Statistical-classification-based admission control
Timothy X. Brown · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
This paper introduces methods based on statistical classification that allow arbitrary measurement features to be incorporated into admission control decisions. Our results show that for high target packet loss rates, nearly any set of features can control the packet loss rate well, while for low target packet loss rates more features provide better control. The methods demonstrate relatively high accuracy in controlling the packet loss rate for both high and low target loss rates and for both memoryless and heavy-tailed traffic distributions. These results represent significant improvements on prior methods and suggest new directions for future research.