Measurement and analysis of intraflow performance characteristics of wireless traffic

Pezaros, D. , Sifalakis, M. and Hutchison, D. (2007) Measurement and analysis of intraflow performance characteristics of wireless traffic. In: IEEE International Workshop on IP Operations and Management (IEEE IPOM’07), San José, CA, USA, October 29-November 2, (doi: 10.1007/978-3-540-75853-2_13)

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It is by now widely accepted that the arrival process of aggregate network traffic exhibits self-similar characteristics which result in the preservation of traffic burstiness (high variability) over a wide range of timescales. This behaviour has been structurally linked to the presence of heavy-tailed, infinite variance phenomena at the level of individual network connections, file sizes, transfer durations, and packet inter-arrival times. In this paper, we have examined the presence of fractal and heavy-tailed behaviour in a number of performance aspects of individual IPv6 microflows as routed over wireless local and wide area network topologies. Our analysis sheds light on several questions regarding flow-level traffic behaviour: whether burstiness preservation is mainly observed at traffic aggregates or is it also evident at individual microflows; whether it is influenced by the end-to-end transport control mechanisms as well as by the network-level traffic multiplexing; whether high variability is independent from diverse link-level technologies, and whether burstiness is preserved in end-to-end performance metrics such as packet delay as well as in the traffic arrival process. Our findings suggest that traffic and packet delay exhibit closely-related Long-Range Dependence (LRD) at the level of individual microflows, with marginal to moderate intensity. Bulk TCP data and UDP flows produce higher Hurst exponent estimates than the acknowledgment flows that consist of minimum-sized packets. Wireless access technologies seem to also influence LRD intensity. At the same time, the distributions of intraflow packet inter-arrival times do not exhibit infinite variance characteristics.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Pezaros, Professor Dimitrios
Authors: Pezaros, D., Sifalakis, M., and Hutchison, D.
Subjects:Q Science > Q Science (General)
College/School:College of Science and Engineering > School of Computing Science
First Published:First published in Lecture Notes in Computer Science 4786:143-155
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher.
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