云计算环境下数字图书馆资源合理配置仿真
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摘要
云计算环境下数字图书馆资源的合理配置在提高资源合理利用方面的意义重大。对图书馆资源进行合理配置时,需要对数字图书馆资源的资源节点和资源模块进行计算。传统方法主要根据数字图书馆的资源聚类系数进行配置,忽略了资源配置时间的影响,导致出现效性差问题,提出基于粒子群算法的云计算环境下数字图书馆资源合理配置方法。利用数字图书馆资源节点的连接度和总度数来分析相连节点的概率,并通过聚类函数计算数字图书馆全部资源节点的平均值和资源配置总流程时间,分析资源配置的质量指标,建立资源配置模型,计算数字图书馆资源配置的适应度值,并利用资源配置速度向量计算资源消耗,得到资源消耗量,采用迭代次数对资源配置的模块数量进行计算,实现云计算环境下数字图书馆资源的合理配置。仿真结果表明,所提的资源配置方法具有有效性和合理性。
Traditionally, the method ignores the influence of resource allocation time, leading to the poor efficiency. This paper proposes a method for rationally allocating digital library resource in cloud computing environment based on particle swarm optimization. Firstly, the degree of connectivity and total degree of digital library resource nodes were used to analyze the probability of connected nodes. Secondly, the average value of all resource nodes in digital library and the total time of resource allocation were calculated through the clustering function. Moreover, the quality indicators of resource allocation were analyzed and the model of resource configuration was built. In addition, the fitness value of digital library resource configuration was calculated and the resource configuration speed vector was used to calculate the resource consumption, so as to obtain the resource consumption. Finally, the number of iterations was used to calculate the number of modules for resource configuration. Thus, the rational allocation of digital library resource in cloud computing environment was achieved. Simulation results show that the proposed resource allocation method is effective and reasonable.
Traditionally, the method ignores the influence of resource allocation time, leading to the poor efficiency. This paper proposes a method for rationally allocating digital library resource in cloud computing environment based on particle swarm optimization. Firstly, the degree of connectivity and total degree of digital library resource nodes were used to analyze the probability of connected nodes. Secondly, the average value of all resource nodes in digital library and the total time of resource allocation were calculated through the clustering function. Moreover, the quality indicators of resource allocation were analyzed and the model of resource configuration was built. In addition, the fitness value of digital library resource configuration was calculated and the resource configuration speed vector was used to calculate the resource consumption, so as to obtain the resource consumption. Finally, the number of iterations was used to calculate the number of modules for resource configuration. Thus, the rational allocation of digital library resource in cloud computing environment was achieved. Simulation results show that the proposed resource allocation method is effective and reasonable.
引文
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[2] 徐岩,李露. 基于高速铁路的LTE无线资源调度算法研究[J]. 铁道学报, 2016,38(9): 81-85.
[3] 张英静,等. 基于TTE的改进加权轮询调度算法[J]. 北京航空航天大学学报, 2017,43(8):1577-1584.
[4] 丛慧,等. 同步卫星转发器二维时频资源蚁群调度算法[J]. 电讯技术, 2017,57(5): 540-547.
[5] 冯璐.大型图书馆中图书质量在线评价系统设计[J].现代电子技术,2018(1):129-132.
[6] 李媛祯,等. 一种Hadoop Yarn的资源调度方法研究[J]. 电子学报, 2016,44(5): 1017-1024.
[7] 曹龙,等. 分层认知无线电网络中基于稳定匹配的资源分配算法[J]. 电子与信息学报, 2016,38(10):2605-2611.
[8] 姚恩建,等. 居住区共享泊位资源优化配置模型及算法[J]. 交通运输系统工程与信息, 2017,17(2):160-167.
[9] 顾炜江. 物联网中共享资源数据调度方法的研究[J]. 计算机仿真, 2017,34(1): 268-271.
[10] 崔建明,刘佳祎,杨呈永. 基于优先排队论网络延迟云计算资源调度算法[J]. 桂林理工大学学报, 2017, 37(2):360-365.