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论文:2017,Vol:35,Issue(1):138-142 |
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引用本文： |
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刘文洁, 李战怀. 一种面向云资源调度的热点迁移策略[J]. 西北工业大学学报 |
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Liu Wenjie, Li Zhanhuai. A Hot-Spot Migration Strategy for Resource Scheduling in Cloud Environment[J]. Northwestern polytechnical university |
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| 一种面向云资源调度的热点迁移策略 |
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| 刘文洁, 李战怀 |
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| 西北工业大学 计算机学院, 陕西 西安 710072 |
| 摘要: |
| 在云环境下的大数据中心，虚拟机数目和虚拟机的负载会随用户和应用的需求而经常变化，虚拟机需要进行动态资源调整，及时移除系统中的热点资源，从而达到整个系统的负载均衡。现有的方法主要采用启发式算法计算迁移调节方案，选择CPU、内存、网络等资源的混合负载最小的机器作为迁移对象。此类方法由于没有区分资源类型，可能会导致从物理机上迁移了单一资源负载高而其他资源负载低的虚拟机。提出了一种云环境下，面向云资源调度的热点迁移方法，其特点是通过判断物理机上所承载虚拟机的CPU或内存各自的容量总和，来判断是否有热点发生，并根据对热点虚拟机迁移代价进行计算的结果来选择合适的目标物理机进行迁移。该方法可以区分不同资源种类的热点，能快速准确地找到热点虚拟机，并保证在迁移过程中代价最小，避免误迁移。 |
| 关键词:
云环境
大数据
资源调度
虚拟机迁移
代价削减
多目标优化
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| A Hot-Spot Migration Strategy for Resource Scheduling in Cloud Environment |
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| Liu Wenjie, Li Zhanhuai |
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| School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China |
| Abstract: |
| In the big data center of cloud environment, the number and load balance of virtual machines will change frequently. The resources of virtual machines should be adjusted dynamically to remove the hot-spot therefore achieve the load balance in the system. Current techniques often use heuristic methods to compute the migration measures, which select the machine whose CPU, memory, network and other resources are combined to achieve the minimum workload. As the kind of method does not distinguish the resource type, it may cause to migrate a machine whose CPU's workload is the highest and other resources' workload is very low. This paper proposed a hot-spot migration method oriented cloud resources. The method judges a hot-spot by checking the sum of all the resources workload of a virtual machine, and selects a proper physical server to migrate by computing migration cost. This kind of method can distinguish hot-spot of different resources and find the host virtual machine quickly. It can also assure the minimum migration cost and avoid the fault migration. |
| Key words:
cloud environment
big data
resource scheduling
virtual machine migration
cost reduction
multi-objective optimization
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| 收稿日期: 2016-09-08
修回日期:
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| DOI: |
| 基金项目: 国家"973"重点基础研究发展计划基金（2012CB316203）与国家自然科学基金（61303037）资助 |
| 通讯作者:
Email： |
| 作者简介: 刘文洁(1976-),女,西北工业大学副教授,主要从事云计算、大数据处理及高可用性系统等研究。
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