Why Do Cascade Sizes Follow a Power-Law?

We introduce random directed acyclic graph and use it to model the information diffusion network. Subsequently, we analyze the cascade generation model (CGM) introduced by Leskovec et al. [19]. Until now only empirical studies of this model were done. In this paper, we present the first theoretical proof that the sizes of cascades generated by the CGM follow the power-law distribution, which is consistent with multiple empirical analysis of the large social networks. We compared the assumptions of our model with the Twitter social network and tested the goodness of approximation.Comment: 8 pages, 7 figures, accepted to WWW 201

Revisiting Gossip-based Ad-Hoc Routing

Abstract—We focus on a popular message dissemination protocol for wireless ad-hoc networks, GOSSIP3. Our contribution is twofold. First, we perform an extensive experimental evaluation of GOSSIP3 under fully utilized wireless channel and across diverse node densities. We identify the parameters of GOSSIP3 that need special configuration for the protocol to operate optimally. Second, we devise a self-configuration algorithm for GOSSIP3 that allows the protocol to work optimally for any network. We demonstrate through simulations that our protocol significantly outperforms the default configuration of GOSSIP3. I