This thesis deals with the business processes related to warehouse management in one of distribution centers of the brewing group in which this draft leads to an up-to-date solution to the use of new warehouse and infromation technologies.

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Many hard drives manufactured today use the Serial ATA (SATA) protocol to communicate with the host machine, typically a PC. SATA is a much faster and much more robust protocol than its predecessor, ATA (also referred to as Parallel ATA or IDE). Many hardware designs, including those using Field-Programmable Gate Arrays (FPGAs), have a need for a long-term storage solution, and a hard drive would be ideal. One such design is the high-speed Data Acquisition System (DAS) created for the NASA Surface Water and Ocean Topography mission. This system utilizes a Xilinx Virtex-4 FPGA. Although the DAS includes a SATA connector for interfacing with a disk, a SATA core is needed to implement the protocol for disk operations. In this work, an open-source SATA core for Virtex-4 FPGAs has been created. SATA cores for Virtex-5 and Virtex-6 devices were already available, but they are not compatible with the different serial transceivers in the Virtex-4. The core can interface with disks at SATA I or SATA II speeds, and has been shown working at rates up to 180MB/s. It has been successfully integrated into the hardware design of the DAS board so that radar samples can be stored on the disk.

Document retrieval systems recover documents from a dataset and order them according to their perceived relevance to a user’s search query. This is a difficult task for machines to accomplish because there exists a semantic gap between the meaning of the terms in a user’s literal query and a user’s true intentions. Even with this ambiguity that arises with a lack of context, users still expect that the set of documents returned by a search engine is both highly relevant to their query and properly ordered. The focus of this thesis is on document retrieval systems that explore methods of ordering documents from unstructured, textual corpora using text queries. The main goal of this study is to enhance the Okapi BM25 document retrieval model. In doing so, this research hypothesizes that the structure of text inside documents and queries hold valuable semantic information that can be incorporated into the Okapi BM25 model to increase its performance. Modifications that account for a term’s part of speech, the proximity between a pair of related terms, the proximity of a term with respect to its location in a document, and query expansion are used to augment Okapi BM25 to increase the model’s performance. The study resulted in 87 modifications which were all validated using open source corpora. The top scoring modification from the validation phase was then tested under the Lisa corpus and the model performed 10.25% better than Okapi BM25 when evaluated under mean average precision. When compared against two industry standard search engines, Lucene and Solr, the top scoring modification largely outperforms these systems by upwards to 21.78% and 23.01%, respectively.

The performance of storage systems is central to handling the huge amount of data being generated from a variety of sources including scientific experiments, social media, crowdsourcing, and from an increasing variety of cyber-physical systems. The emerging high-speed storage technologies enable the ingestion of and access to such large volumes of data efficiently. However, the combination of high data volume requirements of new applications that largely generate unstructured and semistructured streams of data combined with the emerging high-speed storage technologies pose a number of new challenges, including the low latency handling of such data and ensuring that the network providing access to the data does not become the bottleneck. The traditional relational model is not well suited for efficiently storing and retrieving unstructured and semi-structured data. An alternate mechanism, popularly known as Key-Value Store (KVS) has been investigated over the last decade to handle such data. A KVS store only needs a 'key' to uniquely identify the data record, which may be of variable length and may or may not have further structure in the form of predefined fields. Most of the KVS in existence have been designed for hard-disk based storage (before the SSDs gain popularity) where avoiding random accesses is crucial for good performance. Unfortunately, as the modern solid-state drives become the norm as the data center storage, the HDD-based KV structures result in high read, write, and space amplifications which becomes detrimental to both the SSD’s performance and endurance. Also note that regardless of how the storage systems are deployed, access to large amounts of storage by many nodes must necessarily go over the network. At the same time, the emerging storage technologies such as Flash, 3D-crosspoint, phase change memory (PCM), etc. coupled with highly efficient access protocols such as NVMe are capable of ingesting and reading data at rates that challenge even the leading edge networking technologies such as 100Gb/sec Ethernet. At the same time, some of the higher-end storage technologies (e.g., Intel Optane storage based on 3-D crosspoint technology, PCM, etc.) coupled with lean protocols like NVMe are capable of providing storage access latencies in the 10-20$\mu s$ range, which means that the additional latency due to network congestion could become significant. The purpose of this thesis is to addresses some of the aforementioned issues. We propose a new hash-based and SSD-friendly key-value store (KVS) architecture called FlashKey which is especially designed for SSDs to provide low access latencies, low read and write amplification, and the ability to easily trade-off latencies for any sequential access, for example, range queries. Through detailed experimental evaluation of FlashKey against the two most popular KVs, namely, RocksDB and LevelDB, we demonstrate that even as an initial implementation we are able to achieve substantially better write amplification, average, and tail latency at a similar or better space amplification. Next, we try to deal with network congestion by dynamically replicating the data items that are heavily used. The tradeoff here is between the latency and the replication or migration overhead. It is important to reverse the replication or migration as the congestion fades away since our observation tells that placing data and applications (that access the data) together in a consolidated fashion would significantly reduce the propagation delay and increase the network energy-saving opportunities which is required as the data center network nowadays are equipped with high-speed and power-hungry network infrastructures. Finally, we designed a tradeoff between network consolidation and congestion. Here, we have traded off the latency to save power. During the quiet hours, we consolidate the traffic is fewer links and use different sleep modes for the unused links to save powers. However, as the traffic increases, we reactively start to spread out traffic to avoid congestion due to the upcoming traffic surge. There are numerous studies in the area of network energy management that uses similar approaches, however, most of them do energy management at a coarser time granularity (e.g. 24 hours or beyond). As opposed to that, our mechanism tries to steal all the small to medium time gaps in traffic and invoke network energy management without causing a significant increase in latency. / Computer and Information Science

Dans le domaine aéronautique, l'optimisation du rendement énergétique global, la réduction des masses embarquées et la nécessité de répondre aux besoins énergétiques croissants conduisent à développer de nouvelles technologies et méthodes pour générer l'énergie électrique à bord, pour la distribuer, la convertir et la stocker. Dans cette thèse, des éléments de stockage de l'énergie électrique sont caractérisés dans l'optique d'être modélisés. Parmi les différents systèmes de stockage, présentés dans un état de l'art préliminaire, sont retenus les supercondensateurs et les accumulateurs électrochimiques Lithium-ion polymère, considérés respectivement comme des sources de puissance et d'énergie, à l'échelle de l'application. Ces moyens de stockage sont caractérisés par chronopotentiométrie à courant constant et par spectrométrie d'impédance électrochimique. Les essais sont éffectués dans des conditions expérimentales, définissant le domaine de validités des modèles, en cohérence avec les contraintes de l'application finale. Différents modèles sont alors développés en fonction de leur utilisation : des modèles simples, fonctionnels et suffisants pour la gestion globale d'énergie et des modèles dynamiques, comportementaux et nécessaires pour l'analyse de la qualité du réseau. Ils sont ensuite validés sur des profils de mission. Pour disposer d'un système de stockage performant et en adéquation avec les besoins énergétiques de l'aéronef, une méthode de dimensionnement est proposée, associant des composants de stockage complémentaires. Un gestion fréquentielle des sources est mise en oeuvre de manière à minimiser la masse du système de stockage. / In aeronautics, the optimization of the global energetic efficiency, the reduction of the embedded weight and the need to meet the growing energetic requirements lead to develop new technologies and methods to generate electrical energy, to distribute it, to convert it and to store it aboard. In this thesis, electrical energy storage systems are characterized with a view to be modeled. Among varied storage systems, presented in an introductory state of the art, ultracapacitors and Lithium-ion polymer secondary batteries are studied. These components are considered respectively as power and energy sources, in regards to the application scale. These storage systems are characterized by chronopotentiometry at constant current and by electrochemical impedance spectrometry. Tests are carried out in experimental conditions which define the validity area of modeling, in relation with the application constraints. Different models are developed according to their future use : simple models, which are functional and sufficient for the global energy management, and dynamics models, which are behavioral and necessary for the analysis of the network quality. Then, they validated thanks to mission profiles. Finally, to dispose of an efficient storage system that meets the energetic requirements of the aircraft, a sizing method is suggested by combining complementary storage systems. An energy management based on frequency approach is implemented in order to minimize the storage system weight.

Maintaining closeness between data sources and data consumers is crucial for workload I/O performance. In cloud environments, this kind of closeness can be violated by system administrative events and storage architecture barriers. VM migration events are frequent in cloud environments. VM migration changes VM runtime inter-connection or cache contexts, significantly degrading VM I/O performance. Virtualization is the backbone of cloud platforms. I/O virtualization adds additional hops to workload data access path, prolonging I/O latencies. I/O virtualization overheads cap the throughput of high-speed storage devices and imposes high CPU utilizations and energy consumptions to cloud infrastructures. To maintain the closeness between data sources and workloads during VM migration, we propose Clique, an affinity-aware migration scheduling policy, to minimize the aggregate wide area communication traffic during storage migration in virtual cluster contexts. In host-side caching contexts, we propose Successor to recognize warm pages and prefetch them into caches of destination hosts before migration completion. To bypass the I/O virtualization barriers, we propose VIP, an adaptive I/O prefetching framework, which utilizes a virtual I/O front-end buffer for prefetching so as to avoid the on-demand involvement of I/O virtualization stacks and accelerate the I/O response. Analysis on the traffic trace of a virtual cluster containing 68 VMs demonstrates that Clique can reduce inter-cloud traffic by up to 40%. Tests of MPI Reduce_scatter benchmark show that Clique can keep VM performance during migration up to 75% of the non-migration scenario, which is more than 3 times of the Random VM choosing policy. In host-side caching environments, Successor performs better than existing cache warm-up solutions and achieves zero VM-perceived cache warm-up time with low resource costs. At system level, we conducted comprehensive quantitative analysis on I/O virtualization overheads. Our trace replay based simulation demonstrates the effectiveness of VIP for data prefetching with ignorable additional cache resource costs.

The ship emission already occupy the eighth position in the world biggest emitters ranking. This happens because the ship operations have a huge demand variation therefore in order to reduce the ship emissions is required an efficient operation of the generators. This work aims at integrating advanced storage systems into the operation of diesel generators. The variation of the operation point has a direct interference on the emissions and on the diesel consumption, this variation is allowed through the frequency and voltage control. The use of lithium batteries for various operation points of the generators is analyzed. The use of an energy storage system allowed the operation of the generators in a better operation point therefore there was a reduction in diesel consumption and in CO2 emissions when the diesel generators. The main result of this work could also shed light in the operation of isolated power systems equipped with advanced storage systems and diesel generators. / As emissões dos navios já ocupam a oitava posição entre os países com maior emissão no mundo. Isso pode ser explicado pelo fato de que as operações dos navios têm uma grande variação de demanda de potência, com isso a operação inteligente dos geradores a diesel é fundamental para a redução das emissões. A abordagem desenvolvida nesse trabalho integra o uso de sistemas de armazenamento avançados na operação dos geradores a diesel. A variação do ponto de operação dos geradores a diesel interfere diretamente no consumo e nas emissões, essa variação só é possível por meio do controle de frequência e tensão providos pelo sistema de armazenamento de energia. Nesse trabalho foram analisados o uso de baterias de lítio para diferentes pontos de operação do gerador a diesel. O uso das baterias possibilitou a operação dos geradores num melhor ponto de carga com isso houve uma redução das emissões e do consumo de combustível. Os resultados encontrados nesse trabalho podem ser extrapolados qualitativamente para outros sistemas de potência offshore, como plataformas de petróleo e de perfuração, que operem com sistemas de baterias avançadas e geradores a diesel.

Os Sistemas de Armazenamento a Baterias (SAEB) têm demonstrado uma grande flexibilidade de aplicações em melhorias e resoluções de problemas em Sistemas de Distribuição de Energia Elétrica (SDEEs). Grandes variações no valor de tensão dentro de um período, seja diário ou semanal, são observados devido à predominante topologia radial dos SDEEs e o constante aumento da utilização de Geradores Distribuídos (GDs). Pelas características de operar como carga ou geração, os SAEBs podem ser utilizados para melhorar o perfil de tensão. No entanto, as restrições de operação desses dispositivos tornam dificultoso identificar bons momentos de atuação e barramentos de alocação para este propósito. Geralmente, essa atuação é tratada de uma forma dependente dos GDs, porém essa abordagem não permite que os SAEBs possam operar em momentos independentes a fim de melhorar o perfil de tensão do SDEE. Desta forma, neste trabalho é desenvolvida uma abordagem para o planejamento da alocação e atuação do SAEB, utilizando uma modificação no algoritmo Particle Swarm Optimization (PSO) de forma que o SAEB possa atuar independente dos GDs e ser alocado em outras barras, com o objetivo de melhorar o perfil de tensão. As soluções são analisadas através de simulações de Monte Carlo para investigar o comportamento em diversas situações de curva de carga. Os resultados demonstram que a abordagem proposta busca encontrar boas alocações e atuações e que os parâmetros técnicos dos SAEBs, como capacidade de energia armazenada e potência nominal do inversor, influenciam diretamente nos resultados. / Battery Energy Storage Systems (BESS) have demonstrated great flexibility of applications in improvements and problem-solving in Electrical Distribution Systems (DSs). Significant variations in the nominal voltage value within a period, either daily or weekly, are observed due to the predominant radial topology of the DSs and the constant increase of the use of Distributed Generators (DGs). By the characteristics of operating as load or generation, SAEBs can be used to improve the voltage profile. However, the restrictions of these devices make it difficult to identify good operating moments and allocation buses for this purpose. Generally, this operation is treated in a way dependent on the DGs, but this strategy does not allow the BESS to operate at independent moments to improve the voltage profile of the SDEE. Thus, in this work an approach is developed for SAEBs allocation and operation planning, using a modification in the Particle Swarm Optimization (PSO) algorithm so that the SAEB can operate independently of the GDs and be allocated in other bars, with the objective to improve the voltage profile. The solutions are analyzed through Monte Carlo simulations to investigate the behavior in various load curve situations. The results demonstrate that the proposed approach seeks to find proper allocations and actions and that the technical parameters of SAEBs directly influence the results.

The way the world creates and distributes energy is changing. In 2015 77% of the world’s new power generation installations were either wind or solar PV. These forms of energy are by their nature intermittent – the sun will never shine 24 hours a day. With the rise of these intermittent energy sources, the need to store the energy they create has also risen. Batteries are emerging as a popular choice to solve this problem, with some analysts predicting that by 2024 battery energy storage will reach a scale of 12.5 gigawatts and become an industry with $165 billion in annual revenue. The increase in electric vehicles has caused the average price of lithium-ion batteries to plummet in recent years with expectations of this trend continuing. Managing the energy stored in many, distributed batteries is difficult, but when done right has numerous benefits. This business plan outlines the way Energy Max will provide a software platform to manage battery energy storage. Energy Max plans to sell its software directly to battery energy storage system manufacturers. The company will leverage its connections in Asia in order to focus on potential customers in China and Taiwan. By pursuing this strategy, the company can become a trusted partner to these manufacturers in helping them build a more complete solution to provide end-users. In return for providing the software, customers will be required to pay a one-time integration fee as well as a $15/kWh fee for batteries utilizing the software. This business plans assumes the first year of operations will be spent both building the product and developing Energy Max’s pipeline of future customers. In Year 2 the company will have two customers, but deployment of batteries with the software platform will still be low due to the likely cautious nature of customers. Under a normal growth scenario, the company will grow to Year 5 when Energy Max will attract 18 customers and have its software on 1% of worldwide Li-ion energy storage installations. Following this plan will require $3.5 million of outside funding and positive net income after tax in Year 4.