一种多云环境的资源及应用监控方法SEPQMS
发布时间：2018-11-23 11:14
【摘要】：资源及应用监控是云资源规划调度、弹性提供、服务质量评价等的前提.基于多云监控需求,提出了一种可扩展、适应资源弹性、平台独立并提供传输质量控制的多云监控方法.采用以插件方式安装指标探测器的监控代理,实施对资源及应用相关指标的收集.遵循对象管理组织的数据分发服务标准规范,设计了多云环境的发布/订阅式监控数据分发模型框架.原型系统实验表明:本方法只引入了较小的监控开销,能够跨平台实施弹性的多云监控,按需订制监控指标,动态部署和自治管理监控代理适应监控资源增减和迁移,并能按需控制监控数据传输质量.
[Abstract]:Resource and application monitoring is the premise of cloud resource planning and scheduling, flexible provision, quality of service evaluation and so on. Based on the requirement of cloud monitoring, an extensible, flexible, platform independent and transmission quality control method is proposed. Monitor agent with plug-in to install indicator detector, implement collection of resource and application related index. In accordance with the standard specification of data distribution service of object management organization, a publish / subscribe monitoring data distribution model framework for cloudy environment is designed. The experiment of prototype system shows that the method only introduces small monitoring overhead, and can implement flexible cloud monitoring across platforms. The dynamic deployment and autonomous management monitoring agent can adapt to the increase, decrease and migration of monitoring resources. And can control the quality of monitoring data transmission on demand.
【作者单位】： 解放军理工大学指挥信息系统学院;牡丹江医学院教育技术与信息中心;
【基金】：江苏省自然科学基金项目(BK20131069)
【分类号】：TP277;TP393.09
[Abstract]:Resource and application monitoring is the premise of cloud resource planning and scheduling, flexible provision, quality of service evaluation and so on. Based on the requirement of cloud monitoring, an extensible, flexible, platform independent and transmission quality control method is proposed. Monitor agent with plug-in to install indicator detector, implement collection of resource and application related index. In accordance with the standard specification of data distribution service of object management organization, a publish / subscribe monitoring data distribution model framework for cloudy environment is designed. The experiment of prototype system shows that the method only introduces small monitoring overhead, and can implement flexible cloud monitoring across platforms. The dynamic deployment and autonomous management monitoring agent can adapt to the increase, decrease and migration of monitoring resources. And can control the quality of monitoring data transmission on demand.
【作者单位】： 解放军理工大学指挥信息系统学院;牡丹江医学院教育技术与信息中心;
【基金】：江苏省自然科学基金项目(BK20131069)
【分类号】：TP277;TP393.09
【参考文献】
相关期刊论文 前2条
1 蔡宏果;元昌安;罗锦光;张增银;石亚冰;;基于server session约束的序列模式增长挖掘研究[J];郑州大学学报(理学版);2010年01期
2 杨明辉,郭肇德;基于扩展的BNF文法的通用语法分析算法[J];软件学报;1992年03期
【共引文献】
相关期刊论文 前3条
1 朱华e，
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