Sökning: "Google Cloud"

Visar resultat 1 - 5 av 125 uppsatser innehållade orden Google Cloud.

  1. 1. Comparing Model- and Delay-based Congestion Controls in a Kubernetes Cluster

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

    Författare :Robin Allansson; Vittcki Yang; [2024]
    Nyckelord :;

    Sammanfattning : Today's society is heavily influenced by the use of cloud-based services and the internet as a whole. This is causing higher demand for stable networks and maximized efficiency inside the cloud industry. The direction the cloud-based industry went was to maximize their hardware using virtualization. LÄS MER

  3. 2. Defining an Evaluation Model for Container Orchestration Operator Frameworks

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

    Författare :André Arnesson; Samuel Alberius; [2023]
    Nyckelord :container orchestration; cloud native application; operator; software framework; evaluation model; Technology and Engineering;

    Sammanfattning : The growing complexity of cloud native applications has necessitated the intro- duction of operators to the container orchestration tools’ suite of components. Operators affords developers the ability to encode domain knowledge and make fine-grained controllers for their Kubernetes clusters, radically extending the range of feasible applications to host. LÄS MER

  4. 3. Low-No code Platforms for Predictive Analytics

    Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Soma Karmakar; [2023]
    Nyckelord :Low code; no code; Predictive analytics; databricks; azure; AWS; Google cloud;

    Sammanfattning : In the data-driven landscape of modern business, predictive analytics plays a pivotal role inanticipating and mitigating customer churn—a critical challenge for organizations. However, thetraditional complexities of machine learning hinder accessibility for decision-makers. LÄS MER

  5. 4. Federated Machine Learning for Resource Allocation in Multi-domain Fog Ecosystems

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Weilin Zhang; [2023]
    Nyckelord :Workload Allocation; Federated Learning; Deep Q-network; Fog networks; Federated Average Aggregation;

    Sammanfattning : The proliferation of the Internet of Things (IoT) has increasingly demanded intimacy between cloud services and end-users. This has incentivised extending cloud resources to the edge in what is deemed fog computing. The latter is manifesting as an ecosystem of connected clouds, geo-dispersed and of diverse capacities. LÄS MER

  7. 5. Comparative Analysis of the Performance of ARCore and WebXR APIs for AR Applications

    M1-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Abu Bakr Rahman Shaik; Venkata Sai Yakkshit Reddy Asodi; [2023]
    Nyckelord :ARCore; Augmented Reality; Object Visualisation; WebXR;

    Sammanfattning : Background: Augmented Reality has become a popular technology in recent years. Two of the most prominent AR APIs are ARCore, developed by Google, and We- bXR, an open standard for AR and Virtual Reality (VR) experiences on the web. LÄS MER