A non-instrusive, wavelet-based approach to detecting network performance problems
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
A wavelet-based approach to detect shared congestion
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Wavelet compression techniques for computer network measurements
SPPR'07 Proceedings of the Fourth conference on IASTED International Conference: Signal Processing, Pattern Recognition, and Applications
The discrete multiple wavelet transform and thresholding methods
IEEE Transactions on Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
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Measuring metrics of high-speed networks produces large amounts of information over long periods of time, making the conventional storage of the data practically inefficient. Such metrics are derived from packet information and can be represented as time series signals. This paper looks at the Wavelet transform as a method of analysing and compressing measurement signals. A live system calculates these measurements and performs wavelet techniques to preserve the significant information and discard the small variations. An investigation of an appropriate wavelet is presented along with results from off-line and on-line experiments. Finally, a comparison of compression performance is presented against bzip2.