Model-based end-to-end available bandwidth inference using queueing analysis

  • Authors:
  • Xiaojun Hei;Brahim Bensaou;Danny H. K. Tsang

  • Affiliations:
  • Department of Electrical & Electronic Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;Department of Electrical & Electronic Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Network modelling and simulation
  • Year:
  • 2006

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Abstract

End-to-end available bandwidth estimation between Internet hosts is important to understand network congestion and enhance the performance of Quality-of-Service (QoS) demanding applications. In this paper, we investigate model-based available bandwidth measurement via the use of an active probing stream. A general end-to-end measurement framework, which unifies the current research approaches and highlights insights for measurement practice, is proposed. Within this framework, the end-to-end available bandwidth is inferred based on the measurement of the performance metrics of an active probing stream. We study two probing streams: Poisson and periodic probing. Of particular interest to our investigations is the Squared Coefficient of Variation (SCV) of the inter-probing packet arrival time at the receiver. The performance comparison of the available bandwidth measurements based on loss models and delay models indicates that the delay-based measurement exhibits many advantages over the loss-based measurements, such as accuracy, overhead and robustness. We conducted a comparison study between the proposed SCV-baged probing scheme, namely, SCVProbe, and Pathload using ns-2 simulation in terms of probing accuracy, convergence time and overhead. Our evaluation results indicate that SCVProbe achieves similar or even better measurement accuracy than Pathload with much less probing time and smaller overhead.