Abstract
Data, voice, and compressed moving pictures flowing in ATM broadband ISDN networks are expected to be high autocorrelated time series traffics which are different from conventional voice and packet traffics. This paper first describes traffic modeling by a self-similar process for time series data. Second, it computes the value of the Hurst parameter which shows self-similarity of the traffic using the method of R/S analysis for moving picture data recorded on a laser disk with MPEG2 compression with variable bit length. As a result of this analysis, we found a high degree of self-similarity, that is, long memory property of the traffic, because MPEG2 generates I frame periodically. © 2000 Scripta Technica, Electron Comm Jpn Pt 1, 83(6): 108–116, 2000
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