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In this chapter we have shown that a form of predictive congestion control called selective aggressiveness control (SAC) is able to exploit correlation structure present in long-range dependent traf c for performance improvement purposes. We have shown that predictability can be implemented on-line with suf cient accuracy such that when coupled with SAC mechanism, the cost associated with conservative bandwidth consumption during the linear increase phase of a generic linear increase=exponential decrease feedback congestion control algorithm can be offset to bring forth improved throughput. Furthermore, we show that the relative performance gain is higher the more long-range dependent the underlying network traf c. We have also shown that SAC preserves fairness to the degree expected of a feedback congestion control and its ef ciency property is desirable within a range. An important consequence of multiple time scale congestion control is its ability to mitigate the dely-bandwidth product problem of broadband wide area networks by endowing proactivity. We refer the reader to [46, 48] for this result. Current work is directed along four avenues: (1) in devising new mechanisms capable of exploiting predictability at longer time scales, (2) in further optimizing the various components of SAC, (3) in implementing the ideas of SAC in TCP, and (4) adopting the multiple time scale traf c control framework to the QoS-sensitive transport of real-time traf c using packet-level adaptive forward error correction. The TCP results are reported in [48], and the extension to quality of service is performed via multiple time scale redundancy control and described in [47]. REFERENCES



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1. A. Adas and A. Mukherjee. On resource management and QoS guarantees for long range dependent traf c. In Proc. IEEE INFOCOM'95, pp. 779 787, 1995. 2. R. Addie, M. Zukerman, and T. Neame. Fractal traf c: measurements, modelling and performance evaluation. In Proc. IEEE INFOCOM'95, pp. 977 984, 1995. 3. T. Anderson. The Statistical Analysis of Time Series. Wiley, New York, 1994. 4. J. Beran. Statistics for Long-Memory Processes. Monographs on Statistics and Applied Probability. Chapman and Hall, New York, 1994. 5. J.-C. Bolot and A. U. Shankar. Analysis of a uid approximation to ow control dynamics. In Proc. IEEE INFOCOM'92, pp. 2398 2407, 1992. 6. L. Brakmo and L. Peterson. TCP Vegas: end to end congestion avoidance on a global internet. IEEE J. Select. Areas Commun., 13(8):1465 1480, 1995. 7. I. Chlamtac and W. R. Franta. Rationale, directions, and issues surrounding high speed networks. Proc. IEEE, 78(1):94 120, 1990. 8. M. Crovella and A. Bestavros. Self-similarity in World Wide Web traf c: evidence and possible causes. In Proceedings of the 1996 ACM SIGMETRICS International

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