Multimedia Traffic Algorithm: Computation of Burstiness Curve

The variability rate of video sources has introduced the need for characterizing network traffic. Characterizing traffic can estimate the amount of resources allocated by a network (such as bandwidth, buffer space, etc.) during the call admission control (CAC) process. This is necessary for efficient traffic policing. Moreover, one common method of characterizing a traffic source is with its burstiness curve. Each point in a burstiness curve corresponds to the maximum queue size encountered (or the amount of buffering needed) when a traffic source is fed into a server with a deterministic service rate. The burstiness curve is useful in the optimal allocation of resources to satisfy a desired quality of service for a video stream in a packet network. University of California, Santa Cruz Office for Management of Intellectual Property 831.459.5415

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