Intelligent Reasoning Approach for Active Queue Management in Wireless Ad Hoc Networks

Intelligent Reasoning Approach for Active Queue Management in Wireless Ad Hoc Networks

Essam Natsheh, Adznan B. Jantan, Sabira Khatun, Shamala Subramaniam
Copyright: © 2007 |Pages: 20
DOI: 10.4018/jbdcn.2007010102
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Mobile ad hoc network is a network without infrastructure where every node has its own protocols and services for powerful cooperation in the network. Every node also has the ability to handle the congestion in its queues during traffic overflow. Traditionally, this was done through Drop-Tail policy where the node drops the incoming packets to its queues during overflow condition. Many studies showed that early dropping of incoming packet is an effective technique to avoid congestion and to minimize the packet latency. Such approach is known as Active Queue Management (AQM). In this article, an enhanced algorithm called fuzzy-AQM is suggested using a fuzzy logic system to achieve the benefits of AQM. Uncertainty associated with queue congestion estimation and lack of mathematical model for estimating the time to start dropping incoming packets makes the fuzzy-AQM algorithm the best choice. Extensive performance analysis via simulation showed the effectiveness of the proposed method for congestion detection and avoidance improving overall network performance.

Complete Article List

Search this Journal:
Reset
Volume 19: 1 Issue (2023): Forthcoming, Available for Pre-Order
Volume 18: 2 Issues (2022): 1 Released, 1 Forthcoming
Volume 17: 2 Issues (2021)
Volume 16: 2 Issues (2020)
Volume 15: 2 Issues (2019)
Volume 14: 2 Issues (2018)
Volume 13: 2 Issues (2017)
Volume 12: 2 Issues (2016)
Volume 11: 2 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing