DocumentCode :
3378829
Title :
Queue Length Distribution and Loss probability of Generalized Processor Sharing Systems under Multi-Class Self-Similar Traffic
Author :
Jin, Xiaolong ; Min, Geyong
Author_Institution :
Dept. of Comput., Univ. of Bradford, Bradford
fYear :
2007
fDate :
24-26 Oct. 2007
Firstpage :
179
Lastpage :
185
Abstract :
Performance modelling of generalized processor sharing (GPS) systems in the presence of self-similar traffic has attracted significant research efforts. To simplify the interdependent relationships between traffic flows in GPS systems, most existing studies have been confined to the unrealistic scenarios where only two traffic flows are taken into account. This paper develops an analytical model for investigating both queue length distributions and loss probabilities of GPS systems subject to multi-class self-similar traffic. To this end, we present an efficient approach to decompose the complicated system based on the notion of feasible ordering of GPS systems and the empty buffer approximation. Through extensive comparisons between analytical and simulation results, we investigate the correctness of the decomposition approach and validate the accuracy of the analytical performance results.
Keywords :
probability; queueing theory; telecommunication traffic; GPS system; empty buffer approximation; generalized processor sharing system; loss probability; multiclass self-similar traffic; queue length distribution; Analytical models; Distributed computing; Global Positioning System; Informatics; Performance analysis; Performance loss; Processor scheduling; Queueing analysis; Telecommunication traffic; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, 2007. MASCOTS '07. 15th International Symposium on
Conference_Location :
Istanbul
ISSN :
1526-7539
Print_ISBN :
978-1-4244-1853-4
Electronic_ISBN :
1526-7539
Type :
conf
DOI :
10.1109/MASCOTS.2007.55
Filename :
4674414
Link To Document :
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