Title
Analytical Models Based Discrete-Time Queueing For The Congested Network
Abstract
Congestion is one of the well-studied problems in computer networks, which occurs when the request for network resources exceeds the buffer capacity. Many active queue management techniques such as BLUE and RED have been proposed in the literature to control congestions in early stages. In this paper, we propose two discrete-time queueing network analytical models to drop the arrival packets in preliminary stages when the network becomes congested. The first model is based on Lambda Decreasing and it drops packets from a probability value to another higher value according to the buffer length. Whereas the second proposed model drops packets linearly based on the current queue length. We compare the performance of both our models with the original BLUE in order to decide which of these methods offers better quality of service. The comparison is done in terms of packet dropping probability, average queue length, throughput ratio, average queueing delay, and packet loss rate.
Year
DOI
Venue
2012
10.1142/S1793962311500048
INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING
Keywords
Field
DocType
Analytical models, congestion control, discrete-time queueing, simulation
Mean value analysis,Bulk queue,Computer science,Active queue management,Queue,Computer network,Packet loss,Layered queueing network,Queueing theory,Network congestion
Journal
Volume
Issue
ISSN
3
1
1793-9623
Citations 
PageRank 
References 
1
0.37
13
Authors
5
Name
Order
Citations
PageRank
M. Al-diabat1151.77
Hussein Abdel-Jaber2356.45
Fadi Thabtah3837.86
Osman Abou-Rabia412822.62
mahmoud kishta510.37