多媒体系统群体行为的雾计算智能激励机制

Intelligent Incentive Mechanism for Fog Computing-based Multimedia Systems with Swarming Behavior

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%。

In order to improve the efficiency of multimedia data transmission and system execution and reduce the ope-rating cost of multimedia services,this paper proposed an intelligent incentive mechanism based on fog computing from the analysis model and evolution of group behavior of multimedia systems.Firstly,based on the characteristics of simplification,decentralized deployment,redundancy,robustness and self-management,an evolutionary model of group behavior analysis for distributed multimedia systems is established,and an evolutionary algorithm of group behavior analysis for multimedia systems is presented.Then,in order to maximize the system utility,the fog server nodes are scheduled by self-organization and active evolution.In order to optimize individual service strategy,fog computing combines with evolutionary process to control group behavior participation.On this basis,the fog server nodes update individual sche-duling step by step,and real-time statistics the system topology scheduling effect.The simulation experiment is based on the simulation platform of networked control system of Matlab,and the multimedia system is deployed.The topology and wireless transmission of distributed multimedia system are simulated by Matlab.The EMSSB(Evolution algorithm of Multimedia Systems Swarming Behavior)algorithm and IIFS(Intelligent Incentive algorithm with Fog computing and Swarming Behavior)algorithm proposed above are implemented in combination with C language.The data of simulation experiments are the average of 100 repetition delays.In each repetitive experiment,the other parameters are consistent except that the time and number of multimedia requests are set to random.The simulation results show that the proposed incentive algorithm performs well in real-time multimedia data transmission,fog node incentive effectiveness and user request response.The proposed incentive algorithm can shorten the end-to-end delay by 45%,effectively control the participation degree,and control the different participation proportion according to the user’s request.In addition,the user response delay and multimedia data stream transmission delay can be reduced by 53%and 45%,respectively.