Buffer Size Estimation for Nodes in Delay Tolerant Vehicular Networks Under Self-Similar Traffic

Abstract

Delay and Disruption Tolerant Networks (DTNs) are attracting significant attention in recent years. It has been shown that the traffic in DTNs may also be bursty and correlated and therefore exhibit self-similar characteristics. The proposed work analyses the queueing behaviour and estimates the crucial network parameter, buffer size in vehicular DTN in presence of bursty traffic. We have modified the existing $N$-burst model for a delay tolerant environment to show that, even with fairly low buffer overflow probability (BOP), the buffer size in such type of networks can be substantially large. Simulations and statistical analysis of the data traffic concretize the fact that our proposed $N$-burst model exhibits self-similarity in a vehicular DTN environment and gives realistic buffer size for target BOPs.