On the Performance Analysis of Epidemic Routing in Non-Sparse Delay Tolerant Networks

We study the behavior of epidemic routing in a delay tolerant network as a function of node density. Focusing on the probability of successful delivery to a destination within a deadline (PS), we show that PS experiences a phase transition as node density increases. Specifically, we prove that PS exhibits a phase transition when nodes are placed according to a Poisson process and allowed to move according to independent and identical processes with limited speed. We then propose four fluid models to evaluate the performance of epidemic routing in non-sparse networks. A model is proposed for supercritical networks based on approximation of the infection rate as a function of time. Other models are based on the approximation of the pairwise infection rate. Two of them, one for subcritical networks and another for supercritical networks, use the pairwise infection rate as a function of the number of infected nodes. The other model uses pairwise infection rate as a function of time, and can be applied for both subcritical and supercritical networks achieving good accuracy. The model for subcritical networks is accurate when density is not close to the percolation critical density. Moreover, the models that target only supercritical regime are accurate

Performance Modeling of Epidemic Routing in Mobile Social Networks with Emphasis on Scalability

This paper investigates the performance of epidemic routing in mobile social networks. It first analyzes the time taken for a node to meet the first node of a set of nodes restricted to move in a specific subarea. Afterwards, a monolithic Stochastic Reward Net (SRN) is proposed to evaluate the delivery delay and the average number of transmissions under epidemic routing by considering skewed location visiting preferences. This model is not scalable enough, in terms of the number of nodes and frequently visited locations. In order to achieve higher scalability, the folding technique is applied to the monolithic model, and an approximate folded SRN is proposed to evaluate performance of epidemic routing. Discrete-event simulation is used to validate the proposed models. Both SRN models show high accuracy in predicting the performance of epidemic routing. We also propose an Ordinary Differential Equation (ODE) model for epidemic routing and compare it with the folded model. Obtained results show that the folded model is more accurate than the ODE model. Moreover, it is proved that the number of transmissions by the time of delivery follows uniform distribution, in a general class of networks, where positions of nodes are always independent and identically distributed