Self-management di malattie croniche in sistemi di mobile Health: sviluppo di un modello agent-based per casi di diabete

L'obiettivo della tesi è proporre e motivare l'adozione di un modello computazionale Agent-Based nell'ambito del Self-Management di malattie croniche in un sistema di mobile Health. Viene quindi affrontata in maniera approfondita la tematica del mobile Health, settore in grande espansione che vede l'introduzione massiccia dei dispositivi mobili (smartphone, tablet, PDA) in ambito sanitario, e quella del Self-Managment di malattie croniche, un processo di cura caratterizzato dalla partecipazione autonoma del paziente stesso, fornendo una panoramica dei vari approcci computazionali sviluppati. Successivamente vengono presentate le peculiarità dei modelli computazionali risultati dalle ricerche in letteratura strumenti innovati nell'ambito. Nel caso di studio viene adottata la tecnica di modellazione Agent-Based per sviluppare un modello a supporto di malati cronici affetti da diabete mellito di tipo 1. Con la successiva implementazione sulla piattaforma di simulazione MASON, vengono eseguiti diversi esperimenti per dimostrare la fattibilità dell’approccio adottato nell'ambito del Self-Management di malattie croniche.

EASE: EPC as a service to ease mobile core network deployment over cloud

The objective of this article is to demonstrate the feasibility of on-demand creation of cloud-based elastic mobile core networks, along with their lifecycle management. For this purpose the article describes the key elements to realize the architectural vision of EPC as a Service, an implementation option of the Evolved Packet Core, as specified by 3GPP, which can be deployed in cloud environments. To meet several challenging requirements associated with the implementation of EPC over a cloud infrastructure and providing it “as a Service,” this article presents a number of different options, each with different characteristics, advantages, and disadvantages. A thorough analysis comparing the different implementation options is also presented.

The University in the Cloud Computing.

With the advancement of Information and Communication Technology ICT which favors increasingly fast, easy, and accessible communication for all and which can reach large groups of people, there have been changes, in recent years in our society that have modified the way we interact, communicate and transmit information. Access to this, it is possible, not only through computers situated in a fixed location, but new mobile devices make it available, wherever the user happens to be located. Now, information "travels" with the user. These forms of communication, transmission and access to information, have also affected the way to conceive and manage business. To these new forms of business that the Internet has brought, is now added the concept of companies in the Cloud Computing ClC. The ClC technology is based on the supply and consumption of services on demand and pay per use, and it gives a 180 degree turn to the business management concept. Small and large businesses may use the latest developments in ICT, to manage their organizations without the need for expensive investments in them. This will enable enterprises to focus more specifically within the scope of their business, leaving the ICT control to the experts. We believe that education can also and should benefit from these new philosophies. ?Due to the global economic crisis in general and each country in particular, economic cutbacks have come to most universities. These are seen in the need to raise tuition rates, which makes increasingly fewer students have the opportunity to pursue higher education?. In this paper we propose using ClC technologies in universities and we make a dissertation on the advantages that it can provide to both: universities and students. For the universities, we expose two focuses, one: ?to reorganize university ICT structures with the ClC philosophy? and the other one, ?to extend the offer of the university education with education on demand?. Regarding the former we propose to use public or private Clouds, to reuse resources across the education community, to save costs on infrastructure investment, in upgrades and in maintenance of ICT, and paying only for what you use and with the ability to scale according to needs. Regarding the latter, we propose an educational model in the ClC, to increase the current university offerings, using educational units in the form of low-cost services and where students pay only for the units consumed on demand. For the students, they could study at any university in the world (virtually), from anywhere, without travel costs: money and time, and what is most important paying only for what they consume. We think that this proposal of education on demand may represent a great change in the current educational model, because strict registration deadlines disappear, and also the problem of economically disadvantaged students, who will not have to raise large amounts of money for an annual tuition. Also it will decrease the problem of loss of the money invested in an enrollment when the student dropout. In summary we think that this proposal is interesting for both, universities and students, we aim for "Higher education from anywhere, with access from any mobile device, at any time, without requiring large investments for students, and with reuse and optimization of resources by universities. Cost by consumption and consumption by service?. We argue for a Universal University "wisdom and knowledge accessible to all?

A real case of a cognitive multiplayer game: design and development of the iOS client in Swift and its cloud architecture

as tecnologías emergentes como el cloud computing y los dispositivos móviles están creando una oportunidad sin precedentes para mejorar el sistema educativo, permitiendo tanto a los educadores personalizar y mejorar la experiencia de aprendizaje, como facilitar a los estudiantes que adquieran conocimientos sin importar dónde estén. Por otra parte, a través de técnicas de gamificacion será posible promover y motivar a los estudiantes a que aprendan materias arduas haciendo que la experiencia sea más motivadora. Los juegos móviles pueden ser el camino correcto para dar soporte a esta experiencia de aprendizaje mejorada. Este proyecto integra el diseño y desarrollo de una arquitectura en la nube altamente escalable y con alto rendimiento, así como el propio cliente de iOS, para dar soporte a una nueva version de Temporis, un juego móvil multijugador orientado a reordenar eventos históricos en una línea temporal (e.j. historia, arte, deportes, entretenimiento y literatura). Temporis actualmente está disponible en Google Play. Esta memoria describe el desarrollo de la nueva versión de Temporis (Temporis v.2.0) proporcionando detalles acerca de la mejora y adaptación basados en el Temporis original. En particular se describe el nuevo backend hecho en Go sobre Google App Engine creado para soportar miles de usuarios, asó como otras características por ejemplo como conseguir enviar noticaciones push desde la propia plataforma. Por último, el cliente de iOS en Temporis v.2.0 se ha desarrollado utilizando las últimas y más relevantes tecnologías, prestando especial atención a Swift (el lenguaje de programación nuevo de Apple, que es seguro y rápido), el Paradigma Funcional Reactivo (que ayuda a construir aplicaciones altamente interactivas además de a minimizar errores) y la arquitectura VIPER (una arquitectura que sigue los principios SOLID, se centra en la separación de asuntos y favorece la reutilización de código en otras plataformas). ABSTRACT Emerging technologies such as cloud computing and mobile devices are creating an unprecedented opportunity for enhancing the educational system, letting both educators customize and improve the learning experience, and students acquire knowledge regardless of where they are. Moreover, through gamification techniques it would be possible to encourage and motivate students to learn arduous subjects by making the experience more motivating. Mobile games can be a perfect vehicle to support this enhanced learning experience. This project integrates the design and development of a highly scalable and performant cloud architecture, as well as the iOS client that uses it, in order to provide support to a new version of Temporis, a mobile multiplayer game focused on ordering time-based (e.g. history, art, sports, entertainment and literature) in a timeline that currently is available on Google Play. This work describes the development of the new Temporis version (Temporis v.2.0), providing details about improvements and details on the adaptation of the original Temporis. In particular, the new Google App Engine backend is described, which was created to support thousand of users developed in Go language are provided, in addition to other features like how to achieve push notications in this platform. Finally, the mobile iOS client developed using the latest and more relevant technologies is explained paying special attention to Swift (Apple's new programming language, that is safe and fast), the Functional Reactive Paradigm (that helps building highly interactive apps while minimizing bugs) and the VIPER architecture (a SOLID architecture that enforces separation of concerns and makes it easy to reuse code for other platforms).

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.

A Cloud-based Framework for Security Analysis of Browser Extensions

In today's internet world, web browsers are an integral part of our day-to-day activities. Therefore, web browser security is a serious concern for all of us. Browsers can be breached in different ways. Because of the over privileged access, extensions are responsible for many security issues. Browser vendors try to keep safe extensions in their official extension galleries. However, their security control measures are not always effective and adequate. The distribution of unsafe extensions through different social engineering techniques is also a very common practice. Therefore, before installation, users should thoroughly analyze the security of browser extensions. Extensions are not only available for desktop browsers, but many mobile browsers, for example, Firefox for Android and UC browser for Android, are also furnished with extension features. Mobile devices have various resource constraints in terms of computational capabilities, power, network bandwidth, etc. Hence, conventional extension security analysis techniques cannot be efficiently used by end users to examine mobile browser extension security issues. To overcome the inadequacies of the existing approaches, we propose CLOUBEX, a CLOUd-based security analysis framework for both desktop and mobile Browser EXtensions. This framework uses a client-server architecture model. In this framework, compute-intensive security analysis tasks are generally executed in a high-speed computing server hosted in a cloud environment. CLOUBEX is also enriched with a number of essential features, such as client-side analysis, requirements-driven analysis, high performance, and dynamic decision making. At present, the Firefox extension ecosystem is most susceptible to different security attacks. Hence, the framework is implemented for the security analysis of the Firefox desktop and Firefox for Android mobile browser extensions. A static taint analysis is used to identify malicious information flows in the Firefox extensions. In CLOUBEX, there are three analysis modes. A dynamic decision making algorithm assists us to select the best option based on some important parameters, such as the processing speed of a client device and network connection speed. Using the best analysis mode, performance and power consumption are improved significantly. In the future, this framework can be leveraged for the security analysis of other desktop and mobile browser extensions, too.

Towards Automation in Digital Investigations : Seeking Efficiency in Digital Forensics in Mobile and Cloud Environments

Cybercrime and related malicious activity in our increasingly digital world has become more prevalent and sophisticated, evading traditional security mechanisms. Digital forensics has been proposed to help investigate, understand and eventually mitigate such attacks. The practice of digital forensics, however, is still fraught with various challenges. Some of the most prominent of these challenges include the increasing amounts of data and the diversity of digital evidence sources appearing in digital investigations. Mobile devices and cloud infrastructures are an interesting specimen, as they inherently exhibit these challenging circumstances and are becoming more prevalent in digital investigations today. Additionally they embody further characteristics such as large volumes of data from multiple sources, dynamic sharing of resources, limited individual device capabilities and the presence of sensitive data. These combined set of circumstances make digital investigations in mobile and cloud environments particularly challenging. This is not aided by the fact that digital forensics today still involves manual, time consuming tasks within the processes of identifying evidence, performing evidence acquisition and correlating multiple diverse sources of evidence in the analysis phase. Furthermore, industry standard tools developed are largely evidence-oriented, have limited support for evidence integration and only automate certain precursory tasks, such as indexing and text searching. In this study, efficiency, in the form of reducing the time and human labour effort expended, is sought after in digital investigations in highly networked environments through the automation of certain activities in the digital forensic process. To this end requirements are outlined and an architecture designed for an automated system that performs digital forensics in highly networked mobile and cloud environments. Part of the remote evidence acquisition activity of this architecture is built and tested on several mobile devices in terms of speed and reliability. A method for integrating multiple diverse evidence sources in an automated manner, supporting correlation and automated reasoning is developed and tested. Finally the proposed architecture is reviewed and enhancements proposed in order to further automate the architecture by introducing decentralization particularly within the storage and processing functionality. This decentralization also improves machine to machine communication supporting several digital investigation processes enabled by the architecture through harnessing the properties of various peer-to-peer overlays. Remote evidence acquisition helps to improve the efficiency (time and effort involved) in digital investigations by removing the need for proximity to the evidence. Experiments show that a single TCP connection client-server paradigm does not offer the required scalability and reliability for remote evidence acquisition and that a multi-TCP connection paradigm is required. The automated integration, correlation and reasoning on multiple diverse evidence sources demonstrated in the experiments improves speed and reduces the human effort needed in the analysis phase by removing the need for time-consuming manual correlation. Finally, informed by published scientific literature, the proposed enhancements for further decentralizing the Live Evidence Information Aggregator (LEIA) architecture offer a platform for increased machine-to-machine communication thereby enabling automation and reducing the need for manual human intervention.

An Autonomic Framework for Mobile Cloud Computing

This thesis presents the formal definition of a novel Mobile Cloud Computing (MCC) extension of the Networked Autonomic Machine (NAM) framework, a general-purpose conceptual tool which describes large-scale distributed autonomic systems. The introduction of autonomic policies in the MCC paradigm has proved to be an effective technique to increase the robustness and flexibility of MCC systems. In particular, autonomic policies based on continuous resource and connectivity monitoring help automate context-aware decisions for computation offloading. We have also provided NAM with a formalization in terms of a transformational operational semantics in order to fill the gap between its existing Java implementation NAM4J and its conceptual definition. Moreover, we have extended NAM4J by adding several components with the purpose of managing large scale autonomic distributed environments. In particular, the middleware allows for the implementation of peer-to-peer (P2P) networks of NAM nodes. Moreover, NAM mobility actions have been implemented to enable the migration of code, execution state and data. Within NAM4J, we have designed and developed a component, denoted as context bus, which is particularly useful in collaborative applications in that, if replicated on each peer, it instantiates a virtual shared channel allowing nodes to notify and get notified about context events. Regarding the autonomic policies management, we have provided NAM4J with a rule engine, whose purpose is to allow a system to autonomously determine when offloading is convenient. We have also provided NAM4J with trust and reputation management mechanisms to make the middleware suitable for applications in which such aspects are of great interest. To this purpose, we have designed and implemented a distributed framework, denoted as DARTSense, where no central server is required, as reputation values are stored and updated by participants in a subjective fashion. We have also investigated the literature regarding MCC systems. The analysis pointed out that all MCC models focus on mobile devices, and consider the Cloud as a system with unlimited resources. To contribute in filling this gap, we defined a modeling and simulation framework for the design and analysis of MCC systems, encompassing both their sides. We have also implemented a modular and reusable simulator of the model. We have applied the NAM principles to two different application scenarios. First, we have defined a hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. Merging P2P and cloud paradigms brings together the advantages of both: high availability, provided by the Cloud presence, and low cost, by exploiting inexpensive peers resources. As an example, we have shown how the proposed approach can be used to design NAM-based collaborative storage systems based on an autonomic policy to decide how to distribute data chunks among peers and Cloud, according to cost minimization and data availability goals. As a second application, we have defined an autonomic architecture for decentralized urban participatory sensing (UPS) which bridges sensor networks and mobile systems to improve effectiveness and efficiency. The developed application allows users to retrieve and publish different types of sensed information by using the features provided by NAM4J's context bus. Trust and reputation is managed through the application of DARTSense mechanisms. Also, the application includes an autonomic policy that detects areas characterized by few contributors, and tries to recruit new providers by migrating code necessary to sensing, through NAM mobility actions.

Architettura cloud per lo sviluppo multi-piattaforma di Sistemi Operativi: Principi generali

Vengono analizzate le strategie di rilascio delle principali Distribuzioni Linux e i metodi per la compilazione automatizzata del software. Si propone quindi una nuova metodologia sia per il rilascio di media installabili e sia per la pacchettizzazione. Sfruttando le tecnologie del campo DevOps, si introduce quindi un alto grado di scalabilità anche in ambienti Cloud, grazie anche alla riproducibilità di ogni componente dell'infrastruttura proposta. Vedremo quindi come questo approccio aumenta l'automatizzazione nei cicli produttivi per la realizzazione della Distribuzione Sabayon Linux e per la definizione di un'infrastruttura automatizzata attualmente in production.

Architettura cloud per lo sviluppo multi-piattaforma di Sistemi Operativi: Applicazioni specifiche

Il mondo dell’Internet of Things e del single board computing sono settori in forte espansione al giorno d’oggi e le architetture ARM sono, al momento, i dominatori in questo ambito. I sistemi operativi e i software si stanno evolvendo per far fronte a questo cambiamento e ai nuovi casi d’uso che queste tecnologie introducono. In questa tesi ci occuperemo del porting della distribuzione Linux Sabayon per queste architetture, la creazione di un infrastruttura per il rilascio delle immagini e la compilazione dei pacchetti software.

Mobile Mapping System

Nella tesi si espone il Mobile Mapping System, cioè il rilevamento di dati geospaziali utilizzando sensori montati a bordo di appositi veicolo senza l'ausilio di punti di contatto a terra. Si illustrano i diversi dispositivi del sistema installati a bordo, le loro diverse applicazioni e metodologie di rilevamento. Si trattano le varie problematiche sorte e le loro risoluzioni.

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.

A mobile cloud computing framework integrating multilevel encoding for performance monitoring in telerehabilitation

Recent years have witnessed a surge in telerehabilitation and remote healthcare systems blessed by the emerging low-cost wearable devices to monitor biological and biokinematic aspects of human beings. Although such telerehabilitation systems utilise cloud computing features and provide automatic biofeedback and performance evaluation, there are demands for overall optimisation to enable these systems to operate with low battery consumption and low computational power and even with weak or no network connections. This paper proposes a novel multilevel data encoding scheme satisfying these requirements in mobile cloud computing applications, particularly in the field of telerehabilitation. We introduce architecture for telerehabilitation platform utilising the proposed encoding scheme integrated with various types of sensors. The platform is usable not only for patients to experience telerehabilitation services but also for therapists to acquire essential support from analysis oriented decision support system (AODSS) for more thorough analysis and making further decisions on treatment.

Engineering searchable encryption of mobile cloud networks : when QoE meets QoP

Mobile cloud computing can effectively address the resource limitations of mobile devices, and is therefore essential to enable extensive resource consuming mobile computing and communication applications. Of all the mobile cloud computing applications, data outsourcing, such as iCloud, is fundamental, which outsources a mobile user's data to external cloud servers and accordingly provides a scalable and always on approach for public data access. With the security and privacy issues related to outsourced data becoming a rising concern, encryption on outsourced data is often necessary. Although encryption increases the quality of protection (QoP) of data outsourcing, it significantly reduces data usability and thus harms the mobile user's quality of experience (QoE). How to strike a balance between QoP and QoE is therefore an important yet challenging task. In this article we focus on the fundamental problem of QoP and QoE provisioning in searchable encryption of data outsourcing. We develop a fine-grained data search scheme and discuss its implementation on encrypted mobile cloud data, which is an effective balance between QoE and QoP in mobile cloud data outsourcing.

Enabling efficient multi-keyword ranked search over encrypted mobile cloud data through blind storage

In mobile cloud computing, a fundamental application is to outsource the mobile data to external cloud servers for scalable data storage. The outsourced data, however, need to be encrypted due to the privacy and confidentiality concerns of their owner. This results in the distinguished difficulties on the accurate search over the encrypted mobile cloud data. To tackle this issue, in this paper, we develop the searchable encryption for multi-keyword ranked search over the storage data. Specifically, by considering the large number of outsourced documents (data) in the cloud, we utilize the relevance score and k-nearest neighbor techniques to develop an efficient multi-keyword search scheme that can return the ranked search results based on the accuracy. Within this framework, we leverage an efficient index to further improve the search efficiency, and adopt the blind storage system to conceal access pattern of the search user. Security analysis demonstrates that our scheme can achieve confidentiality of documents and index, trapdoor privacy, trapdoor unlinkability, and concealing access pattern of the search user. Finally, using extensive simulations, we show that our proposal can achieve much improved efficiency in terms of search functionality and search time compared with the existing proposals.