ABSTRACT Broadcasting data delivery is rapidly becoming the good choice for disseminating information to a massive user population in many new application areas where the client-to-server communication is limited. There are two different ways of data dissemination. One is called push-based that the data items are broadcasted periodically in the channels, another one is called pull-based that the client requests a piece of data on the uplink channel and the server responds by sending this piece of data to the client. In push-based, most of the previous researches assume that each mobile client needs only one data item. However, in many situations, a mobile client might need more than one data item. In pull-based, the data items were broadcasted dynamically. Most of the previous researches assume that the data items which requested by the clients are of the same size. However, the data items may of different sizes in reality. In this thesis, we propose Improved QDS Expansion Method (Improved-QEM) and Heuristic On-line Algorithm to overcome the above two weaknesses, respectively. The issue of scheduling the broadcast data for the situation that each client may access multiple data items can not be simply considered as multiple subissues. There have been two methods was proposed, Query Expansion Method (QEM) and Modified Query Expansion Methods (Modified-QEM). These two methods are heuristic-based algorithm and do not provide the optimal solution. To improve the performance, our Improved-QEM is an efficient scheduling for query-set-based broadcasting, which is integrated with Query Expansion Method (QEM) and mining association rules technique. The mining association rules can globally find the data item sets (large itemsets) which are requested by clients, frequently. From our simulation results, we show that, as compared to the local optimal approach in the previous methods, our Improved-QEM can construct the schedule with the smaller TQD than that constructed by QEM and Modified-QEM, where TQD is denotes Total Query Distance and is proportional to the average access time. The on-line (push-based) algorithms are easy to adapt to time varying demands for the data items, which uses some decision-making mechanism to determine which data item is to be broadcasted next. Hence, when the number of data items is huge, it is important to schedule broadcasting program such that, it can provide the small overall mean access time. Therefore, Vaidya and Hameed have proposed two on-line algorithms, On-line Algorithm and On-line with Bucketing Algorithm. The main disadvantage of On-line Algorithm is the heavy run-time overhead and the main disadvantage of On-line Algorithm with Bucketing is the poor performance of the overall mean access time. Therefore, we propose the heuristic on-line algorithm to solve these two problems. From our simulation results, we show that our heuristic algorithm provides the performance that closes to the overall mean access time and has with low run-time overhead.

Submitted by Kamila Costa (kamilavasconceloscosta@gmail.com) on 2015-06-18T18:45:56Z No. of bitstreams: 1 Tese-Rodrigo Ribeiro de Oliveira.pdf: 2799682 bytes, checksum: 60b9680a231c5e27560663458d4e673d (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-19T20:40:50Z (GMT) No. of bitstreams: 1 Tese-Rodrigo Ribeiro de Oliveira.pdf: 2799682 bytes, checksum: 60b9680a231c5e27560663458d4e673d (MD5) / Made available in DSpace on 2015-06-19T20:40:50Z (GMT). No. of bitstreams: 1 Tese-Rodrigo Ribeiro de Oliveira.pdf: 2799682 bytes, checksum: 60b9680a231c5e27560663458d4e673d (MD5) Previous issue date: 2015-03-27 / This PhD thesis presents a novel hardware reconfiguration methodology, which uses the digital TV broadcast signal for reconfiguring hardware modules in digital TV receivers. The proposed methodology allows hardware cores to be signaled, during the transport stream generation step, transmitted and then reassembled. At the receiver, the recovered cores are then used to reconfigure reprogrammable field programmable gate array (FPGA) devices, which are integrated into each receiver unit. Besides, content signaling allows receivers to choose between FPGA cores synthesized for different manufacturers, which enables receivers to select broadcast hardware cores related to the employed FPGA models. The results of the performed experiments, which were carried out during the development of this work, consist in a proof of concept and show the technical feasibility of this methodology, regarding reconfiguration of pre-synthesized hardware cores through the digital TV environment. Receiver manufacturers could benefit from this methodology for developing reconfigurable architectures, which would allow the incorporation of technological advances into receiver hardware and provide better control regarding product life cycle. As a result, future revisions of DTV standards could occur without the need for device replacement. / Esta tese de doutorado apresenta uma metodologia de reconfiguração de hardware, que utiliza o sinal da emissora de TV digital como base para atualizar módulos de receptores de TV digital. A metodologia proposta permite que núcleos de hardware sejam sinalizados, durante a geração do fluxo de transporte, transmitidos e posteriormente remontados. Desse modo, os núcleos recebidos são usados na reconfiguração de dispositivos baseados em lógica reprogramável (field programable gate array - FPGA), que estão integrados ao hardware de cada unidade receptora. Além disso, a sinalização de conteúdo permite a distinção entre núcleos sintetizados para FPGAs de diferentes fabricantes, o que habilita receptores de TV digital a selecionar somente núcleos de hardware relativos aos modelos de FPGA utilizados. Os resultados obtidos com os experimentos realizados, durante o desenvolvimento deste trabalho, consistem em uma prova de conceito e demonstram a viabilidade técnica do uso desta metodologia de transmissão e reconfiguração, para núcleos pré-sintetizados de hardware enviados em um ambiente de televisão digital. Fabricantes de receptores poderiam utilizar os benefícios desta metodologia para o desenvolvimento de arquiteturas reconfiguráveis, o que permitiria a incorporação de avanços tecnológicos às funções de hardware do receptor e um maior controle do ciclo de vida de produto. Como resultado, futuras revisões de normas de TV Digital não resultariam em troca de equipamento.

Les infrastructures de calcul très haute performance ont connu une croissance rapide en particulier ces dernières années. Cette croissance a toujours été motivée par les besoins accrus en puissance de calcul qu'expriment les scientifiques dans divers domaines. Cependant, ces systèmes devenus de plus en plus larges constituent de gros consommateurs d'électricité et consomment déjà plusieurs mégawatts. Afin de consommer ''moins'' et ''mieux'', nous avons proposé un environnement logiciel qui d'une part, permet de choisir avant de pré-exécuter l'application, les versions de services applicatifs consommant le moins d'énergie, et qui d'autre part, repose sur une grille électrique intelligente pour planifier les réservations des ressources de calcul de ces infrastructures. Cet environnement, appelé SESAMES, a été adapté à deux services applicatifs indispensables au calcul très haute performance : la tolérance aux pannes et la diffusion de données. Des validations expérimentales ont montré que l'on peut réduire la consommation énergétique de chacun des deux services étudiés en s'appuyant sur les estimations énergétiques précises fournies par SESAMES pour n'importe quel contexte d'exécution et pour n'importe quelle plate-forme dotée de wattmètres. Notre méthodologie d'estimation repose sur une description du contexte d'exécution et sur une calibration de la plate-forme d'exécution basée sur la collecte de mesures énergétiques. Des simulations ont démontré que l'ordonnanceur multi-critères des réservations de ressources proposé dans SESAMES, permet de réduire à la fois la consommation énergétique, le coût financier et l'impact environnemental de ces réservations, tout en respectant les contraintes imposées par l'utilisateur et le fournisseur d'énergie. / High performance computing (HPC) infrastructures have experienced a rapid growth, particularly these last years. This growth has been driven by the increased need in terms of computational power expressed by scientists in various fields. However, their increasing size makes them important electricity consumers since they already consume several megawatts. In order to consume "less" and better", we proposed a framework which permits to choose the less consuming versions of the services before pre-executing the application. In addition, our framework relies on a smart grid in order to schedule resource reservations on these computing infrastructures. This framework, called SESAMES, is adapted to two services required in high performance computing: fault tolerance and data broadcasting. Experimental validations have shown that we can reduce the energy consumption of both services by relying on accurate energy estimations provided by SESAMES for any execution context and for any platform equipped with wattmeters. Our estimation methodology is based on a description of the execution context and on a platform calibration that consists of gathering energy measurements. Simulations have shown that the multi-criteria reservation scheduler proposed in SESAMES, simultaneously reduces the energy consumption, the financial cost and the environmental impact of these reservations, while respecting the constraints imposed by the user and the energy supplier.