22 research outputs found

    Parallel and Distributed Computing

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    The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

    Efficient Passive Clustering and Gateways selection MANETs

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    Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets

    Entrega de conteúdos multimédia em over-the-top: caso de estudo das gravações automáticas

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    Doutoramento em Engenharia EletrotécnicaOver-The-Top (OTT) multimedia delivery is a very appealing approach for providing ubiquitous, exible, and globally accessible services capable of low-cost and unrestrained device targeting. In spite of its appeal, the underlying delivery architecture must be carefully planned and optimized to maintain a high Qualityof- Experience (QoE) and rational resource usage, especially when migrating from services running on managed networks with established quality guarantees. To address the lack of holistic research works on OTT multimedia delivery systems, this Thesis focuses on an end-to-end optimization challenge, considering a migration use-case of a popular Catch-up TV service from managed IP Television (IPTV) networks to OTT. A global study is conducted on the importance of Catch-up TV and its impact in today's society, demonstrating the growing popularity of this time-shift service, its relevance in the multimedia landscape, and tness as an OTT migration use-case. Catch-up TV consumption logs are obtained from a Pay-TV operator's live production IPTV service containing over 1 million subscribers to characterize demand and extract insights from service utilization at a scale and scope not yet addressed in the literature. This characterization is used to build demand forecasting models relying on machine learning techniques to enable static and dynamic optimization of OTT multimedia delivery solutions, which are able to produce accurate bandwidth and storage requirements' forecasts, and may be used to achieve considerable power and cost savings whilst maintaining a high QoE. A novel caching algorithm, Most Popularly Used (MPU), is proposed, implemented, and shown to outperform established caching algorithms in both simulation and experimental scenarios. The need for accurate QoE measurements in OTT scenarios supporting HTTP Adaptive Streaming (HAS) motivates the creation of a new QoE model capable of taking into account the impact of key HAS aspects. By addressing the complete content delivery pipeline in the envisioned content-aware OTT Content Delivery Network (CDN), this Thesis demonstrates that signi cant improvements are possible in next-generation multimedia delivery solutions.A entrega de conteúdos multimédia em Over-The-Top (OTT) e uma proposta atractiva para fornecer um serviço flexível e globalmente acessível, capaz de alcançar qualquer dispositivo, com uma promessa de baixos custos. Apesar das suas vantagens, e necessario um planeamento arquitectural detalhado e optimizado para manter níveis elevados de Qualidade de Experiência (QoE), em particular aquando da migração dos serviços suportados em redes geridas com garantias de qualidade pré-estabelecidas. Para colmatar a falta de trabalhos de investigação na área de sistemas de entrega de conteúdos multimédia em OTT, esta Tese foca-se na optimização destas soluções como um todo, partindo do caso de uso de migração de um serviço popular de Gravações Automáticas suportado em redes de Televisão sobre IP (IPTV) geridas, para um cenário de entrega em OTT. Um estudo global para aferir a importância das Gravações Automáticas revela a sua relevância no panorama de serviços multimédia e a sua adequação enquanto caso de uso de migração para cenários OTT. São obtidos registos de consumos de um serviço de produção de Gravações Automáticas, representando mais de 1 milhão de assinantes, para caracterizar e extrair informação de consumos numa escala e âmbito não contemplados ate a data na literatura. Esta caracterização e utilizada para construir modelos de previsão de carga, tirando partido de sistemas de machine learning, que permitem optimizações estáticas e dinâmicas dos sistemas de entrega de conteúdos em OTT através de previsões das necessidades de largura de banda e armazenamento, potenciando ganhos significativos em consumo energético e custos. Um novo mecanismo de caching, Most Popularly Used (MPU), demonstra um desempenho superior as soluções de referencia, quer em cenários de simulação quer experimentais. A necessidade de medição exacta da QoE em streaming adaptativo HTTP motiva a criaçao de um modelo capaz de endereçar aspectos específicos destas tecnologias adaptativas. Ao endereçar a cadeia completa de entrega através de uma arquitectura consciente dos seus conteúdos, esta Tese demonstra que são possíveis melhorias de desempenho muito significativas nas redes de entregas de conteúdos em OTT de próxima geração

    An Investigation into Trust and Reputation Frameworks for Autonomous Underwater Vehicles

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    As Autonomous Underwater Vehicles (AUVs) become more technically capable and economically feasible, they are being increasingly used in a great many areas of defence, commercial and environmental applications. These applications are tending towards using independent, autonomous, ad-hoc, collaborative behaviour of teams or fleets of these AUV platforms. This convergence of research experiences in the Underwater Acoustic Network (UAN) and Mobile Ad-hoc Network (MANET) fields, along with the increasing Level of Automation (LOA) of such platforms, creates unique challenges to secure the operation and communication of these networks. The question of security and reliability of operation in networked systems has usually been resolved by having a centralised coordinating agent to manage shared secrets and monitor for misbehaviour. However, in the sparse, noisy and constrained communications environment of UANs, the communications overheads and single-point-of-failure risk of this model is challenged (particularly when faced with capable attackers). As such, more lightweight, distributed, experience based systems of “Trust” have been proposed to dynamically model and evaluate the “trustworthiness” of nodes within a MANET across the network to prevent or isolate the impact of malicious, selfish, or faulty misbehaviour. Previously, these models have monitored actions purely within the communications domain. Moreover, the vast majority rely on only one type of observation (metric) to evaluate trust; successful packet forwarding. In these cases, motivated actors may use this limited scope of observation to either perform unfairly without repercussions in other domains/metrics, or to make another, fair, node appear to be operating unfairly. This thesis is primarily concerned with the use of terrestrial-MANET trust frameworks to the UAN space. Considering the massive theoretical and practical difference in the communications environment, these frameworks must be reassessed for suitability to the marine realm. We find that current single-metric Trust Management Frameworks (TMFs) do not perform well in a best-case scaling of the marine network, due to sparse and noisy observation metrics, and while basic multi-metric communications-only frameworks perform better than their single-metric forms, this performance is still not at a reliable level. We propose, demonstrate (through simulation) and integrate the use of physical observational metrics for trust assessment, in tandem with metrics from the communications realm, improving the safety, security, reliability and integrity of autonomous UANs. Three main novelties are demonstrated in this work: Trust evaluation using metrics from the physical domain (movement/distribution/etc.), demonstration of the failings of Communications-based Trust evaluation in sparse, noisy, delayful and non-linear UAN environments, and the deployment of trust assessment across multiple domains, e.g. the physical and communications domains. The latter contribution includes the generation and optimisation of cross-domain metric composition or“synthetic domains” as a performance improvement method

    Discount options as a financial instrument supporting REDD +

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