{"title":"Billing system CPU time on individual VM","authors":"Boris Teabe, A. Tchana, D. Hagimont","doi":"10.1109/CCGrid.2016.76","DOIUrl":null,"url":null,"abstract":"In virtualized cloud hosting centers, a virtual machine (VM) is generally allocated a fixed computing capacity. The virtualization system schedules the VMs and guarantees that each VM capacity is provided and respected. However, a significant amount of CPU time is consumed by the underlying virtualization system, which generally includes device drivers (mainly network and disk drivers). In today's virtualization systems, this CPU time consumed is difficult to monitor and it is not charged to VMs. Such a situation can have important consequences for both clients and provider: performance isolation and predictability for the former and resource management (and especially consolidation) for the latter. In this paper, we propose a virtualization system mechanism which allows estimating the CPU time used by the virtualization system on behalf of VMs. Subsequently, this CPU time is charged to VMs, thus removing the two previous side effects. This mechanism has been implemented in Xen. Its benefits have been evaluated using reference benchmarks.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGrid.2016.76","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In virtualized cloud hosting centers, a virtual machine (VM) is generally allocated a fixed computing capacity. The virtualization system schedules the VMs and guarantees that each VM capacity is provided and respected. However, a significant amount of CPU time is consumed by the underlying virtualization system, which generally includes device drivers (mainly network and disk drivers). In today's virtualization systems, this CPU time consumed is difficult to monitor and it is not charged to VMs. Such a situation can have important consequences for both clients and provider: performance isolation and predictability for the former and resource management (and especially consolidation) for the latter. In this paper, we propose a virtualization system mechanism which allows estimating the CPU time used by the virtualization system on behalf of VMs. Subsequently, this CPU time is charged to VMs, thus removing the two previous side effects. This mechanism has been implemented in Xen. Its benefits have been evaluated using reference benchmarks.