Large impact of temporal/spatial correlations on per-session performance measures: single and multiple node cases

The problem of evaluating the end-to-end performance in an ATM environment is known to be difficult and largely open. Since applications may have very different quality of service (QoS) requirements, a performance measure associated with a random cell would not necessarily reveal the impact of multiplexing on the QoS of a specific application. For this reason, it is important that the traffic stream of interest be tagged and its distortion due to multiplexing be evaluated; for analysis purposes the co-existing traffic is aggregated and forms the background traffic. In the past studies the background traffic has been assumed to be uncorrelated and be diverted after a single multiplexing stage. jective in this work is to evaluate the impact of temporal and spatial correlations on the end-to-end performance of a tagged traffic stream. Such correlations can be significant due to temporal correlation in the background traffic or partial commonality in the routing path (background traffic is not necessarily diverted). A binary queuing activity indicator (QAI) is proposed in this work to provide for a simple mechanism to capture these correlations. Results derived for various delay metrics of a tagged traffic stream associated with single and multiple nodes show the substantial impact of the spatial/temporal correlations. Furthermore, they suggest that the proposed QAI indicator is capable of capturing such correlations.