Table of Contents
Journal of Complex Systems
Volume 2013 (2013), Article ID 972352, 13 pages
http://dx.doi.org/10.1155/2013/972352
Research Article

Diffusion Models for Information Dissemination Dynamics in Wireless Complex Communication Networks

1National Taiwan University of Science and Technology, Taipei 106, Taiwan
2School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), 15780 Zografou, Athens, Greece
3Department of EECS, University of Michigan, Ann Arbor, MI 48109, USA
4Graduate Institute of Communication Engineering, National Taiwan University, Taipei 106, Taiwan

Received 1 May 2013; Revised 18 July 2013; Accepted 29 July 2013

Academic Editor: Jinhui Zhang

Copyright © 2013 Shin-Ming Cheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Information dissemination has become one of the most important services of communication networks. Modeling the diffusion of information through such networks is crucial for our modern information societies. In this work, novel models, segregating between useful and malicious types of information, are introduced, in order to better study Information Dissemination Dynamics (IDD) in wireless complex communication networks, and eventually allow taking into account special network features in IDD. According to the proposed models, and inspired from epidemiology, we investigate the IDD in various complex network types through the use of the Susceptible-Infected (SI) paradigm for useful information dissemination and the Susceptible-Infected-Susceptible (SIS) paradigm for malicious information spreading. We provide analysis and simulation results for both types of diffused information, in order to identify performance and robustness potentials for each dissemination process with respect to the characteristics of the underlying complex networking infrastructures. We demonstrate that the proposed approach can generically characterize IDD in wireless complex networks and reveal salient features of dissemination dynamics in each network type, which could eventually aid in the design of more advanced, robust, and efficient networks and services.