954 research outputs found

    Virtual sensor networks: collaboration and resource sharing

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    This thesis contributes to the advancement of the Sensing as a Service (SeaaS), based on cloud infrastructures, through the development of models and algorithms that make an efficient use of both sensor and cloud resources while reducing the delay associated with the data flow between cloud and client sides, which results into a better quality of experience for users. The first models and algorithms developed are suitable for the case of mashups being managed at the client side, and then models and algorithms considering mashups managed at the cloud were developed. This requires solving multiple problems: i) clustering of compatible mashup elements; ii) allocation of devices to clusters, meaning that a device will serve multiple applications/mashups; iii) reduction of the amount of data flow between workplaces, and associated delay, which depends on clustering, device allocation and placement of workplaces. The developed strategies can be adopted by cloud service providers wishing to improve the performance of their clouds. Several steps towards an efficient Se-aaS business model were performed. A mathematical model was development to assess the impact (of resource allocations) on scalability, QoE and elasticity. Regarding the clustering of mashup elements, a first mathematical model was developed for the selection of the best pre-calculated clusters of mashup elements (virtual Things), and then a second model is proposed for the best virtual Things to be built (non pre-calculated clusters). Its evaluation is done through heuristic algorithms having such model as a basis. Such models and algorithms were first developed for the case of mashups managed at the client side, and after they were extended for the case of mashups being managed at the cloud. For the improvement of these last results, a mathematical programming optimization model was developed that allows optimal clustering and resource allocation solutions to be obtained. Although this is a computationally difficult approach, the added value of this process is that the problem is rigorously outlined, and such knowledge is used as a guide in the development of better a heuristic algorithm.Esta tese contribui para o avanço tecnológico do modelo de Sensing as a Service (Se-aaS), baseado em infraestrutura cloud, através do desenvolvimento de modelos e algoritmos que resolvem o problema da alocação eficiente de recursos, melhorando os métodos e técnicas atuais e reduzindo os tempos associados `a transferência dos dados entre a cloud e os clientes, com o objetivo de melhorar a qualidade da experiência dos seus utilizadores. Os primeiros modelos e algoritmos desenvolvidos são adequados para o caso em que as mashups são geridas pela aplicação cliente, e posteriormente foram desenvolvidos modelos e algoritmos para o caso em que as mashups são geridas pela cloud. Isto implica ter de resolver múltiplos problemas: i) Construção de clusters de elementos de mashup compatíveis; ii) Atribuição de dispositivos físicos aos clusters, acabando um dispositivo físico por servir m´ múltiplas aplicações/mashups; iii) Redução da quantidade de transferência de dados entre os diversos locais da cloud, e consequentes atrasos, o que dependente dos clusters construídos, dos dispositivos atribuídos aos clusters e dos locais da cloud escolhidos para realizar o processamento necessário. As diferentes estratégias podem ser adotadas por fornecedores de serviço cloud que queiram melhorar o desempenho dos seus serviços.(…

    MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a museum

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    In recent years there has been a growing interest into the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discovering and following the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present MusA (Museum Assistant), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these application

    Resource allocation model for sensor clouds under the sensing as a service paradigm

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    The Sensing as a Service is emerging as a new Internet of Things (IoT) business model for sensors and data sharing in the cloud. Under this paradigm, a resource allocation model for the assignment of both sensors and cloud resources to clients/applications is proposed. This model, contrarily to previous approaches, is adequate for emerging IoT Sensing as a Service business models supporting multi-sensing applications and mashups of Things in the cloud. A heuristic algorithm is also proposed having this model as a basis. Results show that the approach is able to incorporate strategies that lead to the allocation of fewer devices, while selecting the most adequate ones for application needs.FCT (Foundation for Science and Technology) from Portugal within CEOT (Center for Electronic, Optoelectronic and Telecommunications) UID/MULTI/00631/2019info:eu-repo/semantics/publishedVersio

    RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

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    Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the first six months. The project aim is to scale the Erlang’s radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the effectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene

    SECURING THE DATA STORAGE AND PROCESSING IN CLOUD COMPUTING ENVIRONMENT

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    Organizations increasingly utilize cloud computing architectures to reduce costs and en- ergy consumption both in the data warehouse and on mobile devices by better utilizing the computing resources available. However, the security and privacy issues with publicly available cloud computing infrastructures have not been studied to a sufficient depth for or- ganizations and individuals to be fully informed of the risks; neither are private nor public clouds prepared to properly secure their connections as middle-men between mobile de- vices which use encryption and external data providers which neglect to encrypt their data. Furthermore, cloud computing providers are not well informed of the risks associated with policy and techniques they could implement to mitigate those risks. In this dissertation, we present a new layered understanding of public cloud comput- ing. On the high level, we concentrate on the overall architecture and how information is processed and transmitted. The key idea is to secure information from outside attack and monitoring. We use techniques such as separating virtual machine roles, re-spawning virtual machines in high succession, and cryptography-based access control to achieve a high-level assurance of public cloud computing security and privacy. On the low level, we explore security and privacy issues on the memory management level. We present a mechanism for the prevention of automatic virtual machine memory guessing attacks

    A comparison framework and review of service brokerage solutions for cloud architectures

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    Cloud service brokerage has been identified as a key concern for future cloud technology development and research. We compare service brokerage solutions. A range of specific concerns like architecture, programming and quality will be looked at. We apply a 2-pronged classification and comparison framework.We will identify challenges and wider research objectives based on an identification of cloud broker architecture concerns and technical requirements for service brokerage solutions. We will discuss complex cloud architecture concerns such as commoditisation and federation of integrated, vertical cloud stacks

    Service Composition for IP Smart Object using Realtime Web Protocols: Concept and Research Challenges

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    The Internet of Things (IoT) refers to a world-wide network of interconnected physical things using standardized communication protocols. Recent development of Internet Protocol (IP) stacks for resource-constrained devices unveils a possibility for the future IoT based on the stable and scalable IP technology much like today's Internet of computers. One important question remains: how can data and events (denoted as services) introduced by a variety of IP networked things be exchanged and aggregated e ciently in various application domains. Because the true value of IoT lies in the interaction of several services from physical things, answers to this question are essential to support a rapid creation of new IoT smart and ubiquitous applications. The problem is known as service composition. This article explains the practicability of the future full-IP IoT with realtime Web protocols to formally state the problem of service composition for IP smart objects, provides literature review, and discusses its research challenges

    RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

    Get PDF
    Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene
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