Sökning: "Kluster"

Visar resultat 16 - 20 av 491 uppsatser innehållade ordet Kluster.

1. 16. Predicting resource usage on a Kubernetes platform using Machine Learning Methods

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

   Författare :Arvid Gördén; [2023]
   Nyckelord :Master thesis; Kubernetes; scaling; resource management; horizontal pod autoscaler; vertical scaling; machine learning; Masterarbete; Kubernetes; scaling; resurshantering; horisontell pod autoscaler; vertikal scaling; maskininlärning;

   Sammanfattning : Cloud computing and containerization has been on the rise in recent years and have become important areas of research and development in the field of computer science. One of the challenges in distributed and cloud computing is to predict the resource utilization of the nodes that run the applications and services. LÄS MER

3. 17. United through Division: An Innovative Approach to European Monetary Policy : A Study of the Optimal Currency Areas in the European Union through Cluster Analysis Conducted on Samples Between 2007–2019

   Magister-uppsats, Linköpings universitet/Nationalekonomi; Linköpings universitet/Filosofiska fakulteten

   Författare :Marinda Gadén; Alexander Granberg; [2023]
   Nyckelord :European Union; Monetary Union; Cluster Analysis; European Monetary Union; Euro; Europäische Union; Währungsunion; Klusteranalyse; Europäische Wirtschafts-und Währungsunion; Euro; Europeiska unionen; valutaunion; klusteranalys; europeiska monetära unionen; Euro;

   Sammanfattning : The study deals with the theory of optimal currency areas complemented with the EU's Maastricht criteria in order to investigate how today’s Economic and Monetary Union of the European Union can be divided into smaller unions with countries that are more homogeneous based on said criteria compared to the current larger currency union. To investigate this, we use cluster analysis as the method easily enables analysis of similarities and differences between countries. LÄS MER

4. 18. Clustering of Unevenly Spaced Mixed Data Time Series

   Master-uppsats, KTH/Matematisk statistik

   Författare :Pierre Sinander; Asik Ahmed; [2023]
   Nyckelord :mixed data time series; unevenly spaced time series; clustering; dynamic time warping; Gower dissimilarity; time warping regularisation; numeriska och kategoriska tidsserier; ojämnt fördelade tidsserier; kluster analys; dynamic time warping; Gower dissimilaritet; regularisering av tidsförvränging;

   Sammanfattning : This thesis explores the feasibility of clustering mixed data and unevenly spaced time series for customer segmentation. The proposed method implements the Gower dissimilarity as the local distance function in dynamic time warping to calculate dissimilarities between mixed data time series. LÄS MER

5. 19. Comparing Sustainability Assessment Software for Packaging: A Conceptual Framework : A Multiple Case Study

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Fridrik Arni Halldorsson; Stanislav Demyanenko; [2023]
   Nyckelord :Sustainability; Packaging; Life-Cycle Assessment; LCA; Assessment Software.; Hållbarhet; Förpackning; Livscykelanalys; LCA; Bedömningsprogramvara;

   Sammanfattning : As sustainability becomes an increasingly critical consideration for businesses, the need for effective sustainability assessment tools and software has grown substantially. This master thesis aims to address this problem by exploring various available tools on the market which are used to measure the sustainability impact of packaging solutions and materials used in their production. LÄS MER

7. 20. Intelligent autoscaling in Kubernetes : the impact of container performance indicators in model-free DRL methods

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

   Författare :Tommaso Praturlon; [2023]
   Nyckelord :Cloud computing; container autoscaling; resource optimisation; Deep Reinforcement Learning; Actor-Critic; Kubernetes; service mesh; Cloud computing; container autoscaling; Optimering av resurser; Deep Reinforcement Learning; Actor-Critic; Kubernetes; service mesh;

   Sammanfattning : A key challenge in the field of cloud computing is to automatically scale software containers in a way that accurately matches the demand for the services they run. To manage such components, container orchestrator tools such as Kubernetes are employed, and in the past few years, researchers have attempted to optimise its autoscaling mechanism with different approaches. LÄS MER