Sökning: "examensarbete cloud"

Visar resultat 1 - 5 av 91 uppsatser innehållade orden examensarbete cloud.

  1. 1. Prestandajämförelse mellan krypterade och okrypterade tidsseriedatabaser med IoT-baserad temperatur- och geopositionsdata

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Sinem Uzunel; Joanna Xu; [2024]
    Nyckelord :AWS Timestream; InfluxDB Cloud; Performance Testing; Time Series; Time Series databases; Encryption; Database Query; Internet of Things IoT ; Performance Analysis; AWS Timestream; InfluxDB Cloud; Prestandatest; Tidsserier; Tidsseriedatabas; Kryptering; Databasfråga; Internet of Things IoT ; Prestandaanalys;

    Sammanfattning : Internet of Things (IoT) är en växande teknologi som spelar en allt större roll i samhället. Den innefattar ett nätverk av internetanslutna enheter som samlar in och utbyter data. Samtidigt som IoT växer uppstår utmaningar kring hantering av stora datamängder och säkerhetsaspekter. LÄS MER

  3. 2. Enhancement of a Power Line Information System by Combining BIM and LiDAR Data

    Master-uppsats, KTH/Lantmäteri – fastighetsvetenskap och geodesi

    Författare :Daniel Wollberg; [2024]
    Nyckelord :GIS; BIM; FME; CloudCompare; GIS; BIM; FME; CloudCompare;

    Sammanfattning : With the great ongoing energy transition in Sweden, Svenska Kraftnät (SVK) sees a huge need for investment in the Swedish transmission network and supporting IT- systems.  SVK has a great amount of collected laser data over the electric power transmission network however this data does not contain any semantic attribution that can be analyzed on broader information systems. LÄS MER

  4. 3. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

    Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER

  5. 4. Confidential Federated Learning with Homomorphic Encryption

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

    Författare :Zekun Wang; [2023]
    Nyckelord :Cloud Technology; Confidential Computing; Federated Learning; Homomorphic Encryption; Trusted Execution Environment; Molnteknik; Konfidentiell databehandling; Federerad inlärning; Homomorfisk kryptering; Betrodd körningsmiljö;

    Sammanfattning : Federated Learning (FL), one variant of Machine Learning (ML) technology, has emerged as a prevalent method for multiple parties to collaboratively train ML models in a distributed manner with the help of a central server normally supplied by a Cloud Service Provider (CSP). Nevertheless, many existing vulnerabilities pose a threat to the advantages of FL and cause potential risks to data security and privacy, such as data leakage, misuse of the central server, or the threat of eavesdroppers illicitly seeking sensitive information. LÄS MER

  7. 5. Dimensioning Microservices on Kubernetes Platforms Using Machine Learning Techniques

    Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Adam Rubak; [2023]
    Nyckelord :Kubernetes; dimensioning; scaling; resource management; horizontal pod autoscaler; machine learning; Kubernetes; dimensionering; skalning; resurshantering; horisontell pod autoscaler; maskininlärning;

    Sammanfattning : In recent years, cloud computing and containerization have become increasingly popular for various applications. However, optimizing resource usage and minimizing costs while providing reliable and efficient service to users can be a challenge. One such challenge is scaling containers according to the current system load. LÄS MER