenzione di Budapest sul Cybercrime. In merito al reato di pedopornografia si offre una rassegna della normativa comunitaria e nazionale, ponendo l���enfasi sugli aspetti rilevanti ai fini dell���analisi forense. Rilevato che il file sharing su reti peer-to-peer �� il canale sul quale maggiormente si concentra lo scambio di materiale illecito, si fornisce una panoramica dei protocolli e dei sistemi maggiormente diffusi, ponendo enfasi sulla rete eDonkey e il software eMule che trovano ampia diffusione tra gli utenti italiani. Si accenna alle problematiche che si incontrano nelle attivit�� di indagine e di repressione del fenomeno, di competenza delle forze di polizia, per poi concentrarsi e fornire il contributo rilevante in tema di analisi forensi di sistemi informatici sequestrati a soggetti indagati (o imputati) di reato di pedopornografia: la progettazione e l���implementazione di eMuleForensic consente di svolgere in maniera estremamente precisa e rapida le operazioni di analisi degli eventi che si verificano utilizzando il software di file sharing eMule; il software �� disponibile sia in rete all���url http://www.emuleforensic.com, sia come tool all���interno della distribuzione forense DEFT. Infine si fornisce una proposta di protocollo operativo per l���analisi forense di sistemi informatici coinvolti in indagini forensi di pedopornografia.

Self-Organizing Mechanisms for Task Allocation in a Knowledge-Based Economy

A prevalent claim is that we are in knowledge economy. When we talk about knowledge economy, we generally mean the concept of ���Knowledge-based economy��� indicating the use of knowledge and technologies to produce economic benefits. Hence knowledge is both tool and raw material (people���s skill) for producing some kind of product or service. In this kind of environment economic organization is undergoing several changes. For example authority relations are less important, legal and ownership-based definitions of the boundaries of the firm are becoming irrelevant and there are only few constraints on the set of coordination mechanisms. Hence what characterises a knowledge economy is the growing importance of human capital in productive processes (Foss, 2005) and the increasing knowledge intensity of jobs (Hodgson, 1999). Economic processes are also highly intertwined with social processes: they are likely to be informal and reciprocal rather than formal and negotiated. Another important point is also the problem of the division of labor: as economic activity becomes mainly intellectual and requires the integration of specific and idiosyncratic skills, the task of dividing the job and assigning it to the most appropriate individuals becomes arduous, a ���supervisory problem��� (Hogdson, 1999) emerges and traditional hierarchical control may result increasingly ineffective. Not only specificity of know how makes it awkward to monitor the execution of tasks, more importantly, top-down integration of skills may be difficult because ���the nominal supervisors will not know the best way of doing the job ��� or even the precise purpose of the specialist job itself ��� and the worker will know better��� (Hogdson,1999). We, therefore, expect that the organization of the economic activity of specialists should be, at least partially, self-organized. The aim of this thesis is to bridge studies from computer science and in particular from Peer-to-Peer Networks (P2P) to organization theories. We think that the P2P paradigm well fits with organization problems related to all those situation in which a central authority is not possible. We believe that P2P Networks show a number of characteristics similar to firms working in a knowledge-based economy and hence that the methodology used for studying P2P Networks can be applied to organization studies. Three are the main characteristics we think P2P have in common with firms involved in knowledge economy: - Decentralization: in a pure P2P system every peer is an equal participant, there is no central authority governing the actions of the single peers; - Cost of ownership: P2P computing implies shared ownership reducing the cost of owing the systems and the content, and the cost of maintaining them; - Self-Organization: it refers to the process in a system leading to the emergence of global order within the system without the presence of another system dictating this order. These characteristics are present also in the kind of firm that we try to address and that��� why we have shifted the techniques we adopted for studies in computer science (Marcozzi et al., 2005; Hales et al., 2007 [39]) to management science.

The role of technology at school: new perspectives on distance education and cyberbullying

The integration of digital technology in school is a complex phenomenon that affects both teaching and peer relationships. Accordingly, the main aim of this dissertation was to investigate the implementation of distance education among Italian teachers during the COVID-19 pandemic and analyze peer relationships concerning cyberbullying and bullying. While the theoretical section provided an overview of the phenomena, four empirical studies were presented. The first one tested a moderated moderation model among 178 secondary teachers on the interactions among perceived usefulness, perceived ease of use of technology and online teaching self-efficacy. Findings showed that each variable significantly predicted the intention to use technology. In addition, a moderation effect of online teaching self-efficacy on perceived usefulness was found. The second study analyzed the differences in factors promoting the integration of digital technology among 357 teachers of different levels and subjects and their positive and negative experiences with distance education. Results revealed several differences in the function of the grade and subjects taught. Moreover, four main themes emerged from the content analysis. The third study investigated the dyadic perception of bullying and cyberbullying among 50 students using the eye-tracker. Findings showed that, despite differences among different kinds of bullying and cyberbullying, the victim and bully were the most observed roles. Finally, the last study tested two multiple mediation models among 563 students on the association between bullying, cyberbullying, and well-being, considering three different variables related to the school context (peer network, teacher support and school connectedness). The results highlighted the importance of peer networks and school connectedness in mediating the association between victimization, cybervictimzation and well-being. Taken together, the findings provided a rich overview of digital technology integration in schools, highlighting positive and negative aspects and its implications for future research and school policies.

Multidimensional analysis of complex networks

Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.

Wireless Networks for Body-Centric Communications

Progress in miniaturization of electronic components and design of wireless systems paved the way towards ubiquitous and pervasive communications, enabling anywhere and anytime connectivity. Wireless devices present on, inside, around the human body are becoming commonly used, leading to the class of body-centric communications. The presence of the body with all its peculiar characteristics has to be properly taken into account in the development and design of wireless networks in this context. This thesis addresses various aspects of body-centric communications, with the aim of investigating network performance achievable in different scenarios. The main original contributions pertain to the performance evaluation for Wireless Body Area Networks (WBANs) at the Medium Access Control layer: the application of Link Adaptation to these networks is proposed, Carrier Sense Multiple Access with Collision Avoidance algorithms used for WBAN are extensively investigated, coexistence with other wireless systems is examined. Then, an analytical model for interference in wireless access network is developed, which can be applied to the study of communication between devices located on humans and fixed nodes of an external infrastructure. Finally, results on experimental activities regarding the investigation of human mobility and sociality are presented.

Photoactive Carbon Nanostructures: From Multicomponent Arrays To Nanomaterials

Carbon has a unique ability to shape networks of differently hybridized atoms that can generate various allotropes and may also exist as nanoscale materials. The emergence of carbon nanostructures initially occured through the serendipitous discovery of fullerenes and then through experimental advances which led to carbon nanotubes, nanohorns and graphene. The structural diversity of carbon nanoscopic allotropes and their unique and unprecedentend properties, give rise to countless applications and have been intensively exploited in nanotechnology, since they may address the need to create smarter optoelectronic devices, smaller in size and with better performance. The versatile properties of carbon nanomaterials are reflected in the multidisciplinary character of my doctoral research where, in particular, I take advantage of the opportunities offered by fullerenes and carbon nanotubes in constructing novel functional materials. In this work, carbon nanostructures are incorporated in novel photoactive functional systems constructed through different types of interactions ��� covalent bonds, ion-pairing or self-assembly. The variety of properties exhibited by carbon nanostructures is successfully explored by assigning them a different role in a specific array: fullerenes are employed as electron or energy acceptors, whereas carbon nanotubes behave like optically inert scaffolds for luminescent materials or nanoscale substrates in sonication-induced self-assembly. All the presented systems serve as a testbed for exploring the properties of carbon nanostructures in multicomponent arrays, which may be advantageous for the production of new photovoltaic or optoelectronic devices, as well as in the design and control of self-assembly processes.

Exploring domain-informed and physics-guided learning in image-to-image translation

Image-to-image (i2i) translation networks can generate fake images beneficial for many applications in augmented reality, computer graphics, and robotics. However, they require large scale datasets and high contextual understanding to be trained correctly. In this thesis, we propose strategies for solving these problems, improving performances of i2i translation networks by using domain- or physics-related priors. The thesis is divided into two parts. In Part I, we exploit human abstraction capabilities to identify existing relationships in images, thus defining domains that can be leveraged to improve data usage efficiency. We use additional domain-related information to train networks on web-crawled data, hallucinate scenarios unseen during training, and perform few-shot learning. In Part II, we instead rely on physics priors. First, we combine realistic physics-based rendering with generative networks to boost outputs realism and controllability. Then, we exploit naive physical guidance to drive a manifold reorganization, which allowed generating continuous conditions such as timelapses.

Geometric and Combinatorial Aspects of NonEquilibrium Statistical Mechanics

Non-Equilibrium Statistical Mechanics is a broad subject. Grossly speaking, it deals with systems which have not yet relaxed to an equilibrium state, or else with systems which are in a steady non-equilibrium state, or with more general situations. They are characterized by external forcing and internal fluxes, resulting in a net production of entropy which quantifies dissipation and the extent by which, by the Second Law of Thermodynamics, time-reversal invariance is broken. In this thesis we discuss some of the mathematical structures involved with generic discrete-state-space non-equilibrium systems, that we depict with networks in all analogous to electrical networks. We define suitable observables and derive their linear regime relationships, we discuss a duality between external and internal observables that reverses the role of the system and of the environment, we show that network observables serve as constraints for a derivation of the minimum entropy production principle. We dwell on deep combinatorial aspects regarding linear response determinants, which are related to spanning tree polynomials in graph theory, and we give a geometrical interpretation of observables in terms of Wilson loops of a connection and gauge degrees of freedom. We specialize the formalism to continuous-time Markov chains, we give a physical interpretation for observables in terms of locally detailed balanced rates, we prove many variants of the fluctuation theorem, and show that a well-known expression for the entropy production due to Schnakenberg descends from considerations of gauge invariance, where the gauge symmetry is related to the freedom in the choice of a prior probability distribution. As an additional topic of geometrical flavor related to continuous-time Markov chains, we discuss the Fisher-Rao geometry of nonequilibrium decay modes, showing that the Fisher matrix contains information about many aspects of non-equilibrium behavior, including non-equilibrium phase transitions and superposition of modes. We establish a sort of statistical equivalence principle and discuss the behavior of the Fisher matrix under time-reversal. To conclude, we propose that geometry and combinatorics might greatly increase our understanding of nonequilibrium phenomena.

Reti transeuropee e servizi nei settori dell'energia, delle telecomunicazioni e dei trasporti

Le reti transeuropee sono uno dei vettori della competitivit��, dell���integrazione e dello sviluppo sostenibile dell���Unione. La tesi mette in luce la progressiva affermazione di una coerente politica infrastrutturale europea a carattere strumentale, esaminando tale evoluzione sotto tre profili: normativo, istituzionale e finanziario. In primo luogo, sotto il profilo normativo, la tesi evidenzia, da un lato, la progressiva emancipazione delle istituzioni dell���Unione dall���influenza degli Stati membri nell���esercizio delle proprie competenze in materia di reti transeuropee e, dall���altro, lo sviluppo di relazioni di complementariet�� e specialit�� tra la politica di reti e altre politiche dell���Unione. L���elaborato sottolinea, in secondo luogo, sotto il profilo istituzionale, il ruolo del processo di ��integrazione organica�� dei regolatori nazionali e del processo di ��agenzificazione�� nel perseguimento degli obiettivi di interconnessione e accesso alle reti nazionali. La tesi osserva, infine, sotto il profilo finanziario, l���accresciuta importanza del sostegno finanziario dell���UE alla costituzione delle reti, che si �� accompagnata al parziale superamento dei limiti derivanti dal diritto dell���UE alla politiche di spesa pubblica infrastrutturale degli Stati membri. Da un lato rispetto al diritto della concorrenza e, in particolare, al divieto di aiuti di stato, grazie al rapporto funzionale tra reti e prestazione di servizi di interesse economico generale, e dall���altro lato riguardo ai vincoli di bilancio, attraverso un���interpretazione evolutiva della cd. investment clause del Patto di stabilit�� e crescita. La tesi, in conclusione, rileva gli sviluppi decisivi della politica di reti europea, ma sottolinea il ruolo che gli Stati membri sono destinati a continuare ad esercitare nel suo sviluppo. Da questi ultimi, infatti, dipende la concreta attuazione di tale politica, ma anche il definitivo superamento, in occasione di una prossima revisione dei Trattati, dei retaggi intergovernativi che continuano a caratterizzare il diritto primario in materia.

Tensor-Train decomposition for image classification problems

In these last years a great effort has been put in the development of new techniques for automatic object classification, also due to the consequences in many applications such as medical imaging or driverless cars. To this end, several mathematical models have been developed from logistic regression to neural networks. A crucial aspect of these so called classification algorithms is the use of algebraic tools to represent and approximate the input data. In this thesis, we examine two different models for image classification based on a particular tensor decomposition named Tensor-Train (TT) decomposition. The use of tensor approaches preserves the multidimensional structure of the data and the neighboring relations among pixels. Furthermore the Tensor-Train, differently from other tensor decompositions, does not suffer from the curse of dimensionality making it an extremely powerful strategy when dealing with high-dimensional data. It also allows data compression when combined with truncation strategies that reduce memory requirements without spoiling classification performance. The first model we propose is based on a direct decomposition of the database by means of the TT decomposition to find basis vectors used to classify a new object. The second model is a tensor dictionary learning model, based on the TT decomposition where the terms of the decomposition are estimated using a proximal alternating linearized minimization algorithm with a spectral stepsize.

Peer and group relationships in preschoolers: the role of social and linguistic skills

Being able to positively interact and build relationships with playmates in preschool years is crucial to achieve positive adjustment. An update review and two studies on such topics were provided. Study 1 is observational; it investigates the type of social experience in groups (N = 443) of children (N = 120) at preschool age in child-led vs. teacher-led contexts. The results revealed that in child-led contexts children were more likely to be alone, in dyads, and in small peer groups; groups were mostly characterized by same-gender playmates who engaged in joint interactions, with few social interactions with teachers. In teacher-led contexts, on the other hand, children were more likely to be involved in small, medium and large groups; groups were mostly characterized by other-gender playmates, involved in parallel interactions, with teachers playing a more active role. The purpose of Study 2 was to describe the development of socio-emotional competence, temperamental traits and linguistic skill. It examined the role of children���s reciprocated nominations (=RNs) with peers, assessed via sociometric interview, in relation to socio-emotional competence, temperamental traits and linguistic skill. Finally, the similarity-homophily tendency was investigated. Socio-emotional competence and temperamental traits were assessed via teacher ratings, linguistic skill via test administration. Eighty-four preschool children (M age = 62.53) were recruited within 4 preschool settings. Those children were quite representative of preschool population. The results revealed that children with higher RNs showed higher social competence (tendency), social orientation, positive emotionality, motor activity and linguistic skill. They exhibited lower anxiety-withdrawal. The results also showed that children prefer playmates with similar features: social competence, anger-aggression (tendency), social orientation, positive emotionality, inhibition to innovation, attention, motor activity (tendency) and linguistic skill. Implications for future research were suggested.

Il trattamento ortodontico nei bambini con particolari necessit�� sanitarie (SHCN): una valutazione della durata e del risultato clinico utilizzando l'indice PAR (Peer Assessment Rating), la componente DHC (Dental Health Component) e la componente AC (Aesthetic Component) dell'indice IOTN (Orthodontic Treatment Need Index)

Obbiettivo: Valutazione delle eventuali differenze nel trattamento ortodontico di un gruppo di bambini con particolari necessit�� sanitarie (SHCN) rispetto ad un gruppo di bambini non diagnosticati con SHCN. Materiali e Metodi: Il gruppo campione (SHCN) �� costituito da 50 bambini con SHCN. Il gruppo di controllo (NO SHCN) �� costituito da 50 bambini non diagnosticati con SHCN pienamente corrispondenti per et��, genere e tipo di apparecchio ortodontico utilizzato con i pazienti del gruppo di studio. I dati riguardanti i gruppi SHCN e NO SHCN sono stati analizzati in modo retrospettivo, valutando: - il punteggio pre- e post-trattamento e la riduzione finale dei valori dell'indice PAR (Peer Assessment Rating), della componente DHC (Dental Health Component) e della componente AC (Aesthetic Component) dell'indice IOTN (Orthodontic Treatment Need Index), - il numero di appuntamenti, - il numero di sedute semplici e complesse, - la durata complessiva del trattamento, - l'et�� all���inizio ed alla fine della terapia. Risultati: Non sono state rilevate differenze statisticamente significative tra i due gruppi per quanto concerne il numero di appuntamenti, la durata complessiva del trattamento, l'et�� all���inizio ed alla fine della terapia ortodontica (valori del p-value:0.682, 0.458, 0.535, 0.675). Sono state rilevate differenze statisticamente significative tra i due gruppi per quanto riguarda i punteggi dell���indice PAR, delle componenti DHC e AC dello IOTN pre- e post-trattamento, il numero di sedute semplici e complesse (valori del p-value:0.030, 0.000, 0.020, 0.023, 0.000, 0.000, 0.043, 0.037). Per quanto concerne la riduzione finale del valore dell���indice PAR, della componente DHC e di quella AC dello IOTN non sono state riscontrate differenze statisticamente significative tra i due gruppi (valori del p-value:0.060, 0.765, 0.825). Conclusioni: Lo studio incoraggia gli ortodontisti a trattare i bambini con SHCN nell'obiettivo di migliorarne la qualit�� di vita, pur evidenziando la necessit�� di un maggior numero di sedute complesse.