{"title":"迈向一个全面的虚拟机动态迁移性能模型","authors":"Senthil Nathan, U. Bellur, Purushottam Kulkarni","doi":"10.1145/2806777.2806838","DOIUrl":null,"url":null,"abstract":"Although many models exist to predict the time taken to migrate a virtual machine from one physical machine to another, our empirical validation of these models has shown the 90th percentile error to be 46% (43 secs) and 159% (112 secs) for KVM and Xen live migration, respectively. Our analysis reveals that these models are fundamentally flawed as they all fail to take into account the following three critical parameters: (i) the writable working set size, (ii) the number of pages eligible for the skip technique, (iii) the relation of the number of skipped pages with the page dirty rate and the page transfer rate, and incorrectly model the key parameter---the number of new pages dirtied per unit time. In this paper, we propose a novel model that takes all these parameters into account. We present a thorough validation with 53 workloads and show that the 90th percentile error in the estimated migration times is only 12% (8 secs) and 19% (14 secs) for KVM and Xen live migration, respectively.","PeriodicalId":275158,"journal":{"name":"Proceedings of the Sixth ACM Symposium on Cloud Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"54","resultStr":"{\"title\":\"Towards a comprehensive performance model of virtual machine live migration\",\"authors\":\"Senthil Nathan, U. Bellur, Purushottam Kulkarni\",\"doi\":\"10.1145/2806777.2806838\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Although many models exist to predict the time taken to migrate a virtual machine from one physical machine to another, our empirical validation of these models has shown the 90th percentile error to be 46% (43 secs) and 159% (112 secs) for KVM and Xen live migration, respectively. Our analysis reveals that these models are fundamentally flawed as they all fail to take into account the following three critical parameters: (i) the writable working set size, (ii) the number of pages eligible for the skip technique, (iii) the relation of the number of skipped pages with the page dirty rate and the page transfer rate, and incorrectly model the key parameter---the number of new pages dirtied per unit time. In this paper, we propose a novel model that takes all these parameters into account. We present a thorough validation with 53 workloads and show that the 90th percentile error in the estimated migration times is only 12% (8 secs) and 19% (14 secs) for KVM and Xen live migration, respectively.\",\"PeriodicalId\":275158,\"journal\":{\"name\":\"Proceedings of the Sixth ACM Symposium on Cloud Computing\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"54\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Sixth ACM Symposium on Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2806777.2806838\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth ACM Symposium on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2806777.2806838","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards a comprehensive performance model of virtual machine live migration
Although many models exist to predict the time taken to migrate a virtual machine from one physical machine to another, our empirical validation of these models has shown the 90th percentile error to be 46% (43 secs) and 159% (112 secs) for KVM and Xen live migration, respectively. Our analysis reveals that these models are fundamentally flawed as they all fail to take into account the following three critical parameters: (i) the writable working set size, (ii) the number of pages eligible for the skip technique, (iii) the relation of the number of skipped pages with the page dirty rate and the page transfer rate, and incorrectly model the key parameter---the number of new pages dirtied per unit time. In this paper, we propose a novel model that takes all these parameters into account. We present a thorough validation with 53 workloads and show that the 90th percentile error in the estimated migration times is only 12% (8 secs) and 19% (14 secs) for KVM and Xen live migration, respectively.