DocumentCode
2662687
Title
A Comparison Study of End-to-End Delay Using Different Active Queue Management Algorithms
Author
Kenchannavar, Harish H. ; Kulkarni, U.P. ; Yardi, A.R.
Author_Institution
Dept. of Comput. Sci. & Eng., VTU, Belgaum, India
fYear
2008
fDate
10-12 Dec. 2008
Firstpage
88
Lastpage
91
Abstract
In high-speed networks supported by TCP/IP, congestion control algorithm plays an important role. Real time streaming media, such as video, audio conversations and movies on line, often are transmitted over the Internet. The dominant paradigm for congestion control in the Internet is based on the TCP friendliness. As the load on the network increases, it is critical to find the point at which congestion occurs. When congestion is about to happen, the network should be capable of reducing the rate at which the hosts send the data before the packets start being discarded. Random early detection (RED) algorithm is one such mechanism used at the router to control congestion in the network. It is programmed to monitor the queue length at the specific router. When it detects that congestion is imminent, it notifies the source to adjust its congestion window. The key principle in RED implementation is that, it notifies the source of congestion occurrence by dropping one of its packets. In this paper, we have illustrated the performance of RED and FIFO in the network in terms of end-to-end delay, which is one of the important parameters in the quality of service (QoS) of the network.
Keywords
Internet; computer network management; delays; media streaming; quality of service; queueing theory; telecommunication congestion control; telecommunication network routing; transport protocols; Internet; TCP/IP; active queue management algorithms; congestion control algorithm; end-to-end delay; high-speed networks; quality of service; random early detection algorithm; real time streaming media; Delay; Active Queue Management; Average end-to-end delay; Delay; FIFO; RED;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Modelling Control & Automation, 2008 International Conference on
Conference_Location
Vienna
Print_ISBN
978-0-7695-3514-2
Type
conf
DOI
10.1109/CIMCA.2008.64
Filename
5172605
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