Exploiting Heavy-Tailed Statistics for Predictable QoS Routing in Ad Hoc Wireless Networks
Song Luo
Li, J.H.
Kihong Park
Levy, R.
Intell. Autom. Inc., Rockville;
This paper appears in: INFOCOM 2008. The 27th Conference on Computer Communications. IEEE
Publication Date: 13-18 April 2008
On page(s): 2387-2395
Location: Phoenix, AZ,
ISSN: 0743-166X
ISBN: 978-1-4244-2025-4
INSPEC Accession Number: 9945313
Digital Object Identifier: 10.1109/INFOCOM.2008.308
Current Version Published: 2008-05-02
Abstract
Extensive measurement and analysis have shown that traffic in data networks is better described by heavy-tailed distributions. In this paper, we present our current work on ad hoc routing by exploiting the heavy-tailed nature of the flow lifetime. In particular, the long- and short-lived flows are differentiated based on the unique predictability nascent in heavy- tailed distributions, with the long- and short-lived flows being handled separately. A modified AODV has been implemented to enable heavy-tailedness awareness. Simulation results reveal that the new protocol, AODV-HT, significantly outperforms the state-of-the-art under heavy-tailed workload.
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