Scalable and efficient workload hotspot detection in virtualized environment
作者: Zhou LeiBolin HuJianhua GuoLuokai HuWenfeng ShenYu Lei
作者单位: 1School of Computer Engineering and Science, Shanghai University
2School of Computer, Hubei University of Education
3Department of Computer Science and Engineering, The University of Texas at Arlington
刊名: Cluster Computing, 2014, Vol.17 (4), pp.1253-1264
来源数据库: Springer Nature Journal
DOI: 10.1007/s10586-014-0383-y
关键词: Resource monitoringMemory usage monitoringWorkload computingHotspot detectionVirtualizationMapReduce
英文摘要: Abstract(#br)Workload hotspot detection is a key component of virtual machine (VM) management in virtualized environment. One of its challenges is how to effectively collect the resource usage of VMs. Also, since data centers usually have hundreds or even thousands of nodes, workload hotspot detection must be able to handle a large amount of monitoring data. In this paper, we address these two challenges. We first present a novel approach to VM memory monitoring. This approach collects memory usage data by walking through the page tables of VMs and by checking the present bit of page table entry. Second, we present a MapReduce-based approach to efficiently analyze a large amount of resource usage data of VMs and nodes. Leveraging the power of parallelism and robustness of MapReduce can...
全文获取路径: Springer Nature  (合作)
影响因子:0.776 (2012)

  • virtualized 虚拟化
  • workload 工作量
  • efficient 有用的
  • hotspot 热点
  • detection 探测
  • environment 环境