Title :
WMCD: A Situation Aware Multicast Congestion Detection Scheme Using Support Vector Machines in MANETs
Author :
Xiaoming Liu ; Nyongesa, Henry ; Connan, James
Author_Institution :
Dept. of Comput. Sci., Univ. of the Western Cape, Bellville, South Africa
Abstract :
Congestion is one of the most important issues impeding the development and deployment of IP multicast and multicast application in Mobile ad-hoc network (MANETs). In this paper, we propose a situation aware multicast congestion detection scheme with support vector machines in MANETs. We focus on using support vector machines to detect incipient multicast congestion by using structural situation information. In this way, by using a situation aware learning system, we can detect incipient congestion in advance instead of waiting packet loss. The rate adaptation algorithm can reduce the transmission rate only if the loss is classified as a congestion loss. Simulation results show that a support vector machine is an appropriate mechanism for decision making in proactive multicast congestion detection.
Keywords :
mobile ad hoc networks; multicast communication; support vector machines; IP multicast application; MANET; WMCD; decision making; mobile ad hoc network; proactive multicast congestion detection; rate adaptation algorithm; situation aware learning system; situation aware multicast congestion detection scheme; structural situation information; support vector machines; transmission rate; Ad hoc networks; Mobile computing; Packet loss; Receivers; Support vector machines; Training; MANET; multicast congestion detection; situation-awareness; support vector machines;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
DOI :
10.1109/ICMLA.2013.45