1992Unpublished venueRequires access

Measurements and characterization of traffic in a university environment

B.R. Venkatraman, R. Newman-Wolfe, Randy Chow, Haniph A. Latchman

Open publisher page 1 citations

Abstract

In this paper we characterize the traffic seen in a university environment, especially on the broadband medium which serves as the backbone. The traffic is characterized based on parameters such as the volume of traffic generated, the packet inter-arrival times, the packet size and the protocol type and application that generated the traffic. We use the packet train model to analyze and characterize the traffic. Network traffic being inherently bursty, we propose a practical definition for burstiness and evaluate the burstiness of the traffic measured. Finally we compare the appropriateness and relative efficiency of some of the tools used to measure network traffic and compare their performance.

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What this paper is about

In this paper we characterize the traffic seen in a university environment, especially on the broadband medium which serves as the backbone. The traffic is characterized based on parameters such as the volume of traffic generated, the packet inter-arrival times, the packet size and the protocol type and application that generated the traffic. We use the packet train model to analyze and characterize the traffic. Network traffic being inherently bursty, we propose a practical definition for burstiness and evaluate the burstiness of the traffic measured. Finally we compare the appropriateness and relative efficiency of some of the tools used to measure network traffic and compare their performance.

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Available abstract

In this paper we characterize the traffic seen in a university environment, especially on the broadband medium which serves as the backbone. The traffic is characterized based on parameters such as the volume of traffic generated, the packet inter-arrival times, the packet size and the protocol type and application that generated the traffic. We use the packet train model to analyze and characterize the traffic. Network traffic being inherently bursty, we propose a practical definition for burstiness and evaluate the burstiness of the traffic measured. Finally we compare the appropriateness and relative efficiency of some of the tools used to measure network traffic and compare their performance.

Key concepts: Burstiness, Computer science, Traffic generation model, Computer network, Network packet, Traffic shaping, Internet traffic engineering, Network traffic control

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