English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The explosive growth of Internet leads to increased diversity of applications. Multimedia applications, which are delay sensitive and include telephony, videoconferencing etc. can benefit from this approach to satisfy their QoS routing requirement. Existing route discovery involves estimation of delay at every mobile node which involves calculation of queueing delay as well as contention delay. However, it is a complex procedure but it is required in fulfilling QoS routing requirements in MANET. Artificial neural networks are emerging as a promising technology which can be applied in networking field, simulating human mind in learning from experiences.We have utilized the capability of artificial neural networks (ANN) for accurate prediction of end-to-end packet delay in MANET. Existing link failure strategy involves frequent route discoveries which incur high routing overhead and increased end-to-end delay. In this paper, efficient link failure recovery is also incorporated by utilizing multiple alternate paths in case of link failure, which is determined through signal intensity level and link expiration metric to provide link failure prediction before it breaks up.The proposed methodology has been implemented in a computer simulation. Results show that our approach has been found outperforming to existing approaches and has the potential to be applied in real world scenarios.

A New QoS-Aware Routing Protocol for MANET Using Artificial Neural Network