Essays about: "Distribuerad Databehandling"

Showing result 1 - 5 of 9 essays containing the words Distribuerad Databehandling.

  1. 1. Auto-Tuning Apache Spark Parameters for Processing Large Datasets

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Shidi Zhou; [2023]
    Keywords : Apache Spark; Cloud Environment; Spark Configuration Parameter; Resource Utilization; Ridge Regression; Elastic Net; Random Forest; Deep Neural Network; Bayesian Optimization; Particle Swarm Optimization.; Apache Spark; Molnmiljö; Apache Spark konfigurationsparameter; Resursutnyttjande; Ridge-regression; Elastisk nät; Slumpskog; Djupt neuralt nätverk; Bayesiansk optimering; Partikelsvärmsoptimering.;

    Abstract : Apache Spark is a popular open-source distributed processing framework that enables efficient processing of large amounts of data. Apache Spark has a large number of configuration parameters that are strongly related to performance. Selecting an optimal configuration for Apache Spark application deployed in a cloud environment is a complex task. READ MORE

  3. 2. The state of WebAssembly in distributed systems : With a focus on Rust and Arc-Lang

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Theodor-Andrei Moise; [2023]
    Keywords : WebAssembly; Wasmer; Wasm; Rust; Arc-Lang; Distributed Systems; Continuous Deep Analytics; Docker containers; Performance benchmarking; WebAssembly; Wasmer; Wasm; Rust; Arc-Lang; Distributed Systems; Continuous Deep Analytics; Docker containers; Performance benchmarking;

    Abstract : With the current developments in modern web browsers, WebAssembly has been a rising trend over the last four years. Aimed at replacing bits of JavaScript functionality, it attempts to bring extra features to achieve portability and sandboxing through virtualisation. READ MORE

  4. 3. Deep Multiple Description Coding for Semantic Communication : Theory and Practice

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Martin Lindström; [2022]
    Keywords : Deep Learning; Split Computing; Multiple Description Coding; Semantic Communication; Internet of Things; Image Classification; Djupinlärning; distribuerade beräkningar; distribuerad kodning; semantisk kommunikation; sakernas internet; Internet of Things; bildklassificering;

    Abstract : With the era of wirelessly connected Internet of Things (IoT) devices on the horizon, eective data processing algorithms for IoT devices are of increasing importance. IoT devices often have limited power and computational resources, making data processing on the device unfeasible. READ MORE

  5. 4. Machine Learning with Reconfigurable Privacy on Resource-Limited Edge Computing Devices

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Zannatun Nayem Tania; [2021]
    Keywords : Data Privacy; Resource Management; Machine Learning; Fitbit; Internet of Things IoT ; Optimization; Dataintegritet; Resurshantering; Machine Learning; Fitbit; Internet of Things IoT ; Optimering;

    Abstract : Distributed computing allows effective data storage, processing and retrieval but it poses security and privacy issues. Sensors are the cornerstone of the IoT-based pipelines, since they constantly capture data until it can be analyzed at the central cloud resources. However, these sensor nodes are often constrained by limited resources. READ MORE

  6. 5. Performance Analysis of Distributed Spatial Interpolation for Air Quality Data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Albert Asratyan; [2021]
    Keywords : Distributed Computing; Parallel Execution; Data Interpolation; Kriging; Apache Ray; Geostatistics; Python; Cloud Services; AWS; Air Quality; Distribuerad Databehandling; Parallell Körning; Datainterpolation; Kriging; Apache Ray; Geostatistik; Python; Molntjänster; AWS; Luftkvalitet;

    Abstract : Deteriorating air quality is a growing concern that has been linked to many health- related issues. Its monitoring is a good first step to understanding the problem. However, it is not always possible to collect air quality data from every location. READ MORE