Characterizing and modeling network traffic variability

This paper advocates using the recently introduced index of variability (IDV) and a new measure, peak rate variability (PRV), to characterize the variability (burstiness) in real communications network traffic over the entire range of time scales. Further, we suggest the general hyperexponential interarrival distribution as a model suitable for network traffic and evaluate the ability of the third-order hyperexponential model to capture IDV, PRV and queuing characteristics. Although the hyperexponential interarrival distribution holds promise for network traffic modeling, in part due to its analytical tractability, we conclude that hyperexponential models with order larger than 3 will be required to model the burstiness of real network traffic adequately.