Designing efficient hybrid strategies for information spreading in scale-free networks.

Shuangyan Wang,Wuyi Cheng,Yang Hao

doi:10.1098/rsos.180117

Shuangyan Wang, Wuyi Cheng + Show 1 more

Open Access

https://doi.org/10.1098/rsos.180117

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Abstract

Designing a spreading strategy is one of the critical issues strongly affecting spreading efficiency in complex networks. In this paper, to improve the efficiency of information spreading in scale-free networks, we propose four hybrid strategies by combining two basic strategies, i.e. (i) the LS (in which information is preferentially spread from the large-degree vertices to the small-degree ones), and (ii) the SL (in which information is preferentially spread from the small-degree vertices to the large-degree ones). The objective in combining the two basic LS and SL strategies is to fully exploit the advantages of both strategies. To evaluate the spreading efficiency of the proposed four hybrid strategies, we first propose an information spreading model. Then, we introduce the details of the proposed hybrid strategies that are formulated by combining LS and SL. Third, we build a set of scale-free network structures by differently configuring the relevant parameters. In addition, finally, we conduct various Monte Carlo experiments to examine the spreading efficiency of the proposed hybrid strategies in different scale-free network structures. Experimental results indicate that the proposed hybrid strategies are effective and efficient for spreading information in scale-free networks.

Highlights

In the context of network theory, a complex network is a graph with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often occur in graphs modelling real systems [1,2,3]
It has been widely learned that the largedegree vertices in a scale-free network are of greater diffusions because they have more connections, and it typically costs much more spreading time for small-degree vertices owing to their fewer connections
The LS strategy effectively exploits the diffusion of large-degree vertices, while the SL strategy reduces the consumption of spreading small-degree vertices

Summary

Introduction

In the context of network theory, a complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often occur in graphs modelling real systems [1,2,3]. Salvatore Cuomo et al [23,24] proposed the Integrate & Fire (IF) network to analyse the information sharing and typical behaviours between visitors In their approach, the visitor is modelled as a computational neuron, which is connected with his friends by means of synapses (i.e. connections), representing friendship and/or common interests among them. We examine the spreading efficiency of the proposed hybrid strategies in different scale-free network structures. The rest of this paper is organized as follows: §2 gives a brief introduction to the problem that is to be addressed in this paper; §3 describes the proposed information spreading model and the hybrid strategies in detail; in addition, §3 gives an introduction to the experimental process for evaluating the spreading efficiency; and §§4 and 5 present and discuss the results of the experiments, respectively.

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Discussion

Conclusion