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ACCRS: autonomic based cloud computing resource scaling

机译:accrs:基于自动的云计算资源缩放

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A cloud computing model gives cloud service providers the ability to retain multiple workloads on a single physical system. However, efficient resource provisioning and possible system fault management in the cloud can be a challenge. Early fault detection can provide room to recover from potential faults before impacting QoS. Current static techniques of fault management in computing systems are not satisfactory enough to safeguard the QoS requested by cloud users. Thus, new smart techniques are needed. This paper presents the ACCRS framework for cloud computing infrastructures to advance system's utilization level, reduce cost and power consumption and fulfil SLAs. The ACCRS framework employs Autonomic Computing basic components which includes state monitoring, planning, decision making, fault predication, detection, and root cause analysis for recovery actions to improve system's reliability, availability, and utilization level by scaling resources in response to changes in the cloud system state.
机译:云计算模型使云服务提供商能够在单个物理系统上保留多个工作负载。但是,云中有效的资源供应和可能的系统故障管理可能是一个挑战。早期故障检测可以在影响QoS之前提供从潜在故障中恢复的空间。计算系统中故障管理的当前静态技术不足以保护云用户请求的QoS。因此,需要新的智能技术。本文介绍了云计算基础架构的ACCR框架,以推进系统的利用率,降低成本和功耗并实现SLA。 ACCRS框架采用自主计算基本组件,包括状态监控,规划,决策,故障预测,检测和根本原因分析,以提高系统的可靠性,可用性和利用率级别,以响应云中的更改来缩放资源系统状态。

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