The Uncertainty of Decisions in Measurement Based Admission Control

Most real-time voice and video applications are delay/loss sensitive but relaxed in the sense that they can tolerate some packet loss/delay. Using this information, network utilization can be greatly improved by exploiting statistical multiplexing. To this end, Measurement Based Admission Control (MBAC) has for a long time been recognized as a promising solution. MBAC algorithms, do not require an a priori source characterization which in many cases may be difficult or impossible to attain. Instead, MBAC uses measurements to capture the behavior of existing flows and uses this information together with some coarse knowledge of a new flow when making an admission decision for this requesting flow. The number one requirement of MBAC to be successful is that it can robustly provide Quality of Service (QoS) to the accepted flows. Being robust means that MBAC must be able to withstand a sudden increase in the number of users trying to access the network, handle applications with various capacity requirements and handle an aggregate rate that may change in a highly unpredictable manner