Estimating data divergence in cloud computing storage systems

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Enabling dCache to use preexistent mass storage systems

A mesura que la investigació depèn cada vegada més dels computadors, l'emmagatzematge de dades comença a convertir-se en un recurs escàs per als projectes, i suposa una gran part del cost total. Alguns projectes intenten resoldre aquest problema emprant emmagatzament distribuït. És doncs necessari que alguns centres proveeixin de grans quantitats d'emmagatzematge massiu de baix cost basat en cintes magnètiques. L'inconvenient d'aquesta solució és que el rendiment disminueix, particularment a l'hora de tractar-se de grans quantitats d'arxius petits. El nostre objectiu és crear un híbrid entre un sistema d'alt cost i rendiment basat en discs, i un de baix cost i rendiment basat en cintes. Per això, unirem dCache, un sistema d'emmagatzematge distribuït, amb Castor, un sistema d'emmagatzematge jeràrquic, creant sistemes de fitxers virtuals que contindran grans quantitats d'arxius petits per millorar el rendiment global del sistema.

Power Consumption in Carbon Capture and Storage Systems (CCS) and Possibilities to Reduce Power Consumption with Variable Speed Drives

The aim of this master´s thesis is to study which processes increase the auxiliary power consumption in carbon capture and storage processes and if it is possible to reduce the auxiliary power consumption with variable speed drives. Also the cost of carbon capture and storage is studied. Data about auxiliary power consumption in carbon capture is gathered from various studies and estimates made by various research centres. Based on these studies a view is presented how the power auxiliary power consumption is divided between different processes in carbon capture processes. In a literary study, the operation of three basic carbon capture systems is described. Also different methods to transport carbon dioxide and carbon dioxide storage options are described in this section. At the end of the thesis processes that consume most of the auxiliary power are defined and possibilities to reduce the auxiliary power consumption are evaluated. Cost of carbon capture, transport and storage are also evaluated at this point and in the case that the carbon capture and storage systems are fully deployed. According to the results, it can be estimated what are the processes are where variable speed drives can be used and what kind of cost and power consumption reduction could be achieved. Results also show how large a project carbon capture and storage is if it is fully deployed.

Performance Degradation Modelling and Techno-Economic Analysis of Lithium-Ion Battery Energy Storage Systems

Transmission system operators and distribution system operators are experiencing new challenges in terms of reliability, power quality, and cost efficiency. Although the potential of energy storages to face those challenges is recognized, the economic implications are still obscure, which introduce the risk into the business models. This thesis aims to investigate the technical and economic value indicators of lithium-ion battery energy storage systems (BESS) in grid-scale applications. In order to do that, a comprehensive performance lithium-ion BESS model with degradation effects estimation is developed. The model development process implies literature review on lifetime modelling, use, and modification of previous study progress, building the additional system parts and integrating it into a complete tool. The constructed model is capable of describing the dynamic behavior of the BESS voltage, state of charge, temperature and capacity loss. Five control strategies for BESS unit providing primary frequency regulation are implemented, in addition to the model. The questions related to BESS dimensioning and the end of life (EoL) criterion are addressed. Simulations are performed with one-month real frequency data acquired from Fingrid. The lifetime and cost-benefit analysis of the simulation results allow to compare and determine the preferable control strategy. Finally, the study performs the sensitivity analysis of economic profitability with variable size, EoL and system price. The research reports that BESS can be profitable in certain cases and presents the recommendations.

Using Neo4J geospatial data storage and integration

Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.

Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

Design and Off-design modelling of advanced Power-to-Gas energy storage systems

Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.

Energy storage systems (sistemas de armazenamento de energia)

O armazenamento de energia pode ser efetuado sobre cinco categorias, designadamente, elétrica, eletromecânica, mecânica, térmica e química. Contudo, o assunto aqui debatido é sobre meios de armazenamento de energia elétrica, sendo que o armazenamento de eletricidade é usualmente efetuado recorrendo a outros géneros de energia, tais como, química, mecânica, térmica ou, até, em energia potencial. [1]. Há nos dias de hoje uma crescente preocupação na forma como é gerido o setor elétrico, uma vez que este implica um elevado impacto ambiental. Neste sentido tem havido algumas alterações, nomeadamente, no que diz respeito à produção de energia elétrica. A utilização de energias renováveis estão cada vez mais presentes na produção de eletricidade (Figura 1), pois permitem diminuir de forma indireta a utilização dos combustíveis fósseis, sendo esta a principal vantagem face às centrais de produção convencionais.

A constructive technology assessment of stationary energy storage systems: prospective life cycle orientated analysis

Based on the presentation and discussion at the 3rd Winter School on Technology Assessment, December 2012, Universidade Nova de Lisboa (Portugal), Caparica Campus, PhD programme on Technology Assessment

The role of qualitative data and systems thinking in addressing service decline in market towns

Retail services are a main contributor to municipal budget and are an activity that affects perceived quality-of-life, especially for those with mobility difficulties (e.g. the elderly, low income citizens). However, there is evidence of a decline in some of the services market towns provide to their citizens. In market towns, this decline has been reported all over the western world, from North America to Australia. The aim of this research was to understand retail decline and enlighten on some ways of addressing this decline, using a case study, Thornbury, a small town in the Southwest of England. Data collected came from two participatory approaches: photo-surveys and multicriteria mapping. The interpretation of data came from using participants as analysts, but also, using systems thinking (systems diagramming and social trap theory) for theory building. This research moves away from mainstream economic and town planning perspectives by making use of different methods and concepts used in anthropology and visual sociology (photo-surveys), decision-making and ecological economics (multicriteria mapping and social trap theory). In sum, this research has experimented with different methods, out of their context, to analyse retail decline in a small town. This research developed a conceptual model for retail decline and identified the existence of conflicting goals and interests and their implications for retail decline, as well as causes for these. Most of the potential causes have had little attention in the literature. This research also identified that some of the measures commonly used for dealing with retail decline may be contributing to the causes of retail decline itself. Additionally, this research reviewed some of the measures that can be used to deal with retail decline, implications for policy-making and reflected on the use of the data collection and analysis methods in the context of small to medium towns.

Assessing the feasibility of impregnating phase change materials in lightweight aggregate for development of thermal energy storage systems

This paper assesses the feasibility of impregnation/encasement of phase change materials (PCMs) in lightweight aggregates (LWAs). An impregnation process was adopted to carry out the encasement study of two different PCMs in four different LWAs. The leakage of the impregnated/encased PCMs was studied when they were submitted to freeze/thawing and oven drying tests, separately. The results confirmed that, the impregnation/encasement method is effective with respect to the large thermal energy storage density, and can be suitable for applications were PCMs cannot be incorporated directly such as asphalt road pavements.

A domain-specific language for ETL patterns specification in Data Warehousing Systems

During the last few years many research efforts have been done to improve the design of ETL (Extract-Transform-Load) systems. ETL systems are considered very time-consuming, error-prone and complex involving several participants from different knowledge domains. ETL processes are one of the most important components of a data warehousing system that are strongly influenced by the complexity of business requirements, their changing and evolution. These aspects influence not only the structure of a data warehouse but also the structures of the data sources involved with. To minimize the negative impact of such variables, we propose the use of ETL patterns to build specific ETL packages. In this paper, we formalize this approach using BPMN (Business Process Modelling Language) for modelling more conceptual ETL workflows, mapping them to real execution primitives through the use of a domain-specific language that allows for the generation of specific instances that can be executed in an ETL commercial tool.

Errores en sistemas de procesamiento de datos debido a eventos transitorios en interfaces analógicas: aportes a la mitigación de los mismos. Errors in data processing systems due to single transient events affecting analog interfaces: contributions to their mitigation.

Los eventos transitorios únicos analógicos (ASET, Analog Single Event Transient) se producen debido a la interacción de un ión pesado o un protón de alta energía con un dispositivo sensible de un circuito analógico. La interacción del ión con un transistor bipolar o de efecto de campo MOS induce pares electrón-hueco que provocan picos que pueden propagarse a la salida del componente analógico provocando transitorios que pueden inducir fallas en el nivel sistema. Los problemas más graves debido a este tipo de fenómeno se dan en el medioambiente espacial, muy rico en iones pesados. Casos típicos los constituyen las computadoras de a bordo de satélites y otros artefactos espaciales. Sin embargo, y debido a la continua contracción de dimensiones de los transistores (que trae aparejado un aumento de sensibilidad), este fenómeno ha comenzado a observarse a nivel del mar, provocado fundamentalmente por el impacto de neutrones atmosféricos. Estos efectos pueden provocar severos problemas a los sistemas informáticos con interfaces analógicas desde las que obtienen datos para el procesamiento y se han convertido en uno de los problemas más graves a los que tienen que hacer frente los diseñadores de sistemas de alta escala de integración. Casos típicos son los Sistemas en Chip que incluyen módulos de procesamiento de altas prestaciones como las interfaces analógicas.El proyecto persigue como objetivo general estudiar la susceptibilidad de sistemas informáticos a ASETs en sus secciones analógicas, proponiendo estrategias para la mitigación de los errores.Como objetivos específicos se pretende: -Proponer nuevos modelos de ASETs basados en simulaciones en el nivel dispositivo y resueltas por el método de elementos finitos.-Utilizar los modelos para identificar las secciones más propensas a producir errores y consecuentemente para ser candidatos a la aplicación de técnicas de endurecimiento a radiaciones.-Utilizar estos modelos para estudiar la naturaleza de los errores producidos en sistemas de procesamiento de datos.-Proponer soluciones novedosas para la mitigación de estos efectos en los mismos circuitos analógicos evitando su propagación a las secciones digitales.-Proponer soluciones para la mitigación de los efectos en el nivel sistema.Para llevar a cabo el proyecto se plantea un procedimiento ascendente para las investigaciones a realizar, comenzando por descripciones en el nivel físico para posteriormente aumentar el nivel de abstracción en el que se encuentra modelado el circuito. Se propone el modelado físico de los dispositivos MOS y su resolución mediante el Método de Elementos Finitos. La inyección de cargas en las zonas sensibles de los modelos permitirá determinar los perfiles de los pulsos de corriente que deben inyectarse en el nivel circuito para emular estos efectos. Estos procedimientos se realizarán para los distintos bloques constructivos de las interfaces analógicas, proponiendo estrategias de mitigación de errores en diferentes niveles.Los resultados esperados del presente proyecto incluyen hardware para detección de errores y tolerancia a este tipo de eventos que permitan aumentar la confiabilidad de sistemas de tratamiento de la información, así como también nuevos datos referentes a efectos de la radiación en semiconductores, nuevos modelos de fallas transitorias que permitan una simulación de estos eventos en el nivel circuito y la determinación de zonas sensibles de interfaces analógicas típicas que deben ser endurecidas para radiación.

Minimal-invasive provenance integration into data-intensive systems

Magdeburg, Univ., Fak. für Informatik, Diss., 2014