Implementation of Hurst parameter on DSP processor TMS320C6713 platform using wavelet analysis

Priyanka Pawar, Supriya M. Pharande, P. Wani, A. Patki
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Abstract

Over the last 20 years, analysis, modeling and simulation of network traffic in different networks adopted techniques based on statistics and probability theory. We bring out the limitations of these approaches and implement alternative approach using the long range dependence and self-similarity in the network traffic focused around wavelet analysis method. Hurst (H) parameter estimates amount of self similarity is evaluated using this proposed method. The algorithm is implemented in C programming language. The synthetic self similar traffic with predefined H parameter is used as an input. Real-time implementation of the proposed algorithm using C programming language is implemented in TMS320C6713 processor.
利用小波分析在DSP处理器TMS320C6713平台上实现Hurst参数
近20年来,对不同网络中网络流量的分析、建模和仿真采用了基于统计和概率论的技术。我们指出了这些方法的局限性,并以小波分析方法为中心,利用网络流量的远程依赖和自相似性实现了替代方法。利用该方法对Hurst (H)参数估计量进行了自相似度评估。该算法用C语言实现。采用预定义H参数的合成自相似流量作为输入。在TMS320C6713处理器上,用C语言实现了该算法的实时实现。
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