Network and user driven alpha-beta on-off source model for network traffic

We shed light on the effect of network resources and user behavior on network traffic through a physically motivated model. The classical on-off model successfully captures the long-range, second-order correlations of traffic, allowing us to conclude that transport protocol mechanisms have little influence at time scales beyond the round trip time. However, the on-off model fails to capture the short-range spikiness of traffic, where protocols and congestion control mechanisms have greater influence. Based on observations at the connection-level we conclude that small rate sessions can be characterized by independent duration and rate, while large rate sessions have independent file size and rate. In other words, user patience is the limiting factor of small bandwidth connections, while users with large bandwidth freely choose their files. We incorporate these insights into an improved two-component on-off model-which we call the alpha-beta on-off model-comprising an aggressive alpha component (high rate, large transfer) and passive beta component (residual). We analyze the performance of our alpha-beta on-off model and use it to better understand the causes of burstiness and long-range dependence in network traffic. Our analysis yields new insights on Internet traffic dynamics, the effectiveness of congestion control, the performance of potential future network architectures, and the key parameters required for realistic traffic synthesis.