Bibliographic Details
| Title: |
Simulació i modelat d'entorns cloud per a experimentació amb machine learning |
| Authors: |
Roldán Llinàs, Jordi |
| Contributors: |
Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics, Berral García, Josep Lluís, Gavaldà Mestre, Ricard |
| Publisher Information: |
Universitat Politècnica de Catalunya |
| Publication Year: |
2010 |
| Collection: |
Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
| Subject Terms: |
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Machine learning -- Computer simulation, Cloud Computing, Simulation, Aprenentatge automàtic -- Simulació per ordinador |
| Description: |
Nowadays Cloud computing has emerged as one of the most promising computer paradigms. The idea of selling software as a service has promoted IT enterprises to bet for this new paradigm. Cloud computing aims to power the next generation data centers not only offering software as a service but virtual services like hardware, data storage capacity or application logic. The increasing use of Cloud-based applications will also increase the power dedicated to the data centers that support this Clouds. Research in Cloud computing requires solutions that have to be tested in real environments. It is difficult and expensive to set up suitable test-beds for large scale cluster applications. Simulation can fulfill the needs that we find in Cloud computing experimentation. A large data center simulator can save lots of time and effort in Cloud investigation. This project presents the design and development process of some extensions to an existing virtualized data center simulator for Cloud computing research. It is able to reproduce the behaviour of a real Cloud framework and the information that it offers of the execution makes it suitable for testing and investigation purposes. The final idea of this project was to extend the heterogeneity of the tests that can be run by the simulator to use it as a test-bed for machine learning experimentation. |
| Document Type: |
master thesis |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
https://hdl.handle.net/2099.1/9581; 65753 |
| Availability: |
https://hdl.handle.net/2099.1/9581 |
| Rights: |
Open Access |
| Accession Number: |
edsbas.5854B749 |
| Database: |
BASE |