Sökning: "distributed file system"

Visar resultat 1 - 5 av 64 uppsatser innehållade orden distributed file system.

  1. 1. Profile Based Access Control Model Using JSON Web Tokens

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Mustafa Albayati; Aslan Murjan; [2023]
    Nyckelord :access control; profiles; IoT; device; OpenIDC; Technology and Engineering;

    Sammanfattning : Currently at Axis, a local role-based access control system is used in devices, which forces the user credentials to be directly installed on the individual devices and the limited selection of roles does not allow for fine-grained access rights. This creates an administrative nightmare in a large scale network and leads to elevated privileges. LÄS MER

  3. 2. Low-latency transport protocols inactor systems : Performance evaluation of QUIC in Kompact

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jódís Gunnlaugsdóttir; [2023]
    Nyckelord :Kompact; Component-Actor hybrid framework; Transmission Control Protocol; User Datagram Protocol; Aeron; Quic;

    Sammanfattning : Developers widely use actor frameworks to build highly distributed systems. However, modern actor frameworks are limited in their network implementations, with Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) being the main protocols used for network communication. LÄS MER

  4. 3. Faster Reading with DuckDB and Arrow Flight on Hopsworks : Benchmark and Performance Evaluation of Offline Feature Stores

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Ayushman Khazanchi; [2023]
    Nyckelord :Machine Learning; Feature Store; Distributed Systems; MLOps;

    Sammanfattning : Over the last few years, Machine Learning has become a huge field with “Big Tech” companies sharing their experiences building machine learning infrastructure. Feature Stores, used as centralized data repositories for machine learning features, are seen as a central component to operational and scalable machine learning. LÄS MER

  5. 4. Improvement of the Rucio implementation for the LDCS platform and search for dark data

    Kandidat-uppsats, Lunds universitet/Partikel- och kärnfysik; Lunds universitet/Fysiska institutionen

    Författare :Piotr Yartsev; [2022]
    Nyckelord :Dark matter; rucio; digital infrastructure; Root; LDMX; LDCS; dark data; Python; CERN; particle physics; big data; Geant4; Light Dark Matter eXperiment; Lightweight Distributed Computing System; data storage; Physics and Astronomy;

    Sammanfattning : In this work we aim to implement a software package to detect and categorize dark data, data not accessible or not known by the user, generated in the simulations of the Light Dark Matter eXperiment (LDMX). This will involve studying current existing solutions for such problems, attempting to implement them for the Lightweight Distributed Computing System (LDCS), and developing our own Dark Data Search (DDS) toolkit to perform the detection and categorization of the dark data. LÄS MER

  7. 5. Sequential Anomaly Detection for Log Data Using Deep Learning

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Lina Hammargren; Wei Wu; [2021-06-14]
    Nyckelord :anomaly detection; recurrent neural network; long short-term memory; semi-supervised learning; seq2seq; transformer; unsupervised learning; log analysis;

    Sammanfattning : Abstract Software development with continuous integration changes needs frequent testing for assessment. Analyzing the test output manually is time-consuming and automating this process could be beneficial to an organization. LÄS MER