The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Opportunistic Neighbour Prediction Using an Artificial Neural Network
|
|
Author(s): Fraser Cadger (Intelligent Systems Research Centre, University of Ulster, UK), Kevin Curran (Intelligent Systems Research Centre, University of Ulster, UK), Jose Santos (Intelligent Systems Research Centre, University of Ulster, , UK)and Sandra Moffet (Intelligent Systems Research Centre, University of Ulster, UK)
Copyright: 2017
Pages: 13
Source title:
Artificial Intelligence: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1759-7.ch067
Purchase
|
Abstract
Device mobility is an issue that affects both MANETs and opportunistic networks. While the former employs conventional routing techniques with some element of mobility management, opportunistic networking protocols often use mobility as a means of delivering messages in intermittently connected networks. If nodes are able to determine the future locations of other nodes with reasonable accuracy then they could plan ahead and take into account and even benefit from such mobility. Location prediction in combination with geographic routing has been explored in previous literature. Most of these location prediction schemes have made simplistic assumptions about mobility. However more advanced location prediction schemes using machine learning techniques have been used for wireless infrastructure networks. These approaches rely on the use of infrastructure and are therefore unsuitable for use in opportunistic networks or MANETs. To solve the problem of accurately predicting future location in non-infrastructure networks, the authors have investigated the prediction of continuous numerical coordinates using artificial neural networks. Simulation using three different mobility models representing human mobility has shown an average prediction error of less than 1m in normal circumstances.
Related Content
|
Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava.
© 2024.
20 pages.
|
|
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima.
© 2024.
52 pages.
|
|
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira.
© 2024.
24 pages.
|
|
Fatih Pinarbasi.
© 2024.
20 pages.
|
|
Stavros Kaperonis.
© 2024.
25 pages.
|
|
Thomas Rui Mendes, Ana Cristina Antunes.
© 2024.
24 pages.
|
|
Nuno Geada.
© 2024.
12 pages.
|
|
|