Adaptive Sampling for Network Management, Fuzzy Logic

1. Adaptive Network Management Edwin Hernandez HCS - Lab June 8th, 1999

3. Measurements of Self-similarity in traffic patterns used To determine the hurst parameter, it is required to use the Log(Variance) vrs Log(granularity) graph. In this experiment the Granularity refers to different sampling times. This method is based in the property of slowly decaying variance. The relationship is defined by  =2H-2, and var(X (m) )  am -  , as m   H=0.5337, Videoconference data - multimedia traffic

4. Self-similarity in traffic H=0.8137, TCP Traffic using as source Fractional Gaussian Noise tool (by Vern Paxon, et.al. UCB). Traffic stimulation between hornet and raptor.

5. Results for Adaptive samplers Results using the previous policies. The problem is presented with H=0.5, where the STDev is 3.2 times the average value. High frequency components lost. With H=0.8, The STDev is only 0.31 of the average value.

6. Throughput with H=0.8 Systematic sampling at T=1s