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

Abstract

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

“…5) The first meeting time of any two nodes moving in the same fixed movement mode, starting from a random time, is exponentially distributed. This assumption is reasonable when R L c and R L [12], and has been extensively used in recent years [14], [23], [24], [27], [28], [29] 7) The delay of a message transmission, which corresponds to a short time, is negligible [10], [12], [19], [23], [24], [30], [31], [32], [33], [34], [35].…”