Models for discrete-time self-similar vector processes with application to network traffic

Seungsin Lee; Raghuveer M. Rao; Rajesh Narasimha

doi:10.1117/12.498577

23 July 2003 Models for discrete-time self-similar vector processes with application to network traffic

Seungsin Lee, Raghuveer M. Rao, Rajesh Narasimha

Proceedings Volume 5100, Digital Wireless Communications V; (2003) https://doi.org/10.1117/12.498577
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

Citation Download Citation

Seungsin Lee, Raghuveer M. Rao, and Rajesh Narasimha "Models for discrete-time self-similar vector processes with application to network traffic", Proc. SPIE 5100, Digital Wireless Communications V, (23 July 2003); https://doi.org/10.1117/12.498577

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