Scaling Properties of Delay Tolerant Networks with Correlated Motion Patterns

Abstract

Mobile wireless networks with intermittent connectivity, often called Delay/Disruption Tolerant Networks (DTNs), have recently received a lot of attention because of their efficiency in various application scenarios where delay is noncritical. DTN routing and transport protocols effectively overcome partial connectivity by letting the nodes carry-and-forward data. The scalability of DTN protocols is very important for protocol design and evaluation. In particular, we need models that allow us to predict the performance of DTN as a function of node mobility behavior (e.g., inter-contact times). Yet so far little work has been done to develop a unified framework that formalizes DTN performance as a function of motion behavior. In this paper, we represent DTNs as a class of wireless mobile networks with intermittent connectivity, where the inter-contact behavior of an arbitrary pair of nodes can be described by a generalized two-phase distribution (i.e., a power-law head with an exponential tail). Recent experiments have confirmed that the two-phase distribution is the most realistic model for vehicular and pedestrian scenarios, where the specific shape of the distribution depends on the degree of correlation among mobile traces. Using this DTN model, we make the following contributions. First, we extend the throughput and delay scaling results of Grossglauser and Tse (derived for exponential inter-contact time distributions) to the two-phase distribution with motion correlation. Second, we analyze the impact of finite buffer on the capacity scaling properties of DTNs, again for different correlation behaviors. Finally, we validate our analytical results with a simulation study.