Collaboration in Opportunistic Networks

Motivation. With the increasing integration of wireless short-range communication technologies (Bluetooth, 802.11b WiFi) into mobile devices, novel applications for spontaneous communication, interaction and collaboration are possible. We distinguish between active and passive collaboration. The devices help users become aware of each other and stimulate face-to-face conversation (active collaboration). Also, autonomous device communication for sharing information without user interaction is possible, i.e., devices pass information to other devices in their vicinity (passive collaboration). Both, active and passive collaboration requires a user to specify what kind of information he offers and what kind of information he is interested in. Object of Research: Opportunistic Networks. Spontaneous communication of mobile devices leads to so-called opportunistic networks, a new and promising evolution in mobile ad-hoc networking. They are formed by mobile devices which communicate with each other while users are in close proximity. There are two prominent characteristics present in opportunistic networks: 1) A user provides his personal device as a network node. 2) Users are a priori unknown to each other. Objectives. Due to the fact that a user dedicates his personal device as a node to the opportunistic network and interacts with other users unknown to him, collaboration raises questions concerning two important human aspects: user privacy and incentives. The users’ privacy is at risk, since passive collaboration applications may expose personal information about a user. Furthermore, some form of incentive is needed to encourage a user to share his personal device resources with others. Both issues, user privacy and incentives, need to be taken into account in order to increase the user acceptability of opportunistic network applications. These aspects have not been addressed together with the technical tasks in prior opportunistic network research. Scientific Contribution and Evaluation. This thesis investigates opportunistic networks in their entirety, i.e., our technical design decisions are appropriate for user privacy preservation and incentive schemes. In summary, the proposed concepts comprise system components, a node architecture, a system model and a simple one-hop communication paradigm for opportunistic network applications. One focus of this work is a profile-based data dissemination mechanism. A formal model for this mechanism will be presented. On top of that, we show how to preserve the privacy of a user by avoiding static and thus linkable data and an incentive scheme that is suitable for opportunistic network applications. The evaluation of this work is twofold. We implemented two prototypes on off-the-shelf hardware to show the technical feasibility of our opportunistic network concepts. Also, the prototypes were used to carry out a number of runtime measurements. Then, we developed a novel two-step simulation method for opportunistic data dissemination. The simulation combines real world user traces with artificial user mobility models, in order to model user movements more realistically. We investigate our opportunistic data dissemination process under various settings, including different communication ranges and user behavior patterns. Our results depict, within the limits of our model and assumptions, a good performance of the data dissemination process

Information diffusion in mobile social networks: The speed perspective

Abstract—The emerging of mobile social networks opens op-portunities for viral marketing. However, before fully utilizing mobile social networks as a platform for viral marketing, many challenges have to be addressed. In this paper, we address the problem of identifying a small number of individuals through whom the information can be diffused to the network as soon as possible, referred to as the diffusion minimization problem. Diffusion minimization under the probabilistic diffusion model can be formulated as an asymmetric k-center problem which is NP-hard, and the best known approximation algorithm for the asymmetric k-center problem has approximation ratio of log ∗ n and time complexity O(n5). Clearly, the performance and the time complexity of the approximation algorithm are not satisfiable in large-scale mobile social networks. To deal with this problem, we propose a community based algorithm and a distributed set-cover algorithm. The performance of the proposed algorithms is evaluated by extensive experiments on both synthetic networks and a real trace. The results show that the community based algorithm has the best performance in both synthetic networks and the real trace, and the distributed set-cover algorithm outperforms the approximation algorithm in the real trace in terms of diffusion time. I

From the conception to the definition of a new service: the case of the European GeoPKDD project”

La tesi affronta il processo che parte dalla generazione di un nuovo servizio di tipo technology push ed arriva fino alla sua definizione, attraverso l’analisi del lavoro svolto per WIND Telecomunicazioni s.p.a. nell’ambito del progetto Europeo GeoPKDD. Dopo un inquadramento teorico sulle metodologie di sviluppo di nuovi servizi e sulle peculiarità di uno sviluppo technology push rispetto al caso market pull, il lavoro si concentra sul processo che, partendo dalla generazione di nuove idee basate sulla tecnologia GeoPKDD, si è concluso con la definizione delle specifiche finali da implementare nel servizio finale

Modern Socio-Technical Perspectives on Privacy

This open access book provides researchers and professionals with a foundational understanding of online privacy as well as insight into the socio-technical privacy issues that are most pertinent to modern information systems, covering several modern topics (e.g., privacy in social media, IoT) and underexplored areas (e.g., privacy accessibility, privacy for vulnerable populations, cross-cultural privacy). The book is structured in four parts, which follow after an introduction to privacy on both a technical and social level: Privacy Theory and Methods covers a range of theoretical lenses through which one can view the concept of privacy. The chapters in this part relate to modern privacy phenomena, thus emphasizing its relevance to our digital, networked lives. Next, Domains covers a number of areas in which privacy concerns and implications are particularly salient, including among others social media, healthcare, smart cities, wearable IT, and trackers. The Audiences section then highlights audiences that have traditionally been ignored when creating privacy-preserving experiences: people from other (non-Western) cultures, people with accessibility needs, adolescents, and people who are underrepresented in terms of their race, class, gender or sexual identity, religion or some combination. Finally, the chapters in Moving Forward outline approaches to privacy that move beyond one-size-fits-all solutions, explore ethical considerations, and describe the regulatory landscape that governs privacy through laws and policies. Perhaps even more so than the other chapters in this book, these chapters are forward-looking by using current personalized, ethical and legal approaches as a starting point for re-conceptualizations of privacy to serve the modern technological landscape. The book’s primary goal is to inform IT students, researchers, and professionals about both the fundamentals of online privacy and the issues that are most pertinent to modern information systems. Lecturers or teacherscan assign (parts of) the book for a “professional issues” course. IT professionals may select chapters covering domains and audiences relevant to their field of work, as well as the Moving Forward chapters that cover ethical and legal aspects. Academicswho are interested in studying privacy or privacy-related topics will find a broad introduction in both technical and social aspects

Availability, Integrity, and Confidentiality for Content Centric Network internet architectures

The Internet as we know it today, despite being ``the result of a series of accidents of choices'' in Prof. Jon Crowcroft's words, has undoubtedly been an amazing success story. However, it has been constantly challenged by the demands of the overwhelming evolution of data traffic types, non-functional needs of applications and users, and device diversity. The phrase ``future internet architecture'' can be interpreted as referring to a revised set of design principles. As Dr David Clark rightfully suggested, we need to ``allow for the future in the face of the present''. Content Centric Networking (CCN) is one of the candidates for a future internet architecture. Security is one of the most significant considerations while designing a future internet architecture. Availability, Integrity, and Confidentiality (AIC) are considered the three most crucial components of security: 1) availability is the assurance of continuous, reliable, and uninterrupted access to the information by authorized people, 2) integrity is the preservation of information and prevention of any change in it caused via accident or malicious intent, and 3) confidentiality is the ability to keep the information secret from unintended audience, intruders, and adversaries. This thesis discusses AIC related security threats and corresponding remedies for Named Data Networking (NDN) which is a promising example of CCN. It also presents a system dynamics modelling approach to bridge the gap between the technical solutions and business strategy by quantifying some of the qualitative variables salient to technology architects, policymakers, lawmakers, regulators, and internet service providers for the design of a future-proof internet architecture

Modern Socio-Technical Perspectives on Privacy

This open access book provides researchers and professionals with a foundational understanding of online privacy as well as insight into the socio-technical privacy issues that are most pertinent to modern information systems, covering several modern topics (e.g., privacy in social media, IoT) and underexplored areas (e.g., privacy accessibility, privacy for vulnerable populations, cross-cultural privacy). The book is structured in four parts, which follow after an introduction to privacy on both a technical and social level: Privacy Theory and Methods covers a range of theoretical lenses through which one can view the concept of privacy. The chapters in this part relate to modern privacy phenomena, thus emphasizing its relevance to our digital, networked lives. Next, Domains covers a number of areas in which privacy concerns and implications are particularly salient, including among others social media, healthcare, smart cities, wearable IT, and trackers. The Audiences section then highlights audiences that have traditionally been ignored when creating privacy-preserving experiences: people from other (non-Western) cultures, people with accessibility needs, adolescents, and people who are underrepresented in terms of their race, class, gender or sexual identity, religion or some combination. Finally, the chapters in Moving Forward outline approaches to privacy that move beyond one-size-fits-all solutions, explore ethical considerations, and describe the regulatory landscape that governs privacy through laws and policies. Perhaps even more so than the other chapters in this book, these chapters are forward-looking by using current personalized, ethical and legal approaches as a starting point for re-conceptualizations of privacy to serve the modern technological landscape. The book’s primary goal is to inform IT students, researchers, and professionals about both the fundamentals of online privacy and the issues that are most pertinent to modern information systems. Lecturers or teacherscan assign (parts of) the book for a “professional issues” course. IT professionals may select chapters covering domains and audiences relevant to their field of work, as well as the Moving Forward chapters that cover ethical and legal aspects. Academicswho are interested in studying privacy or privacy-related topics will find a broad introduction in both technical and social aspects

A CHANCE FOR PLACES THAT DON’T MATTER. PLACE-BASED SUSTAINABLE TOURISM PROJECT FOR DEPOPULATED RURAL REGIONS: THE CASE OF PORTUGAL

Human desertification of rural areas is a growing evidence, in a never-ending cycle of decline, with lack of services and businesses, fewer jobs and population ageing. Consequently, land and built heritage is abandoned and degradation take root. To this social and economical deterioration, adds the environmental impact, resulting in the lack of forest management, accumulation of flamable biomass, and as a result, wild fires devastation. This project argues that there is currently a triple-sidded opportunity to invert this trend of decline. Firstly, on the digital transformation of rural areas, which offers connectivity and digitalization, and will power many new opportunities; secondly, on the growing attention from policy makers to the rural society, namely to the socio-economic underdevelopment, ecological degradation and demographic situation; and thirdly, on the availability of unused built heritage, that a new generation of rural built owners received as legacy from their ancestors, and that has become a burden instead of an asset or a benefit. This project presents a strategy that, by taking advantage of the combination of these three fields of opportunity, creates an innovative business, grounded on the the touristic offer of hotel rooms in recovered rural houses, integrated in a rural resort. In this way, this project will associate all the facilities, services and hotel refinement with the unique experience of being a part of local community and encountering a rural lifestyle. It provides a model easily replicable in several locations, with similar characteristics and needs, all over the world. With sustainability as a bedrock, this project commits to an effective and positive environmental, social and economic effect in the community, exploring a place-based approach for the community and visitor engagement. Moreover, this project aspires to make a contribution for youth fixation, by creating more and better jobs and transforming rural communities into modern and vibrant living places, grounded in nature and local uniqueness, turning around the decline and switching the expression from ‘places that don’t matter’ to ‘places that really matter’

Data dissemination in partially cooperative opportunistic networks

Wireless communication between mobile users has become more popular than ever in the last decade, leading to increasing demand for network infrastructure. The growing popularity of smartphones among mobile users, leads an alternative infrastructure-less networking paradigm known as opportunistic networks. In opportunistic networks, mobile nodes such as smartphones use the mobility of devices in addition to wireless forwarding between intermediate nodes to facilitate communication without requiring a simultaneous path between source and destination. Without guaranteed connectivity, the strategy for data delivery is a key research challenge for such networks. In this research, we present the design and evaluation of the Repository-based Data Dissemination (RDD) system, a communication system which does not rely on cooperation from mobile nodes but instead employs a small number of well-placed standalone fixed devices (named repositories) to facilitate data dissemination. To find the optimal location for their repositories, RDD employs knowledge of the mobility characteristics of mobile users. To evaluate RDD, a new mobility model “Human mobility model” has been designed, which was able to closely mimic the users’ real mobility, and proven by conducting a series of experiments compared with real mobility traces. Using this model, the performance of the RDD is evaluated using custom simulation. In comparison with epidemic routing, the results show that RDD is able to drastically reduce resource consumption, expressed in terms of message redundancy, while preserving the performance in terms of data object delivery

The dynamics of data donation : privacy risk, mobility data, and the smart city

With the development of new technologies and their increased applications in the context of a local government, cities have started to claim that they are smart. Smart Cities make use of Information and Communication Technologies (ICTs) to support planning and policy making. For an appropriate and sustainable functioning of these smart cities, collecting data about the different aspects of their territory and operations, including its citizens, is a crucial activity. Currently, there are two main avenues in which smart cities can collect data about their citizens: either through sensors, and cameras strategically placed throughout the city or by asking citizens to voluntarily donate to the local government their personal data (i.e., citizen engagement or ‘e-participation’). Despite the growth and increasing prevalence of the latter practice, little attention has been given to how individuals experience the risks of data donation. Often, studies consider data donation as an aspect of the phenomenon of surveillance, or as a type of data sharing. This study theorises and empirically examines data donation and its risks as a phenomenon which is separate from either surveillance or data sharing. Focusing on mobility data, this study draws on two established donation and privacy risk frameworks to investigate how the risks of donating personal data to a smart city are experienced and socially constructed. The thematic analysis of ten focus groups conducted showed that, in the context of this empirical examination, privacy-specific risks alone do not constitute constructed risks. Instead, they combine in various ways with perceived donation risks to constitute more nuanced and embedded risk constructions. Donation risks are seen as potential consequences of privacy risks and combined they constitute the risks of donating data. This thesis underlines the importance of the context under which data donation takes place as well as privacy’s value in a free and democratic society."This work was supported by the University of St Andrews and the Social Sciences and Humanities Research Council of Canada (SSHRC) under the ‘Big Data Surveillance’ partnership grant. The grant’s reference is: SSHRC 895-2015-1003" -- Fundin