• español
    • English
  • Login
  • English 
    • español
    • English
  • Publication Types
    • bookbook partconference objectdoctoral thesisjournal articlemagazinemaster thesispatenttechnical documentationtechnical report
View Item 
  •   IMDEA Networks Home
  • View Item
  •   IMDEA Networks Home
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Prediction-based Techniques for the Optimization of Mobile Networks

Share
Files
N.Bui-PhD Thesis-May 2017.pdf (14.65Mb)
Identifiers
URI: http://hdl.handle.net/20.500.12761/373
Metadata
Show full item record
Author(s)
Bui, Nicola
Supervisor(s)/Director(s)
Widmer, Joerg
Date
2017-05-12
Abstract
Mobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable. In this thesis we analyze a recent branch of network optimization that is commonly referred to as anticipatory networking and that entails the combination of prediction solutions and network optimization schemes. The main intuition behind anticipatory networking is that knowing in advance what is going on in the network can help understanding potentially severe problems and mitigate their impact by applying solution when they are still in their initial states. Conversely, network forecast might also indicate a future improvement in the overall network condition (i.e. load reduction or better signal quality reported from users). In such a case, resources can be assigned more sparingly requiring users to rely on buffered information while waiting for the better condition when it will be more convenient to grant more resources. In the beginning of this thesis we will survey the current anticipatory networking panorama and the many prediction and optimization solutions proposed so far. In the main body of the work, we will propose our novel solutions to the problem, the tools and methodologies we designed to evaluate them and to perform a real world evaluation of our schemes. By the end of this work it will be clear that not only is anticipatory networking a very promising theoretical framework, but also that it is feasible and it can deliver substantial benefit to current and next generation mobile networks. In fact, with both our theoretical and practical results we show evidences that more than one third of the resources can be saved and even larger gain can be achieved for data rate enhancements.
Share
Files
N.Bui-PhD Thesis-May 2017.pdf (14.65Mb)
Identifiers
URI: http://hdl.handle.net/20.500.12761/373
Metadata
Show full item record

Browse

All of IMDEA NetworksBy Issue DateAuthorsTitlesKeywordsTypes of content

My Account

Login

Statistics

View Usage Statistics

Dissemination

emailContact person Directory wifi Eduroam rss_feed News
IMDEA initiative About IMDEA Networks Organizational structure Annual reports Transparency
Follow us in:
Community of Madrid

EUROPEAN UNION

European Social Fund

EUROPEAN UNION

European Regional Development Fund

EUROPEAN UNION

European Structural and Investment Fund

© 2021 IMDEA Networks. | Accesibility declaration | Privacy Policy | Disclaimer | Cookie policy - We value your privacy: this site uses no cookies!