EconPapers    
Economics at your fingertips  
 

Prediction in mobile ad hoc network based on fuzzy time series

Chunyu Yang

International Journal of Networking and Virtual Organisations, 2019, vol. 20, issue 1, 44-52

Abstract: Several parameters like routing protocol, mobility pattern, average speed of mobile nodes, path length from source to destination, previous delay, etc., affect the end-to-end packet delay in mobile ad hoc network. But the nature of relationship between end-to-end delay and those parameters is still unclear. The end-to-end delay can be represented as a fuzzy time series. In this paper, a new method to forecast the end-to-end delay is presented. The method fully capitalises on the two key technologies, automatic clustering and automatically generated weights, to handle the forecasting problems. First, the automatic clustering algorithm is utilised to generate clustering-based intervals. Then, the variation magnitudes of adjacent historical data are used to generate fuzzy variation groups. Third, the final forecasted variation can be obtained by the weights of the fuzzy variation. Finally, the phase of forecasting is performed. Based on performance evaluation criterion, we found that the predicted value of the proposed method gives satisfactory packed delay prediction in ad hoc network.

Keywords: ad hoc network; fuzzy time series; fuzzy forecasting; automatic clustering. (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=96605 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijnvor:v:20:y:2019:i:1:p:44-52

Access Statistics for this article

More articles in International Journal of Networking and Virtual Organisations from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijnvor:v:20:y:2019:i:1:p:44-52