Sökning: "Distributed File Storage"

Visar resultat 1 - 5 av 34 uppsatser innehållade orden Distributed File Storage.

1. 1. 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

3. 2. Content Based Video Encoding Based on Spatial and TemporalInformation

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Theofanis Papakonstantinou; [2023]
   Nyckelord :;

   Sammanfattning : A significant amount of video content is produced today that needs to be stored, distributed, andstreamed globally in a cost-effective way. This relies on video compression, a process performedby encoding software that remove spatial redundancy, the similarities within a frame, andtemporal redundancy, the similarities between temporarily adjacent frames. LÄS MER

4. 3. 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

5. 4. Hardened Model Aggregation for Federated Learning backed by Distributed Trust Towards decentralizing Federated Learning using a Blockchain

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Morsbach Felix Johannes; [2020]
   Nyckelord :;

   Sammanfattning : Federated learning enables the training of machine learning models on isolated data islands but also introduces new security challenges. Besides training-data-poisoning and model-update-poisoning, centralized federated learning systems are subject to a third type of poisoning attack: model-aggregation-poisoning. LÄS MER

7. 5. Implementation and Evaluation of a DataPipeline for Industrial IoT Using ApacheNiFi

   Kandidat-uppsats, Karlstads universitet

   Författare :Lina Vilhelmsson; Pontus Sjöberg; [2020]
   Nyckelord :Data pipelining; Apache NiFi; IIoT; Industrial IoT;

   Sammanfattning : In the last few years, the popularity of Industrial IoT has grown a lot, and it is expected to have an impact of over 14 trillion USD on the global economy by 2030. One application of Industrial IoT is using data pipelining tools to move raw data from industry machines to data storage, where the data can be processed by analytical instruments to help optimize the industrial operations. LÄS MER