计算机科学 ›› 2025, Vol. 52 ›› Issue (6): 346-354.doi: 10.11896/jsjkx.240900154
周凯, 王凯, 朱宇航, 普黎明, 刘树新, 周德强
ZHOU Kai, WANG Kai, ZHU Yuhang, PU Liming, LIU Shuxin, ZHOU Deqiang
摘要: 在云计算环境中,随着容器数量和类型的不断增加,资源管理和调度复杂性也增加,如何有效地调度容器,优化资源利用率和集群性能成为一个重要的研究课题。现有的容器集群调度策略没有充分考虑容器的多样化需求,缺乏灵活性,难以实现针对不同场景的容器进行定制化调度,容易出现集群资源利用率低下、集群资源负载失衡等问题。为了满足容器多样化需求,提高集群资源负载均衡性,提出了一种基于GMM(高斯混合模型)的容器定制化调度策略(Customized Container Scheduling Strategy Based on GMM,CS-GMM)。首先,根据容器的资源和属性需求进行分类,将其划分为不同的类型。其次,对于每一类容器,分别计算并分配不同的独立权重,依次将容器根据其类型调度到合适的节点,从而实现定制化调度。通过这种方式,满足了容器多样化需求,使不同类型的容器可以根据其特定需求得到最优的资源配置,避免了资源竞争和冲突,从而提高了集群资源的整体利用率和负载均衡度。实验结果表明,与Kubernetes Scheduler相比,该调度策略在多种容器调度场景下均表现出优越的性能,集群节点之间最大资源利用率差值降低17.1%,容器调度成功率提升19%,集群节点负载均衡度提升57.51%。
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