| 负载敏感的云任务三支聚类评分调度研究 |
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| 引用本文： | 吴俊伟,姜春茂.负载敏感的云任务三支聚类评分调度研究[J].智能系统学报,2019,14(2):316-322. |
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| 作者姓名： | 吴俊伟 姜春茂 |
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| 作者单位： | 哈尔滨师范大学 计算机科学技术与信息工程学院, 黑龙江 哈尔滨 150025 |
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| 摘 要： | 在云计算商业化的服务模式中，追求服务质量、负载均衡与经济原则的多目标优化调度。针对集群资源使用率偏低的现象，提出了三支聚类评分（three-way clustering weight，TWCW）算法，首先分析云任务的多样化需求与资源的动态特性，采用三支聚类算法对任务集合聚类划分，然后结合任务属性对类簇对象进行评分调度。基于Cloudsim实验模拟表明:相比于k-means与FCM聚类调度，三支聚类评分算法（TWCW）在任务平均响应时间与资源利用率等方面均有显著提升。
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| 关 键 词： | 云计算 优化调度 多样化需求 动态资源 三支聚类 评分调度 任务响应时间 资源使用率 |
Load-aware score scheduling of three-way clustering for cloud task |
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| WU Junwei,JIANG Chunmao.Load-aware score scheduling of three-way clustering for cloud task[J].CAAL Transactions on Intelligent Systems,2019,14(2):316-322. |
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| Authors: | WU Junwei JIANG Chunmao |
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| Affiliation: | School of Computer Science Technology and Information Engineering, Harbin Normal University, Harbin 150025, China |
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| Abstract: | A commercialized model is established for multi-objective optimization scheduling of service quality, balanced load, and economic principles in cloud computing. A three-way clustering weight (TWCW) algorithm is proposed to solve the problem of the low utilization rate of cluster resources. First, the diversified requirements of cloud tasks and the dynamic characteristics of resources are analyzed to cluster and divide the task set by the TWCW algorithm and then score scheduling by combination with task attributes. Simulation results based on Cloudsim show that compared with k-means and FCM clustering scheduling, the TWCW algorithm has significant improvements in the average task response time and resource utilization rate. |
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| Keywords: | cloud computing optimal scheduling diversified requirement dynamic resource three-way clustering scoring scheduling response time of task resource utilization rate |
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