Affect analysis of FFT algorithm length on traffic self-similarity in NOC

With network performance being highly dependent on the actual traffic, studies have shown that traffic is self-similar and long-range correlation in Network on Chip (NoC). The self-similarity of NoC traffic depends not only on the input sequence, but also changes with the processor algorithm on chip...

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Bibliographic Details
Main Authors: Qin, Ming-Wei, Hu, Jian-Hao, Ma, Shang
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Computer simulation
Conferences
Educational institutions
FFT
Fourier transforms
Hurst exponent
Integrated circuit modeling
Network on Chip
Networks
Self-similarity
Signal processing algorithms
System on chip
Traffic
Traffic engineering
Traffic flow
Very large scale integration
Wavelet transforms
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Summary:With network performance being highly dependent on the actual traffic, studies have shown that traffic is self-similar and long-range correlation in Network on Chip (NoC). The self-similarity of NoC traffic depends not only on the input sequence, but also changes with the processor algorithm on chip. In this paper, we improved firstly the existing method for generating sample traces of self-similar processes to suit Fast Fourier Transform (FFT) Algorithm. Then, Mainly studied the effects of FFT algorithm length for network traffic self-similarity in NoC by simulations. Experimental results show that the self-similarity of output sequence raised with the increasing of FFT length, and the output sequence is not self-similar when the length is long enough.
DOI:10.1109/ICCWAMTIP.2013.6716620