Identifying isochronous traffic using packet interarrival times: a feasibility study

Joseph D. Sloan; Harvey M. Gates

doi:10.1117/12.333702

16 December 1998 Identifying isochronous traffic using packet interarrival times: a feasibility study

Joseph D. Sloan, Harvey M. Gates

Proceedings Volume 3529, Internet Routing and Quality of Service; (1998) https://doi.org/10.1117/12.333702
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

An algorithm was developed with the goal of automatically recognizing isochronous traffic in a packet switched network. Designed with constant bit rate traffic in mid, this algorithm examines the interarrival times between packets in flows classifying as isochronous those flows that have both an average inter arrival times between packets in flows classifying is isochronous those flows that have both an average interarrival time consistent with an isochronous application and sufficiently low variance for interarrival times. The algorithm was analyzed based on a priori considerations and was then applied to actual traffic in an effort to characterize the parameters for appropriate use. Traffic flows from several common isochronous applications were examined focusing on common CODECs. From a priori considerations, the algorithm has the desirable characteristics of building intelligence into the network and being purely local to the individual switch or router on which it is installed while totally transparent to other equipment. While the approach appears sound in general principle, the isochronous applications examined show a much higher degree of variability in packet rates than expected. Moreover, most common applications seem to be shifting to CODECs that produce variable bit rate traffic. Thus, using the algorithm with such applications would require a st of threshold parameters that would likely result in a high misclassification rate.

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Joseph D. Sloan and Harvey M. Gates "Identifying isochronous traffic using packet interarrival times: a feasibility study", Proc. SPIE 3529, Internet Routing and Quality of Service, (16 December 1998); https://doi.org/10.1117/12.333702

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Detection and tracking algorithms

Algorithm development

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Data analysis

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