摘要
为有效解决计算机大数据调度能耗高和访问不安全问题,提出面向云计算并发访问的计算机大数据调度负载均衡方法。在云计算部署方案下,使用正负理想解大数据全面访问机制,保证访问数据的全面性。通过约束数据需求,使得授权合法使用者能够存取获许可的数据,实现多阶段访问的身份认证,保证访问安全;构建基于云计算的调度模型,通过数据分级调度策略达到多批大数据处理最大化收益目的。构建任务执行时间和能耗双重优化函数,结合数据传输路径迭代函数,实现对计算机大数据多批处理调度。访问结果显示总隐私权重最高为16.4,调度结果显示能耗调度结果与理想结果拟合度较高,且资源利用率在96%以上,表明负载能够达到最佳均衡状态。
In order to effectively solve the problems of high energy consumption and to insecure access of computer big data scheduling,a load balancing method for computer big data scheduling for cloud computing concurrent access is proposed.Under the cloud computing deployment scheme,the positive and negative ideal solution big data comprehensive access mechanism is used to ensure the comprehensiveness of access data.By constraining data requirements,authorized legitimate users can access licensed data,achieve multi-stage access identity authentication,and ensure access security.Then,a scheduling model based on cloud computing is constructed to maximize the benefits of multi batch big data processing through data hierarchical scheduling strategy.A dual optimization function for task execution time and energy consumption is built,and the iterated function of data transmission path to achieve multi batch processing scheduling of computer big data is combined.According to the test results,the access results of this method show that the total privacy weight is the highest at 16.4.The scheduling results show that the energy consumption scheduling results have a high fit with the ideal results,and the resource utilization rate is above 96%,indicating that the load can reach the optimal balance state.
作者
王艳兵
WANG Yanbing(Department of Electronic Information,Huishang Vocational College,Hefei 230000,China)
出处
《滨州学院学报》
2023年第6期80-85,共6页
Journal of Binzhou University
基金
安徽省高校自然科学研究重点项目(2023AH053112)
安徽省高等学校省级质量工程项目(2022cjrh044,2021zyjxzyk031)。
关键词
云计算环境
计算机大数据
数据调度
调度能耗
负载均衡
cloud computing environment
computer big data
data scheduling
dispatching energy consumption
load balancing
