Diffusion Models for Information Dissemination Dynamics in Wireless Complex Communication Networks. (4th September 2013)

• Record Type: Journal Article
• Authors: Cheng, Shin-Ming; Karyotis, Vasileios; Chen, Pin-Yu; Chen, Kwang-Cheng; Papavassiliou, Symeon
• Other Names: Zhang Jinhui Academic Editor.
• Is Part Of: Journal of complex systems. Volume 2013(2013)
• Publication Date: 2013-09-04
• Subjects: System analysis -- Periodicals; Computational complexity -- Periodicals; Coupled problems (Complex systems) -- Periodicals; Systems engineering -- Periodicals; Computational complexity; Coupled problems (Complex systems); System analysis; Systems engineering; Electronic journals; Periodicals; 003
• DOI: 10.1155/2013/972352
• Languages: English
• ISSNs: 2356-7244

Abstract

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.