Exploiting Heavy-Tailed Statistics for Predictable QoS Routing in Ad Hoc Wireless Networks

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.