Self-Similarity of Data Traffic in a Delay Tolerant Network

Delay Tolerant Networks (DTNs) ranging from Inter-Planetary Networks (IPN) to Vehicular Ad Hoc Networks (VANETs) are receiving continuous attention in recent years. The existing protocols for DTNs have been primarily designed and analyzed under the assumption that data traffic is either Constant Bit Rate (CBR) or Poisson. It has been observed that such models are incapable of capturing the inter-arrival behavior of the present day traffic which may be bursty in nature. The traffic characteristics in todays communication networks are statistically self-similar in nature, i.e., burstiness and correlation exists over many time scales, also referred to as Long Range Dependency (LRD). In this paper we analyze the traffic characteristics in the nodes of a delay tolerant network. Self-similar traffic is generated by implementing a traffic model in the source module of DTN. It is based on the model of aggregated ON/OFF sources. A mathematical analysis is provided to elucidate the cause of self similar nature of traffic in DTN. Through simulations and statistical analysis of the traffic data, we study the degree of self-similarity of traffic in the nodes of a vehicular delay tolerant network.