计算机科学 ›› 2019, Vol. 46 ›› Issue (11): 94-99.doi: 10.11896/jsjkx.181001975
刘璐1,2, 赵国庆2
LIU Lu1,2, ZHAO Guo-qing2
摘要: 为了改善多媒体数据的传输效率和系统执行度,降低多媒体服务的运营成本,从多媒体系统群体行为的分析模型和演化出发,研究了一种基于雾计算的智能激励机制。首先,从单一化、分散部署与冗余健壮特征和自主管理的群体特质出发,为分布式多媒体系统建立群体行为分析演化模型,并给出了多媒体系统进行群体行为分析的演化算法。接着,根据获取的最大化系统效用,通过自组织和主动演化来调度雾服务器节点。以优化个体服务策略为目标,雾计算结合演化进程控制群体行为参与度。在此基础上,雾服务器节点逐步更新个体调度,并实时统计系统拓扑调度效应。仿真实验基于Matlab的网络控制系统仿真平台,部署了多媒体系统。通过Matlab仿真了分布式多媒体系统的拓扑与无线传输,结合C语言实现提出的EMSSB(Evolution algorithm of Multimedia Systems Swarming Behavior)算法和IIFS(Intelligent Incentive algorithm with Fog computing and Swarming Behavior)算法。仿真实验的数据均为100次重复时延的平均值。每次重复实验中,除了将用户发出多媒体请求的时间和次数设置为随机,其他参数均保持一致。仿真结果表明,所提激励算法在多媒体数据传输的实时性、雾节点激励有效性和用户请求响应等方面表现良好。所提激励算法可以将端到端时延缩短45%,有效控制参与度,并根据用户请求数控制不同的参与比例,此外可以将用户响应时延和多媒体数据流传输延迟分别缩短53%和45%。
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