Abstract
Paxson and Floyd (IEEE/ACM T. Netw. 1995) remarked the limitation of fractional Gaussian noise (FGN)) in accurately modeling LRD network traffic series. Beran (1994) suggested developing a sufficient class of parametric correlation form for modeling whole correlation structure of LRD series. M. Li (Electr. Letts., 2000) gave an empirical correlation form. This paper 1 extends Li's previous letter by analyzing it in Hilbert space and showing its flexibility in data modeling by comparing it with FGN (a commonly used traffic model). The verifications with real traffic suggest that the discussed correlation structure can be used to flexibly model LRD traffic series. © IFIP International Federation for Information Processing 2004.
Cite
CITATION STYLE
Li, M., Liu, J., & Long, D. (2004). An empirical autocorrelation form for modeling LRD traffic series. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3222, 399–402. https://doi.org/10.1007/978-3-540-30141-7_55
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