Probabilistic flooding coverage analysis in large scale wireless networks

Information dissemination is a challenging problem in modern wireless networks in which unnecessary transmissions waste valuable resources. Approaches like traditional flooding, are not suitable in these typically large scale and inherently dynamic environments due to the large number of messages transmitted in the network. Probabilistic flooding has been proposed as a suitable alternative, capable of pruning unnecessary transmissions, while at the same time maintaining a large proportion of the network nodes covered. In this approach, the main analysis objective is on the particular threshold probability, for which the number of messages is minimized and almost all network nodes receive the initial piece of information. The analysis proposed in this paper results in a tractable analytical expression regarding coverage, in the form of a polynomial. Studying its roots: (i) results existing in the open literature are confirmed; and (ii) new and tighter boundaries for the threshold probability are derived. Simulation results confirm the analytical findings and in addition, they demonstrate that the obtained boundaries are suitable for achieving high coverage when probabilistic flooding is employed.