摘要
High resolution traffic measurements from modern communications networks provide unique opportunities for developing and validating mathematical models for aggregate traffic, or WAN (wide area network) traffic. To exploit these opportunities, this paper emphasized the need for structural model that takes into account specific physical feature of the underlying communication network structure. This approach is in sharp contrast to the traditional black box modeling methodology from this time series analysis that ignores, in general, specific physical structure. The paper demonstrated, in particular, how the proposed structural modeling approach provides a direct link between the observed self similarity characteristic of measured aggregate network traffic and the strong empirical evidence in favor of heavy tailed, infinite variance phenomena at the level of individual network connections.
High resolution traffic measurements from modern communications networks provide unique opportunities for developing and validating mathematical models for aggregate traffic, or WAN (wide area network) traffic. To exploit these opportunities, this paper emphasized the need for structural model that takes into account specific physical feature of the underlying communication network structure. This approach is in sharp contrast to the traditional black box modeling methodology from this time series analysis that ignores, in general, specific physical structure. The paper demonstrated, in particular, how the proposed structural modeling approach provides a direct link between the observed self similarity characteristic of measured aggregate network traffic and the strong empirical evidence in favor of heavy tailed, infinite variance phenomena at the level of individual network connections.
