大数据联盟成员间数据资源共享动态演化博弈模型研究——基于共享积极性视角

Research on Dynamic Evolutionary Game Model of Data Resource Sharing among Big Data Alliance Members:Based on the Perspective of Sharing Positivity

为促进大数据联盟成员共享积极性由“倒U”型曲线向“S”型曲线转变,提高联盟运行的稳定性,引入“机会主义共享”策略,丰富传统演化博弈策略集,更加全面地反映出不同积极性状态下大数据联盟共享行为,构建了具备“不共享-机会主义共享-共享”策略集的大数据联盟数据资源共享动态演化博弈模型,揭示了联盟成员在积极和消极状态下的演化博弈行为。并在此基础上通过MATLAB模拟大数据联盟成员间共享博弈演化路径,分析出影响大数据联盟成员共享积极性的关键因素。结果表明,社会惩罚系数对联盟成员选择共享策略具有正向影响,投机收益系数对联盟成员选择共享策略具有负向影响,而提高共享积极程度有利于联盟成员由消极共享状态向积极共享状态的转变。

To promote the sharing positivity of big data alliance members from“inverted U”curve to“S”curve and improve the stability of alliance operations,the conception of“opportunistic sharing”strategy has been adoped to introduce alliance members.The strategy can not only enrich the traditional game strategy set,but also give more comprehensive reflects on the sharing behavior of big data alliance members under difference positive states.On this premise,this paper tries to construct a dynamic evolution game model for big data alliance,which has“no sharing-opportunistic sharing-sharing”strategy sets.It reveals the evolutionary game behavior of alliance members in positive and negative cases,and analyzes the key factors influencing the resource sharing positivity by using MATLAB to simulate the evolutionary path of the sharing game theory on big data alliance members.In the end,the results show that the social penalty coefficient has positive effects on the selection strategy of the alliance members,while the speculative yield coefficient negative.At the same time,the increase of the degree of sharing positivity is beneficial to the members of the alliance converting from the negative to the active sharing states.