Coping with broadband traffic uncertainties: statistical uncertainty, fuzziness, neural networks

Broadband networks will carry traffic with highly unpredictable traffic characteristics. Three approaches for dealing with traffic uncertainty are discussed and compared. The first is based on analyzing the effects of statistical uncertainty in traffic characteristics on queuing system performance. The second uses the theory of fuzzy sets in handling an uncertain service time of a queuing system, and in forecasting new services. The last uses a neural net approach to learn about the certain environment.<<ETX>>

[1]  Jack M. Holtzman,et al.  EXTREMALS OF FUNCTIONS OF RANDOM VARIABLES, OPTIMAL CONTROL THEORY, AND TELETRAFFIC THEORY , 1988 .

[2]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[3]  W. Whitt,et al.  The Queueing Network Analyzer , 1983, The Bell System Technical Journal.

[4]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[5]  E. Lee,et al.  Analysis of fuzzy queues , 1989 .

[6]  A. E. Eckberg,et al.  Sharp Bounds on Laplace-Stieltjes Transforms, with Applications to Various Queueing Problems , 1977, Math. Oper. Res..

[7]  A. Hiramatsu.  ATM communications network control by neural network , 1989, International 1989 Joint Conference on Neural Networks.

[8]  Aleksandr Alekseevich Borovkov,et al.  Stochastic processes in queueing theory , 1976 .

[9]  M. Gruszecki,et al.  Some New Concepts in Demand and Traffic Forecasting and Planning of Future Telecommunication Services , 1990, Comput. Networks ISDN Syst..

[10]  Ward Whitt,et al.  Characterizing Superposition Arrival Processes in Packet Multiplexers for Voice and Data , 1986, IEEE J. Sel. Areas Commun..

[11]  Yann LeCun,et al.  Generalization and network design strategies , 1989 .

[12]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[13]  On using perturbation analysis to do sensitivity analysis: derivatives vs. differences , 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

[14]  W. J. Studden,et al.  Tchebycheff Systems: With Applications in Analysis and Statistics. , 1967 .

[15]  Dennis D. Boos,et al.  Using extreme value theory to estimate large percentiles , 1984 .

[16]  W. Whitt,et al.  On approximations for queues, II: Shape constraints , 1984, AT&T Bell Laboratories Technical Journal.