大数据下客户请求信息快速调度仿真研究  

Simulation Research on Fast Scheduling of Customer Request Information under Big Data

作　　者：赖丹丹 张立臣[1] LAI Dan-dan;ZHANG Li-chen(School of Computers,Guangdong University of Technology,Guangzhou Guangdong 510006,China)

机构地区：[1]广东工业大学计算机学院,广东广州510006

出　　处：《计算机仿真》2018年第11期375-378,共4页Computer Simulation

摘　　要：对大数据下网络客户请求信息的高效调度,能够有效实现物理融合系统的体验质量。对客户请求信息的快速调度,通过信息素更新对调度信息进行调整,对调度信息参数进行赋值,完成大数据下客户请求信息的快速调度。传统方法建立适应度目标函数带权分量,对调度目标函数进行优化,但忽略了对调度参数的赋值,导致调度效果不理想。提出基于蚁群优化的迭代信息快速调度方法。利用迭代信息快速调度模型,给出多维服务质量迭代信息快速调度目标优化函数,对用户效用进行量化处理,对目标优化函数量化结果进行求解。采用信息素更新对迭代信息进行调整,并对调度信息参数进行赋值。对迭代信息顺序进行快速调度,以迭代信息顺序快速调度结果选取最优解以此完成迭代信息快速调度优化。实验结果表明,所提方法对迭代信息快速调度完成时间和信息请求时间较短、成本消耗较低。Efficient scheduling of network customer request information under large data can effectively achieve the quality of experience in physical fusion system. With the rapid scheduling of customer request information,the scheduling information is adjusted through the update of pheromone,and the scheduling information parameters are assigned to complete the rapid scheduling of customer request information under large data. The traditional method establishes the fitness target function with weight component to optimize the scheduling objective function,but neglects the assignment of the scheduling parameters,which leads to the poor scheduling effect. A fast iterative information scheduling method based on ant colony optimization is proposed. The iterative information fast scheduling model was used to provide the multi-dimensional quality of service quality iterative information fast scheduling objective optimization function,the user utility was quantized,the quantitative results of the target optimization function were solved,the information element updating was used to adjust the iterative information,the scheduling information parameters were assigned,and the iterative information was used. In order to achieve quick scheduling,we chose the optimal solution in order to get the optimal solution to achieve the optimal scheduling of iterative information. The experimental results show that the proposed method can shorten the completion time and information request time of the iterative information quickly,and lower the cost consumption.

关 键 词：大数据 客户请求 信息调度优化 蚁群算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TB497[自动化与计算机技术—控制科学与工程]