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Performance Comparison Study of Clusters on Public Clouds / Prestandajämförelse av cluster på offentliga molnleverantörerWahlberg, Martin January 2019 (has links)
As cloud computing has become the more popular choice to host clusters in recent times there are multiple providers that offer their services to the public such as Amazon web services, Google cloud platform and Microsoft Azure. The decision of cluster provider is not only a decision of provider, it is also an indirect decision of cluster infrastructure. The indirect choice of infrastructure makes it important to consider any potential differences in cluster performance caused by the infrastructure in combination with the workload type, but also the cost of the infrastructure on the available public cloud providers. To evaluate whether or not there are any significant differences in either cluster cost or performance between the available public cloud providers, a performance comparison study was conducted. The study consisted of multiple clusters hosted on Amazon Web Services and the Google Cloud Platform. The clusters had access to five different instance types that each correspond to a specific number of available cores, amount of memory and storage. All clusters executed a CPU intensive, I/O intensive, and MapReduce workload while simultaneously having its performance monitored with regard to CPU, memory, and disk usage. The performance comparison study revealed that there are significant performance differences between clusters hosted on Amazon web services and Google cloud platform for the chosen workload types. Since there are significant differences it can be concluded that the choice of provider is crucial as it impacts the cluster performance. Comparing the selected instance types against each other with regard to performance and cost, reveals that a subset of them have better performance as well as lower cost. The instance types that is not a part of this subset, have either better performance or lower cost than its counterpart on the other provider.
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Performance Comparison of Multi Agent Platforms in Wireless Sensor Networks.Bösch, Bernhard Bösch January 2012 (has links)
The technology for the realization of wireless sensors has been available for a long time, but due to progress and development in electrical engineering such sensors can be manufactured cost effectively and in large numbers nowadays. This availability and the possibility of creating cooperating wireless networks which consist of such sensors nodes, has led to a rapidly growing popularity of a technology named Wireless Sensor Networks (WSN). Its disadvantage is a high complexity in the task of programming applications based on WSN, which is a result of its distributed and embedded characteristic. To overcome this shortcoming, software agents have been identified as a suitable programming paradigm. The agent based approach commonly uses a middleware for the execution of the software agent. This thesis is meant to compare such agent middleware in their performance in the WSN domain. Therefore two prototypes of applications based on different agent models are implemented for a given set of middleware. After the implementation measurements are extracted in various experiments, which give information about the runtime performance of every middleware in the test set. In the following analysis it is examined whether each middleware under test is suited for the implemented applications in WSN. Thereupon, the results are discussed and compared with the author’s expectations. Finally a short outlook of further possible development and improvements is presented.
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A MapReduce Performance Study of XML ShreddingLam, Wilma Samhita Samuel 20 October 2016 (has links)
No description available.
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Software Agents for Dlnet Content Review: Study and ExperimentationMitra, Seema 06 April 2007 (has links)
This research is an effort to test our hypothesis that a software agent based architecture will provide a better response time and will be more maintainable and reusable than the present J2EE based architecture of DLNET (Digital Library Network for Engineering and Technology). We have taken a portion of the complete DLNET application for our study, namely the Content Review Process, as our test bed. In this work, we have explored the use of software agents in the current setup of DLNET for the first time, specifically for the Content Review part of the application and tried to evaluate the performance of the resulting application. Our work is a novel approach of doing content review using software agent architecture. The proposed system is an automated process that will asynchronously look for suitable reviewers based on content (the input) and create logs for the administrator to view and analyze. In the first part of the thesis we develop a new system that is parallel to the existing DLNET Content Review Process. In the second part, we compare the newly developed Content Review Process with the baseline (old Content review Process) by designing comparison tests and measuring instruments. This part of the thesis includes the selection of dependent variables, design of various measurement instruments, execution of the quasi-experiments and analysis of the empirical results of comparisons tests. The quasi-experiments are done to measure the response time, maintainability, scalability, correctness, reliability and reusability of the two systems. The results show that the proposed software agent based system gives better response time (an improvement ranging from 57% to 82%) and is more maintainable (an improvement ranging from 16% to 67%) and more reusable (an improvement ranging from 1% to 26%). The improvement in the response time may be attributed to the fact that the agent based systems are inherently multithreaded while the existing content review system is a serial application. Both the systems, however, give comparable results for other dependent variables. / Master of Science
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Comparison of Databases Used in Clearing House SystemsHägglund, Casper January 2024 (has links)
This paper examines what types of databases that could be useful in clearing house systems, focusing on one of Nasdaq's clearing house systems. To determine this, the reports start by looking at what characteristics are important for the database used in a clearing house system. Based on this information, databases that fit these characteristics, like SQLite, MongoDB, Couchbase lite, and Nasdaq's own database, were used in tests to give an overview of their performances related to both latency and throughput. The test results are then analyzed to determine what database has the best performance under different conditions. This paper concluded that Nasdaq's current database is a good fit for this specific system and that the other databases would most likely not result in the same or similar performances. While the other databases, in general, performed worse compared to the current solution, H2 did have better results in some of the tests.
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Uma análise comparativa de ambientes para Big Data: Apche Spark e HPAT / A comparative analysis for Big Data environments: Apache Spark and HPATCarvalho, Rafael Aquino de 16 April 2018 (has links)
Este trabalho compara o desempenho e a estabilidade de dois arcabouços para o processamento de Big Data: Apache Spark e High Performance Analytics Toolkit (HPAT). A comparação foi realizada usando duas aplicações: soma dos elementos de um vetor unidimensional e o algoritmo de clusterização K-means. Os experimentos foram realizados em ambiente distribuído e com memória compartilhada com diferentes quantidades e configurações de máquinas virtuais. Analisando os resultados foi possível concluir que o HPAT tem um melhor desempenho em relação ao Apache Spark nos nossos casos de estudo. Também realizamos uma análise dos dois arcabouços com a presença de falhas. / This work compares the performance and stability of two Big Data processing tools: Apache Spark and High Performance Analytics Toolkit (HPAT). The comparison was performed using two applications: a unidimensional vector sum and the K-means clustering algorithm. The experiments were performed in distributed and shared memory environments with different numbers and configurations of virtual machines. By analyzing the results we are able to conclude that HPAT has performance improvements in relation to Apache Spark in our case studies. We also provide an analysis of both frameworks in the presence of failures.
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LOGGNING AV INTERAKTION MED DATAINSAMLINGSMETODER FÖR WEBBEVENTLOGGNINGSVERKTYG : Experiment om påverkan i svarstider vid loggning av interaktionsdata / LOGING OF INTERACTION WITH DATA COLLECTING METHODS FOR WEB EVENT LOG TOOLS : Experiment about affect in response time when loging interaction dataHenriksson, William January 2018 (has links)
Denna studie undersöker en eventuell påverkan av webbeventloggningsverktyg förautomatiserade användbarhetstestning av användarnas interaktion. I ett experiment mätssvarstider då inspelad interaktion av testpersonerna återuppspelas på den webbapplikationsom testas av webbeventloggningsverktygen med olika datainsamlingsmetoder.Experimentet är uppbyggt av fyra grupper som består av 3 loggningsverktyg somimplementerades utefter de delmålen som sattes upp. Webbeventloggningsverktygensimplementation inspireras av studiens förstudie och i deras numrering loggas allt merinteraktion av användaren som leder till en ökande mängd loggning i bytes. Studiens resultatmötte hypotesen att svarstiden för webbapplikationen när en användare interagerar på sidanökade inte märkbart och det var inte heller en statistiskt signifikant skillnad när loggningenutfördes jämfört mot den nuvarande webbplatsen.
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Tvorba metodiky pro výkonové srovnání databázových systémů datových skladů / Development of methodics for performance comparison of data warehouse systemsRonovský, Jan January 2017 (has links)
This thesis focuses on developing methodics for performance comparison of data warehouse systems. Firstly, the thesis defines data warehouses in various development stages of organization BI and describes knowledge about data warehouses. Methodics developed in the thesis describes architecture of standardized data warehouse, data flow between areas of data warehouse and processes in data warehouse. Understanding of these concepts is crucial for assurance of methodics applicability. Methodics offer logical progression of steps, which start and include testing of data warehouse systems. The contribution of the thesis is in having guide, what needs to be done when organization must do while testing various systems for data warehouses. Also it describes how this testing should be done on middle level detail, which is the absolute minimum level of abstraction that can be done due to wide applicability of methodics. Methodics offers solution to the problem of performance comparison when organization need to answer question - Which data warehouse system should we use in our organization? However, methodics expects already some knowledge about data warehouse content.
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Možnosti porovnávání výkonnosti databázového systému Oracle / The ways of comparing performance of Oracle databasesMareček, Aleš January 2012 (has links)
This thesis examines ways of comparing performance of Oracle databases. The need to compare performance is given by making changes in database systems, for example changes in databases structures or database management systems. One of the goals of this thesis includes a description of options and ways of comparing performance of Oracle databases which does not involve any additional licensing costs. Because there is a need to evaluate obtained performance indicators, part of this thesis deals with the design and implementation tool, which allows analysis of data and their evaluation through defined reports. Functionality of the tool is verified and demonstrated on data obtained from real databases. The main contribution of this thesis is the implementation of the tool, which significantly facilitate evaluating performance impact of changes which should be made in the production database.
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Uma análise comparativa de ambientes para Big Data: Apche Spark e HPAT / A comparative analysis for Big Data environments: Apache Spark and HPATRafael Aquino de Carvalho 16 April 2018 (has links)
Este trabalho compara o desempenho e a estabilidade de dois arcabouços para o processamento de Big Data: Apache Spark e High Performance Analytics Toolkit (HPAT). A comparação foi realizada usando duas aplicações: soma dos elementos de um vetor unidimensional e o algoritmo de clusterização K-means. Os experimentos foram realizados em ambiente distribuído e com memória compartilhada com diferentes quantidades e configurações de máquinas virtuais. Analisando os resultados foi possível concluir que o HPAT tem um melhor desempenho em relação ao Apache Spark nos nossos casos de estudo. Também realizamos uma análise dos dois arcabouços com a presença de falhas. / This work compares the performance and stability of two Big Data processing tools: Apache Spark and High Performance Analytics Toolkit (HPAT). The comparison was performed using two applications: a unidimensional vector sum and the K-means clustering algorithm. The experiments were performed in distributed and shared memory environments with different numbers and configurations of virtual machines. By analyzing the results we are able to conclude that HPAT has performance improvements in relation to Apache Spark in our case studies. We also provide an analysis of both frameworks in the presence of failures.
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