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10th IEEE Symposium on Computers and Communications (ISCC'05)
Estimation of the Probability of Congestion Using Monte Carlo Method in OPS Networks
Cartagena, Murcia, Spain
June 27-June 30
ISBN: 0-7695-2373-0
Anna Urra, University of Girona
Jose L. Marzo, University of Girona
Mateu Sbert, University of Girona
Eusebi Calle, University of Girona
In networks with small buffers, such as Optical Packet Switching based networks, the Covolution Approach is presented as one of the most accurate method used for the Connection Admission Control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the Enhanced Convolution Approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to Enhanced Convolution Approach with an small stochastic error in the probability estimation.
Citation:
Anna Urra, Jose L. Marzo, Mateu Sbert, Eusebi Calle, "Estimation of the Probability of Congestion Using Monte Carlo Method in OPS Networks," iscc, pp.561-566, 10th IEEE Symposium on Computers and Communications (ISCC'05), 2005
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