Network and User Driven Alpha-Beta Onâ Off Source Model for Network Traffic

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Title: Network and User Driven Alpha-Beta Onâ Off Source Model for Network Traffic
Author: Sarvotham, Shriram; Riedi, Rudolf H.; Baraniuk, Richard G.
Type: Journal article
xmlui.Rice_ECE.Keywords: Alpha-beta onâ off model; Network traffic; Long-range dependence
Citation: S. Sarvotham, R. H. Riedi and R. G. Baraniuk, "Network and User Driven Alpha-Beta Onâ Off Source Model for Network Traffic," Computer Networks, vol. 48, no. 3, pp. 335-350, 2005.
Abstract: We shed light on the effect of network resources and user behavior on network traffic through a physically motivated model. The classical onâ 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 onâ 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 onâ off modelâ which we call the alpha-beta onâ off modelâ comprising an aggressive alpha component (high rate, large transfer) and passive beta component (residual). We analyze the performance of our alpha-beta onâ 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.
Date Published: 2005-06-01

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  • ECE Publications [1053 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.