Fuzzy logic based ATM policing

Cheung, K.F.; Tsang, D.H.K.; Cheng, Chun-Sheng; Liu, C.W.

doi:10.1109/iccs.1994.474195

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…Chang and Cheng (1994) and Cheung et al (1994)). Thus, in view of the shortcomings encountered in the above mentioned approaches, we propose to use an adaptive fuzzy system to e ciently predict the CLR in large-sized systems based on only a small amount of information from small-sized systems.…”

Section: Estimation Of Loss Proba B I L I T Y W I T H a F Uzzy Logic mentioning

confidence: 99%

Efficient estimation of cell loss probability in atm multiplexers with a fuzzy logic system

1996

Proceedings of the International IFIP-IEEE Conference on Broadband Communications, Global Infrastructure for the Information Ag

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An important parameter in ATM-based network design and management is the cell loss probability i n A TM multiplexers. However, it depends on many unknown and unpredictable tra c parameters such as burst length distribution, mean rate, etc. In this paper, we propose a simple and robust fuzzy-based algorithm to predict the cell loss probability in large-sized systems based only on both a small amount of information from small-sized systems, and the asymptotic behavior for very large systems. Numerical results show that the value predicted by this algorithm is quite accurate. The application of the proposed algorithm to call admission control is also presented.

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Section: Estimation Of Loss Proba B I L I T Y W I T H a F Uzzy Logic mentioning

confidence: 99%

Efficient estimation of cell loss probability in atm multiplexers with a fuzzy logic system

1996

Proceedings of the International IFIP-IEEE Conference on Broadband Communications, Global Infrastructure for the Information Ag

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“…tin the sequel we use the generic term cell loss probability or CLR to designate either the cell loss probability, the overflow probability or the cell loss ratio Fuzzy logic technique has been proposed to efficiently solve several ATM problems (e.g. Chang and Cheng (1994) and Cheung et a!. (1994)).…”

Section: Introductionmentioning

confidence: 99%

Efficient Estimation of Cell Loss Probability in ATM multiplexers with a Fuzzy Logic System

Lam

Bensaou

Tsang

1996

Broadband Communications

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An important parameter in ATM-based network design and management is the cell loss probability in ATM multiplexers. However, it depends on many unknown and unpredictable traffic parameters such as burst length distribution, mean rate, etc. In this paper, we propose a simple and robust fuzzy-based algorithm to predict the cell loss probability in large-sized systems based only on both a small amount of information from small-sized systems, and the asymptotic behavior for very large systems. Numerical results show that the value predicted by this algorithm is quite accurate. The application of the proposed algorithm to call admission control is also presented.

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Neuro-fuzzy control in ATM networks

Douligeris

Develekos

1997

IEEE Commun. Mag.

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Fuzzy logic based ATM policing

Cited by 5 publications

References 7 publications

Efficient estimation of cell loss probability in atm multiplexers with a fuzzy logic system

Efficient estimation of cell loss probability in atm multiplexers with a fuzzy logic system

Efficient Estimation of Cell Loss Probability in ATM multiplexers with a Fuzzy Logic System

Neuro-fuzzy control in ATM networks

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