On the time scales in video traffic characterization for queueing behavior

To guarantee quality of service (QoS) in future integrated service networks , traffic sources must be characterized to capture the traffic characterist ics relevant to network performance. Recent studies reveal that multimedia traffic shows burstiness over multiple time scales and long range dependenc e (LRD). While researchers agree on the importance of traffic correlation t here is no agreement on how much correlation should be incorporated into a traffic model for performance estimation and dimensioning of networks. In this article, we present an approach for defining a relevant time scale for the characterization of VER video traffic in the sense of queueing dela y. We first consider the Reich formula and characterize traffic by the Piec ewise Linear Arrival Envelope Function (PLAEF). We then define the cutoff i nterval above which the correlation does not affect the queue buildup. The cutoff interval is the upper bound of the time scale which is required for the estimation of queue size and thus the characterization of VER video tra ffic. We also give a procedure to approximate the empirical PLAEF with a co ncave function; this significantly simplifies the calculation in the estima tion of the cutoff interval and delay bound with little estimation loss. We quantify the relationship between the time scale in the correlation of v ideo traffic and the queue buildup using a set of experiments with traces o f MPEG/JPEG-compressed video. We show that the critical interval i.e. the r ange for the correlation relevant to the queueing delay, depends on the tra ffic load: as the traffic load increases, the range of the time scale requi red for estimation for queueing delay also increases. These results offer f urther insights into the implication of LRD in VER video traffic. (C) 1999 Elsevier Science B.V. Ail rights reserved.