Measurement-Based Admission Control with Aggregate Traffic Envelopes
The goal of admission control is to support the quality-of-service demands of real-time applications via resource reservation. In this paper, we introduce a new approach to Measurement-Based Admission Control (MBAC) based on adaptive and measurement-based maximal rate envelopes of the aggregate traffic flow. We show that such traffic envelopes provide a robust and accurate characterization of the aggregate traffic, capturing its temporal correlation as well as the available statistical multiplexing gain. In estimating applications’ future performance, we introduce the notion of a schedulability confidence level which describes the uncertainty of the measurement—based “prediction” and reflects estimation errors and temporal variations in the measured envelope. We then apply principles from extreme value theory and devise techniques to estimate the packet loss probability for a buffered multiplexer. Our results are quite general and apply to heterogeneous and bursty traffic flows belonging to a broad class of underlying traffic distributions including Gaussian, log-normal, and Gamma.
KeywordsTraffic Flow Admission Control Loss Probability Resource Reservation Packet Loss Probability
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