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Data from: Designing efficient hybrid strategies for information spreading in scale-free networks

Cite this dataset

Wang, Shuangyan; Cheng, Wuyi; Hao, Yang (2018). Data from: Designing efficient hybrid strategies for information spreading in scale-free networks [Dataset]. Dryad. https://doi.org/10.5061/dryad.kj2d3

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 combing two basic strategies, i.e., (1) the LS (in which information is preferentially spread from the Large-degree vertices to the Small-degree ones) and (2) 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.

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