We are witnessing exponential growth in the number of powerful, multiply-connected, energy-rich stationary and mobile nodes, which will make available a massive pool of computing and communication resources. We claim that cloud computing can provide resilient on-demand computing, and more effective and efficient utilization of potentially infinite array of resources. Current cloud computing systems are primarily built using stationary resources. Recently, principles of cloud computing have been extended to the mobile computing domain aiming to form local clouds using mobile devices sharing their computing resources to run cloud-based services. However, current cloud computing systems by and large fail to provide true on-demand computing due to their lack of the following capabilities: 1) providing resilience and autonomous adaptation to the real-time variation of the underlying dynamic and scattered resources as they join or leave the formed cloud; 2) decoupling cloud management from resource management, and hiding the heterogeneous resource capabilities of participant nodes; and 3) ensuring reputable resource providers and preserving the privacy and security constraints of these providers while allowing multiple users to share their resources. Consequently, systems and consumers are hindered from effectively and efficiently utilizing the virtually infinite pool of computing resources. We propose a platform for mobile cloud computing that integrates: 1) a dynamic real-time resource scheduling, tracking, and forecasting mechanism; 2) an autonomous resource management system; and 3) a cloud management capability for cloud services that hides the heterogeneity, dynamicity, and geographical diversity concerns from the cloud operation. We hypothesize that this would enable 'Collaborative Computing Cloud (C3)' for on-demand computing, which is a dynamically formed cloud of stationary and/or mobile resources to provide ubiquitous computing on-demand. The C3 would support a new resource-infinite computing paradigm to expand problem solving beyond the confines of walled-in resources and services by utilizing the massive pool of computing resources, in both stationary and mobile nodes. In this dissertation, we present a C3 management platform, named PlanetCloud, for enabling both a new resource-infinite computing paradigm using cloud computing over stationary and mobile nodes, and a true ubiquitous on-demand cloud computing. This has the potential to liberate cloud users from being concerned about resource constraints and provides access to cloud anytime and anywhere. PlanetCloud synergistically manages 1) resources to include resource harvesting, forecasting and selection, and 2) cloud services concerned with resilient cloud services to include resource provider collaboration, application execution isolation from resource layer concerns, seamless load migration, fault-tolerance, the task deployment, migration, revocation, etc. Specifically, our main contributions in the context of PlanetCloud are as follows. 1. PlanetCloud Resource Management • Global Resource Positioning System (GRPS): • Global mobile and stationary resource discovery and monitoring. A novel distributed spatiotemporal resource calendaring mechanism with real-time synchronization is proposed to mitigate the effect of failures occurring due to unstable connectivity and availability in the dynamic mobile environment, as well as the poor utilization of resources. This mechanism provides a dynamic real-time scheduling and tracking of idle mobile and stationary resources. This would enhance resource discovery and status tracking to provide access to the right-sized cloud resources anytime and anywhere. • Collaborative Autonomic Resource Management System (CARMS): Efficient use of idle mobile resources. Our platform allows sharing of resources, among stationary and mobile devices, which enables cloud computing systems to offer much higher utilization, resulting in higher efficiency. CARMS provides system-managed cloud services such as configuration, adaptation and resilience through collaborative autonomic management of dynamic cloud resources and membership. This helps in eliminating the limited self and situation awareness and collaboration of the idle mobile resources. 2. PlanetCloud Cloud Management Architecture for resilient cloud operation on dynamic mobile resources to provide stable cloud in a continuously changing operational environment. This is achieved by using trustworthy fine-grained virtualization and task management layer, which isolates the running application from the underlying physical resource enabling seamless execution over heterogeneous stationary and mobile resources. This prevents the service disruption due to variable resource availability. The virtualization and task management layer comprises a set of distributed powerful nodes that collaborate autonomously with resource providers to manage the virtualized application partitions. / Ph. D.

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-05-04T15:21:39Z No. of bitstreams: 1 Vinícius Tocantins Marques_.pdf: 1798612 bytes, checksum: 644619b1572a14e55b710812ab705ff0 (MD5) / Made available in DSpace on 2016-05-04T15:21:39Z (GMT). No. of bitstreams: 1 Vinícius Tocantins Marques_.pdf: 1798612 bytes, checksum: 644619b1572a14e55b710812ab705ff0 (MD5) Previous issue date: 2016-03-10 / Nenhuma / O uso de aplicações que padronizam as informações utilizadas em emergências médicas é uma das grandes ferramentas de apoio para as equipes de médicos plantonistas neste novo século. A Computação Ubíqua e a Ciência de Situação são elementos de evolução para aplicações computacionais em hospitais. Mais especificamente, a aplicação que consegue correlacionar dados de redes heterogêneas em prol do sucesso do atendimento médico, produz uma ampla rede de colaboração. Sustentado nesse conceito, o paciente em atendimento poderá usufruir de opiniões de uma ampla gama de médicos especialistas, todos a favor do seu bem estar. No geral o que se tem de resultado das buscas são trabalhos que abordam os conceitos de formas separadas. Nesse âmbito, o presente trabalho propõe o desenvolvimento de um modelo colaborativo com suporte à troca de informações entre equipes médicas plantonistas utilizando Ciência de Situação. O modelo visa utilizar recursos de computação ubíqua para melhorar a inserção de dados relevantes na aplicação, bem como otimizar a saída de dados em dispositivos móveis. Como contribuição científica, o modelo proposto emprega inferências computacionais mediante o uso de ciência de situação no intuito de melhorar a tomada de decisão médica e suportar a colaboração entre as equipes médicas. O modelo proposto realizou duas avaliações, sendo uma através de estudo de caso e a outra referente à usabilidade. As avaliações atestaram que o Doctor Collab alcançou uma média de aceitação de 86,9% utilizando o modelo TAM para verificar o grau de assentimento da aplicação frente aos médicos plantonistas. Desta maneira pode-se indicar que o modelo proposto é coerente com as Hipóteses identificadas. / Technological applications used in medical emergencies is one of the greatest support tools for attending physicians teams in this new century. The Ubiquitous Computing and the Situation Awareness are evolving elements for computer applications in hospitals. Specifically, the application that is able to correlate data from heterogeneous networks to improve the success of health care, produces a wide collaboration network. Beside that, the patient can benefit from various views of a wide range of medical specialists, all in favor of their welfare. Overall the results of researches are works that address the topics of different forms. One of the articles did not apply the concepts of ubiquitous computing in order to minimally interfere with the day-to-day medical team. In this context, this paper proposes the development of a collaborative model that supports the exchange of information between physicians medical teams using the Situation Awareness. The model aims to use ubiquitous computing resources to improve the inclusion of relevant data in the application, as well as optimize the data output on mobile devices. As scientific contribution, the proposed model employs computational inferences by using Situation Awareness in order to improve medical decision making and support collaboration between medical teams. The proposed model had two evaluations, one through case study and the other regarding the usability of the model. Evaluations show that the Doctor Collab reached an average of 86.9% acceptance using the Technical Architecture Modelling model to check the assent of application to the attending physicians. In this way it way be indicated that the proposed model is consistent with the identified assumptions.

This thesis proposes an Ecosystem perspective for the engineering of SoS and CPS and illustrates the impact of this perspective in three areas of contribution category First, from a conceptual and Systems Engineering perspective, a conceptual framework including the Ecosystems of System Unified Language Modeling (EoS-UML) profile, a set of Ecosystem Ensemble Diagrams, the Arms :Length Trust Model and the Cyber Physical Threat Model are provided. Second, having established this conceptual view of the ecosystem, we recognize unique role of the cryptographic credentials within it, towards enabling the ecosystem long-term value proposition and acting as a value transfer agent, implementing careful balance of properties meet stakeholder needs. Third, we propose that the ecosystem computers can be used as a distributed compute engine to run Collaborative Algorithms. To demonstrate, we define access control scheme, risk-balanced Cellular Access Control (rbCAC). The rbCAC algorithm defines access control within a cyber-physical environment in a manner which balances cost, risk, and net utility in a multi-authority setting. rbCAC is demonstrated it in an Air Travel and Border Services scenario. Other domains are also discussed included air traffic control threat prevention from drone identity attacks in protected airspaces. These contributions offer significant material for future development, ongoing credential and ecosystem design, including dynamic perimeters and continuous-time sampling, intelligent and self optimizing ecosystems, runtime collaborative platform design contracts and constraints, and analysis of APT attacks to SCADA systems using ecosystem approaches.