Search for dissertations about: "stream data"

Showing result 1 - 5 of 262 swedish dissertations containing the words stream data.

  1. 1. Scalable and Reliable Data Stream Processing

    University dissertation from KTH Royal Institute of Technology

    Author : Paris Carbone; KTH.; [2018]
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; distributed systems; stream processing; data management; databases; distributed computing; data processing; fault tolerance; database optimisation; programming systems; data science; data analytics; computer science; Informations- och kommunikationsteknik; Information and Communication Technology;

    Abstract : Data-stream management systems have for long been considered as a promising architecture for fast data management. The stream processing paradigm poses an attractive means of declaring persistent application logic coupled with state over evolving data. READ MORE

  2. 2. Scalable Validation of Data Streams

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Cheng Xu; Uppsala universitet.; Uppsala universitet.; [2016]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Data Stream Management; Distributed Data Stream Processing; Data Stream Validation; Anomaly Detection; Datavetenskap med inriktning mot databasteknik; Computer Science with specialization in Database Technology;

    Abstract : In manufacturing industries, sensors are often installed on industrial equipment generating high volumes of data in real-time. For shortening the machine downtime and reducing maintenance costs, it is critical to analyze efficiently this kind of streams in order to detect abnormal behavior of equipment. READ MORE

  3. 3. Scalable Scientific Stream Query Processing

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Milena Ivanova; Uppsala universitet.; Uppsala universitet.; [2005]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; data stream management systems; parallel stream processing; scientific stream query processing; user-defined stream partitioning; TECHNOLOGY Information technology Computer science Computer science; TEKNIKVETENSKAP Informationsteknik Datavetenskap Datalogi; Data- och systemvetenskap; Computer Systems Sciences;

    Abstract : Scientific applications require processing of high-volume on-line streams of numerical data from instruments and simulations. In order to extract information and detect interesting patterns in these streams scientists need to perform on-line analyses including advanced and often expensive numerical computations. READ MORE

  4. 4. Data Modeling for Outlier Detection

    University dissertation from Karlskrona : Blekinge Tekniska Högskola

    Author : Shahrooz Abghari; Blekinge Tekniska Högskola.; [2018]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; data modeling; cluster analysis; stream data; outlier detection;

    Abstract : This thesis explores the data modeling for outlier detection techniques in three different application domains: maritime surveillance, district heating, and online media and sequence datasets. The proposed models are evaluated and validated under different experimental scenarios, taking into account specific characteristics and setups of the different domains. READ MORE

  5. 5. Parallel Data Streaming Analytics in the Context of Internet of Things

    University dissertation from Karlskrona : Blekinge Tekniska Högskola

    Author : Hannaneh Najdataei; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; clustering; stream continuous data processing; edge computing; Internet of Things; parallelism; elasticity; data analysis; fog computing; scalability;

    Abstract : We are living in an increasingly connected world, where the ubiquitously sensing technologies enable inter-connection of physical objects, as part of Internet of Things (IoT), and provide continuous massive amount of data. As this growth soars, benefits and challenges come together, which requires development of right tools in order to extract valuable information from data. READ MORE