{"title":"ICE:用于云服务中干扰缓解的集成配置引擎","authors":"A. Maji, S. Mitra, S. Bagchi","doi":"10.1109/ICAC.2015.48","DOIUrl":null,"url":null,"abstract":"Performance degradation due to imperfect isolation of hardware resources such as cache, network, and I/O has been a frequent occurrence in public cloud platforms. A web server that is suffering from performance interference degrades interactive user experience and results in lost revenues. Existing work on interference mitigation tries to address this problem by intrusive changes to the hyper visor, e.g., Using intelligent schedulers or live migration, many of which are available only to infrastructure providers and not end consumers. In this paper, we present a framework for administering web server clusters where effects of interference can be reduced by intelligent reconfiguration. Our controller, ICE, improves web server performance during interference by performing two-fold autonomous reconfigurations. First, it reconfigures the load balancer at the ingress point of the server cluster and thus reduces load on the impacted server. ICE then reconfigures the middleware at the impacted server to reduce its load even further. We implement and evaluate ICE on Cloud Suite, a popular web application benchmark, and with two popular load balancers - HA Proxy and LVS. Our experiments in a private cloud test bed show that ICE can improve median response time of web servers by up to 94% compared to astatically configured server cluster. ICE also outperforms an adaptive load balancer (using least connection scheduling) by up to 39%.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"61 1","pages":"91-100"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":"{\"title\":\"ICE: An Integrated Configuration Engine for Interference Mitigation in Cloud Services\",\"authors\":\"A. Maji, S. Mitra, S. Bagchi\",\"doi\":\"10.1109/ICAC.2015.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Performance degradation due to imperfect isolation of hardware resources such as cache, network, and I/O has been a frequent occurrence in public cloud platforms. A web server that is suffering from performance interference degrades interactive user experience and results in lost revenues. Existing work on interference mitigation tries to address this problem by intrusive changes to the hyper visor, e.g., Using intelligent schedulers or live migration, many of which are available only to infrastructure providers and not end consumers. In this paper, we present a framework for administering web server clusters where effects of interference can be reduced by intelligent reconfiguration. Our controller, ICE, improves web server performance during interference by performing two-fold autonomous reconfigurations. First, it reconfigures the load balancer at the ingress point of the server cluster and thus reduces load on the impacted server. ICE then reconfigures the middleware at the impacted server to reduce its load even further. We implement and evaluate ICE on Cloud Suite, a popular web application benchmark, and with two popular load balancers - HA Proxy and LVS. Our experiments in a private cloud test bed show that ICE can improve median response time of web servers by up to 94% compared to astatically configured server cluster. ICE also outperforms an adaptive load balancer (using least connection scheduling) by up to 39%.\",\"PeriodicalId\":6643,\"journal\":{\"name\":\"2015 IEEE International Conference on Autonomic Computing\",\"volume\":\"61 1\",\"pages\":\"91-100\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"34\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Autonomic Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAC.2015.48\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Autonomic Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAC.2015.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ICE: An Integrated Configuration Engine for Interference Mitigation in Cloud Services
Performance degradation due to imperfect isolation of hardware resources such as cache, network, and I/O has been a frequent occurrence in public cloud platforms. A web server that is suffering from performance interference degrades interactive user experience and results in lost revenues. Existing work on interference mitigation tries to address this problem by intrusive changes to the hyper visor, e.g., Using intelligent schedulers or live migration, many of which are available only to infrastructure providers and not end consumers. In this paper, we present a framework for administering web server clusters where effects of interference can be reduced by intelligent reconfiguration. Our controller, ICE, improves web server performance during interference by performing two-fold autonomous reconfigurations. First, it reconfigures the load balancer at the ingress point of the server cluster and thus reduces load on the impacted server. ICE then reconfigures the middleware at the impacted server to reduce its load even further. We implement and evaluate ICE on Cloud Suite, a popular web application benchmark, and with two popular load balancers - HA Proxy and LVS. Our experiments in a private cloud test bed show that ICE can improve median response time of web servers by up to 94% compared to astatically configured server cluster. ICE also outperforms an adaptive load balancer (using least connection scheduling) by up to 39%.