{"title":"IaaS云内存分配诊断","authors":"R. Pfitscher, M. A. Pillon, R. Obelheiro","doi":"10.1109/SBESC.2013.18","DOIUrl":null,"url":null,"abstract":"Infrastructure-as-a-service (IaaS) clouds enable customers to allocate computing resources in a flexible manner to satisfy their needs, and pay only for the allocated resources. One of the challenges for IaaS customers is the correct provisioning of their resources. Many users end up under provisioning, hurting application performance, or over provisioning, paying for resources that are not really necessary. Memory is an essential resource for any computing system, and is frequently a performance-limiting factor in cloud environments. Our work uses monitoring to enable a cloud customer to determine if the memory allocated to his virtual machines is correctly provisioned, under provisioned, or over provisioned. Experimental results with the Xen platform demonstrate the effectiveness of the proposed approach.","PeriodicalId":359419,"journal":{"name":"2013 III Brazilian Symposium on Computing Systems Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnosing Memory Provisioning in IaaS Clouds\",\"authors\":\"R. Pfitscher, M. A. Pillon, R. Obelheiro\",\"doi\":\"10.1109/SBESC.2013.18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Infrastructure-as-a-service (IaaS) clouds enable customers to allocate computing resources in a flexible manner to satisfy their needs, and pay only for the allocated resources. One of the challenges for IaaS customers is the correct provisioning of their resources. Many users end up under provisioning, hurting application performance, or over provisioning, paying for resources that are not really necessary. Memory is an essential resource for any computing system, and is frequently a performance-limiting factor in cloud environments. Our work uses monitoring to enable a cloud customer to determine if the memory allocated to his virtual machines is correctly provisioned, under provisioned, or over provisioned. Experimental results with the Xen platform demonstrate the effectiveness of the proposed approach.\",\"PeriodicalId\":359419,\"journal\":{\"name\":\"2013 III Brazilian Symposium on Computing Systems Engineering\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 III Brazilian Symposium on Computing Systems Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SBESC.2013.18\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 III Brazilian Symposium on Computing Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBESC.2013.18","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Infrastructure-as-a-service (IaaS) clouds enable customers to allocate computing resources in a flexible manner to satisfy their needs, and pay only for the allocated resources. One of the challenges for IaaS customers is the correct provisioning of their resources. Many users end up under provisioning, hurting application performance, or over provisioning, paying for resources that are not really necessary. Memory is an essential resource for any computing system, and is frequently a performance-limiting factor in cloud environments. Our work uses monitoring to enable a cloud customer to determine if the memory allocated to his virtual machines is correctly provisioned, under provisioned, or over provisioned. Experimental results with the Xen platform demonstrate the effectiveness of the proposed approach.