Quantifying the temporal characteristics of network congestion events for multimedia services

Abstract

Effective quality-of-service (QoS) metrics must relate to end-user experience. For multimedia services these metrics should focus on phenomena that are observable by the end user. Once a congestion event occurs in the network it tends to persist, resulting in long bursts of consecutive packet loss. Such an event is observable to the network customer. There is a need to increase our understanding of the temporal characteristics of congestion. It has become increasingly apparent that the temporal characteristics of congestion events have the dominant effect on user-perceived QoS. A rigorous definition of the time between congestion events is given here, as well as an associated prediction methodology. The inter-congestion event time or the rate of congestion events per unit time provides a network quality metric that is easily understandable to network users and is conveniently predicted and measured. The contribution of this paper is the definition of a metric to characterize congestion events and development of an analytic methodology to predict the expected number of congestion events per unit time. The proposed methodology is evaluated for a variety of traffic models.