Abstract
Statistical multiplexing requires a decision function to classify which source combinations can be multiplexed through a given packet network node while meeting quality of service guarantees. This chapter shows there are no practical fixed statistical multiplexing decision functions that carry reasonable loads and rarely violate quality of service requirements under all distributions of source combinations. It reviews adaptive alternatives and presents statistical-classification-based decision functions that show promise across many distributions including difficult-to-analyze ethernet data, distributions with cross-source correlations, and traffic with mis-specified parameters.
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© 2002 Kluwer Academic Publishers
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Brown, T.X. (2002). Adaptive Statistical Multiplexing for Broadband Communication. In: Kouvatsos, D. (eds) Performance Evaluation and Applications of ATM Networks. The International Series in Engineering and Computer Science, vol 557. Springer, Boston, MA. https://doi.org/10.1007/0-306-47023-3_3
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DOI: https://doi.org/10.1007/0-306-47023-3_3
Publisher Name: Springer, Boston, MA
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