A comparative study of the performance of concurrency control algorithms in a centralised database

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Proceedings of the 3rd Open Source Geospatial Research & Education Symposium OGRS 2014

The third Open Source Geospatial Research & Education Symposium (OGRS) was held in Helsinki, Finland, on 10 to 13 June 2014. The symposium was hosted and organized by the Department of Civil and Environmental Engineering, Aalto University School of Engineering, in partnership with the OGRS Community, on the Espoo campus of Aalto University. These proceedings contain the 20 papers presented at the symposium. OGRS is a meeting dedicated to exchanging ideas in and results from the development and use of open source geospatial software in both research and education.  The symposium offers several opportunities for discussing, learning, and presenting results, principles, methods and practices while supporting a primary theme: how to carry out research and educate academic students using, contributing to, and launching open source geospatial initiatives. Participating in open source initiatives can potentially boost innovation as a value creating process requiring joint collaborations between academia, foundations, associations, developer communities and industry. Additionally, open source software can improve the efficiency and impact of university education by introducing open and freely usable tools and research results to students, and encouraging them to get involved in projects. This may eventually lead to new community projects and businesses. The symposium contributes to the validation of the open source model in research and education in geoinformatics

Design of a performance evaluation tool for multimedia databases with special reference to Oracle

Increased production and use of multimedia data has led to the development of a more advanced Database Management System (DBMS), like an Object Relational Database Management System (ORDBMS). These advanced databases are necessitated by the complexity in structure and the functionality required by multimedia data. Unfortunately, no suitable benchmarks exist with which to test the performance of databases when handling multimedia data. This thesis describes the design of a benchmark to measure the performance of basic functionality found in multimedia databases. The benchmark, called MORD (Multimedia Object Relational Databases), targets Oracle, a well known commercial Object Relational Database Management System (ORDBMS) that can handle multimedia data. Although MORD targets Oracle, it can easily be applied to other Multimedia Database Management System (MMDBMS) as a result of a design that stressed its portability, and simplicity. MORD consists of a database schema, test data, and code to simulate representative queries on multimedia databases. A number of experiments are described that validate MORD and ensure its correct design and that its objectives are met. A by-product of these experiments is an initial understanding of the performance of multimedia databases. The experiments show that with multimedia data the buffer cache should be at least large enough to hold the largest dataset, a bigger block size improves the performance, and turning off logging and caching for bulk loading improves the performance. MORD can be used to compare different ORDBMS or to assist in the configuration of a specific database

Mapeamento de qualidade de experiência (QOE) através de qualidade de serviço (QOS) focado em bases de dados distribuídas

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2017.A falta de conceitualização congruente sobre qualidade de serviço (QoS) para bases de dados (BDs) foi o fator que impulsionou o estudo resultante nesta tese. A definição de QoS como uma simples verificação de se um nó corre risco de falha devido ao número de acessos, como faziam, na época do levantamento bibliométrico desta tese, alguns sistemas comerciais, era uma simplificação exagerada para englobar um conceito tão complexo. Outros trabalhos que dizem lidar com estes conceitos também não são exatos, em termos matemáticos, e não possuem definições concretas ou com qualidade passível de utilização ou replicação, o que torna inviável sua aplicação ou mesmo verificação. O foco deste estudo é direcionado à bases de dados distribuídas (BDDs), de maneira que a conceitualização aqui desenvolvida é também compatível, ao menos parcialmente, com modelos não distribuídos de BDs. As novas definições de QoS desenvolvidas são utilizadas para se lidar com o conceito correlacionado de qualidade de experiência (QoE), em uma abordagem em nível de sistema focada em completude de QoS. Mesmo sendo QoE um conceito multidimensional, difícil de ser mensurado, o foco é mantido em uma abordagem passível de mensuramento, de maneira a permitir que sistemas de BDDs possam lidar com autoavaliação. A proposta de autoavaliação surge da necessidade de identificação de problemas passíveis de autocorreção. Tendo-se QoS bem definida, de maneira estatística, pode-se fazer análise de comportamento e tendência comportamental de maneira a se inferir previsão de estados futuros, o que permite o início de processo de correção antes que se alcance estados inesperados, por predição estatística. Sendo o objetivo geral desta tese a definição de métricas de QoS e QoE, com foco em BDDs, lidando com a hipótese de que é possível se definir QoE estatisticamente com base em QoS, para propósitos de nível de sistema. Ambos os conceitos sendo novos para BDDs quando lidando com métricas mensuráveis exatas. E com estes conceitos então definidos, um modelo de recuperação arquitetural é apresentado e testado para demonstração de resultados quando da utilização das métricas definidas para predição comportamental.Abstract : The hitherto lack of quality of service (QoS) congruent conceptualization to databases (DBs) was the factor that drove the initial development of this thesis. To define QoS as a simple verification that if a node is at risk of failure due to memory over-commitment, as did some commercial systems at the time that was made the bibliometric survey of this thesis, it is an oversimplification to encompass such a complex concept. Other studies that quote to deal with this concept are not accurate and lack concrete definitions or quality allowing its use, making infeasible its application or even verification. Being the focus targeted to distributed databases (DDBs), the developed conceptualization is also compatible, at least partially, with models of non-distributed DBs. These newfound QoS settings are then used to handle the correlated concept of quality of experience (QoE) in a system-level approach, focused on QoS completeness. Being QoE a multidimensional concept, hard to be measured, the focus is kept in an approach liable of measurement, in a way to allow DDBs systems to deal with self-evaluation. The idea of self-evaluation arises from the need of identifying problems subject to self-correction. With QoS statistically well-defined, it is possible to analyse behavior and to indetify tendencies in order to predict future states, allowing early correction before the system reaches unexpected states. Being the general objective of this thesis the definition of metrics of QoS and QoE, focused on DDBs, dealing with the hypothesis that it is possible to define QoE statistically based on QoS, for system level purposes. Both these concepts being new to DDBs when dealing with exact measurable metrics. Once defined these concepts, an architectural recovering model is presented and tested to demonstrate the results when using the metrics defined for behavioral prediction

The 1991/92 graduate student researchers program, including the underrepresented minority focus component

The Graduate Student Research Program (GSRP) was expanded in 1987 to include the Underrepresented Minority Focus Component (UMFC). This program was designed to increase minority participation in graduate study and research, and ultimately, in space science and aerospace technology careers. This booklet presents the areas of research activities at NASA facilities for the GSRP and summarizes and presents the objectives of the UMFC

Fifth Conference on Artificial Intelligence for Space Applications

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration