{"title":"使用云上分布式服务实现的动态测量进行SLA评估","authors":"K. Ravindran, Arun Adiththan, Michael Iannelli","doi":"10.1145/2593793.2593794","DOIUrl":null,"url":null,"abstract":"Given the business mode of offering computing services to customers in a cloud setting, a major question arises: how good are the services of a cloud provider when compared to that of other providers. The paper attempts to answer the question by describing a methodology to measure the various cloud parameters (such as VM cycles and number of VM instances) at run-time and map them onto meaningful service-level attributes. The paper provides a concrete definition of the service attributes experienced by the client application: such as availability, agility, and elasticity, in terms of the underlying cloud infrastructure parameters (i.e., VM instances and network bandwidth). Since the IaaS parameters are hard to measure directly, we resort to a measurement methodology that maps the client-visible PaaS-layer service attributes onto the underlying IaaS parameters exported by the cloud provider. Our measurement methodology satisfies the requirements of cloud testing: \"stealthiness\" and \"non-intrusiveness\", while minimizing the measurement overhead.","PeriodicalId":380234,"journal":{"name":"Principles of Engineering Service-Oriented Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"SLA evaluation with on-the-fly measurements of distributed service implementation over clouds\",\"authors\":\"K. Ravindran, Arun Adiththan, Michael Iannelli\",\"doi\":\"10.1145/2593793.2593794\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given the business mode of offering computing services to customers in a cloud setting, a major question arises: how good are the services of a cloud provider when compared to that of other providers. The paper attempts to answer the question by describing a methodology to measure the various cloud parameters (such as VM cycles and number of VM instances) at run-time and map them onto meaningful service-level attributes. The paper provides a concrete definition of the service attributes experienced by the client application: such as availability, agility, and elasticity, in terms of the underlying cloud infrastructure parameters (i.e., VM instances and network bandwidth). Since the IaaS parameters are hard to measure directly, we resort to a measurement methodology that maps the client-visible PaaS-layer service attributes onto the underlying IaaS parameters exported by the cloud provider. Our measurement methodology satisfies the requirements of cloud testing: \\\"stealthiness\\\" and \\\"non-intrusiveness\\\", while minimizing the measurement overhead.\",\"PeriodicalId\":380234,\"journal\":{\"name\":\"Principles of Engineering Service-Oriented Systems\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Principles of Engineering Service-Oriented Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2593793.2593794\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Principles of Engineering Service-Oriented Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2593793.2593794","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SLA evaluation with on-the-fly measurements of distributed service implementation over clouds
Given the business mode of offering computing services to customers in a cloud setting, a major question arises: how good are the services of a cloud provider when compared to that of other providers. The paper attempts to answer the question by describing a methodology to measure the various cloud parameters (such as VM cycles and number of VM instances) at run-time and map them onto meaningful service-level attributes. The paper provides a concrete definition of the service attributes experienced by the client application: such as availability, agility, and elasticity, in terms of the underlying cloud infrastructure parameters (i.e., VM instances and network bandwidth). Since the IaaS parameters are hard to measure directly, we resort to a measurement methodology that maps the client-visible PaaS-layer service attributes onto the underlying IaaS parameters exported by the cloud provider. Our measurement methodology satisfies the requirements of cloud testing: "stealthiness" and "non-intrusiveness", while minimizing the measurement overhead.