Adaptive random sampling for traffic volume measurement.

Baek-Young Choi; Zhi-Li Zhang

Abstract??Traffic measurement and monitoring are an important component of network management and traffic engineering. With high-speed Internet backbone links, efficient and effective packet sampling techniques for traffic measurement and monitoring are not only desirable, but also increasingly becoming a necessity. Since the utility of sampling depends on theaccuracyandeconomyof measurement, it is important tocontrolsampling error. In this paper, we propose anadaptivepacket sampling technique forflow-leveltraffic measurement withstratification approach. We employ and advance sampling theory in order to ensure the accurate estimation of large flows. With real network traces, we demonstrate that the proposed sampling technique provides unbiased estimation of flow size withcontrollable error bound, in terms of both packet and byte counts forelephantflows, while avoiding excessive oversampling.

STATISTICAL sampling; COMPUTER network management; BOTTLENECKS (Manufacturing); WAVE packets

Telecommunication Systems, 2007, Vol 34, Issue 1/2, p71

1018-4864

Academic Journal

10.1007/s11235-006-9023-z