G. Engelbrecht, J. Bisbal, S. Benkner, Alejandro F Frangi
{"title":"为生物医学数据服务提供可协商的基于sla的QoS支持","authors":"G. Engelbrecht, J. Bisbal, S. Benkner, Alejandro F Frangi","doi":"10.1109/GRID.2010.5697972","DOIUrl":null,"url":null,"abstract":"Researchers in data intensive domains, like the Virtual Physiological Human initiative (VPH-I), are commonly overwhelmed with the vast and increasing amount of data available. Advanced studies in biomedicine and other domains often require a considerable amount of effort to achieve data access to a critical mass of relevant data to analyze the problem at hand. We aim to improve this situation and propose a novel application of Quality of Service (QoS) mechanisms for data services. This enables scientists to obtain exactly the data they require, rather than being spoilt for choice which data source might comprise suitable data. The proposed QoS support includes a negotiation model based on service level agreements (SLAs), which in turn comprises data-related service level objectives (SLOs) to express the required guarantees about the quantity or quality of data. Moreover a corresponding QoS management model is presented which resolves the complex process of the SLA generation within data access and data mediation services. The benefits of this approach are materialized in the context of the @neurIST data environment and an initial experimental evaluation demonstrates promising performance improvements in a real world scenario.","PeriodicalId":6372,"journal":{"name":"2010 11th IEEE/ACM International Conference on Grid Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Towards negotiable SLA-based QoS support for biomedical data services\",\"authors\":\"G. Engelbrecht, J. Bisbal, S. Benkner, Alejandro F Frangi\",\"doi\":\"10.1109/GRID.2010.5697972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Researchers in data intensive domains, like the Virtual Physiological Human initiative (VPH-I), are commonly overwhelmed with the vast and increasing amount of data available. Advanced studies in biomedicine and other domains often require a considerable amount of effort to achieve data access to a critical mass of relevant data to analyze the problem at hand. We aim to improve this situation and propose a novel application of Quality of Service (QoS) mechanisms for data services. This enables scientists to obtain exactly the data they require, rather than being spoilt for choice which data source might comprise suitable data. The proposed QoS support includes a negotiation model based on service level agreements (SLAs), which in turn comprises data-related service level objectives (SLOs) to express the required guarantees about the quantity or quality of data. Moreover a corresponding QoS management model is presented which resolves the complex process of the SLA generation within data access and data mediation services. The benefits of this approach are materialized in the context of the @neurIST data environment and an initial experimental evaluation demonstrates promising performance improvements in a real world scenario.\",\"PeriodicalId\":6372,\"journal\":{\"name\":\"2010 11th IEEE/ACM International Conference on Grid Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 11th IEEE/ACM International Conference on Grid Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GRID.2010.5697972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 11th IEEE/ACM International Conference on Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GRID.2010.5697972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
摘要
数据密集型领域的研究人员,如虚拟生理人计划(Virtual Physiological Human initiative, VPH-I),通常被大量不断增加的可用数据所淹没。生物医学和其他领域的高级研究往往需要付出相当大的努力,才能获得关键数量的相关数据,以分析手头的问题。我们的目标是改善这种情况,并提出了一种新的数据服务质量(QoS)机制的应用。这使科学家能够准确地获得他们需要的数据,而不是被选择哪个数据源可能包含合适的数据所困扰。建议的QoS支持包括一个基于服务水平协议(sla)的协商模型,该模型又由与数据相关的服务水平目标(slo)组成,以表示对数据数量或质量的所需保证。提出了相应的QoS管理模型,解决了数据访问和数据中介服务中SLA生成的复杂过程。这种方法的好处在@neurIST数据环境中得到了体现,初步的实验评估表明,在现实世界的场景中,这种方法的性能有了很大的提高。
Towards negotiable SLA-based QoS support for biomedical data services
Researchers in data intensive domains, like the Virtual Physiological Human initiative (VPH-I), are commonly overwhelmed with the vast and increasing amount of data available. Advanced studies in biomedicine and other domains often require a considerable amount of effort to achieve data access to a critical mass of relevant data to analyze the problem at hand. We aim to improve this situation and propose a novel application of Quality of Service (QoS) mechanisms for data services. This enables scientists to obtain exactly the data they require, rather than being spoilt for choice which data source might comprise suitable data. The proposed QoS support includes a negotiation model based on service level agreements (SLAs), which in turn comprises data-related service level objectives (SLOs) to express the required guarantees about the quantity or quality of data. Moreover a corresponding QoS management model is presented which resolves the complex process of the SLA generation within data access and data mediation services. The benefits of this approach are materialized in the context of the @neurIST data environment and an initial experimental evaluation demonstrates promising performance improvements in a real world scenario.