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Intent-driven cloud resource design framework to meet cloud performance requirements and its application to a cloud-sensor system
Journal of Cloud Computing ( IF 3.418 ) Pub Date : 2021-06-02 , DOI: 10.1186/s13677-021-00242-w
Chao Wu , Shingo Horiuchi , Kenji Murase , Hiroaki Kikushima , Kenichi Tayama

In cloud service delivery, the cloud user is concerned about “what” function and performance the cloud service could provide, while the cloud provider is concerned about “how” to design proper underlying cloud resources to meet the cloud user’s requirements. We take the cloud user’s requirement as intent and aim to translate the intent autonomously into cloud resource decisions. In recent years, intent-driven management has been a widely spread management concept which aims to close the gap between the operator’s high-level requirements and the underlying infrastructure configuration complexity. Intent-driven management has drawn attention from telecommunication industries, standards organizations, the open source software community and academic research. There are various application of intent-driven management which are being studied and implemented, including intent-driven Software Defined Network (SDN), intent-driven wireless network configuration, etc. However, application of intent-driven management into the cloud domain, especially the translation of cloud performance-related intent into the amount of cloud resource, has not been addressed by existing studies. In this work, we have proposed an Intent-based Cloud Service Management (ICSM) framework, and focused on realizing the RDF (Resource Design Function) to translate cloud performance-related intent into concrete cloud computation resource amount settings that are able to meet the intended performance requirement. Furthermore, we have also proposed an intent breach prevention mechanism, P-mode, which is essential for commercial cloud service delivery. We have validated the proposals in a sensor-cloud system, designed to meet the user’s intent to process a large quantity of images collected by the sensors in a restricted time interval. The validation results show that the framework achieved 88.93 ~ 90.63% precision for performance inference, and exceeds the conventional resource approach in the aspects of human cost, time cost and design results. Furthermore, the intent breach prevention mechanism P-mode significantly reduced the breach risk, at the same time keeping a high level of precision.

中文翻译:

满足云性能需求的意图驱动的云资源设计框架及其在云传感器系统中的应用

在云服务交付中,云用户关心的是云服务可以提供“什么”功能和性能,而云提供商关心的是“如何”设计合适的底层云资源以满足云用户的需求。我们以云用户的需求为意图,旨在自主地将意图转化为云资源决策。近年来,意图驱动管理已成为一种广泛传播的管理概念,旨在缩小运营商的高层需求与底层基础设施配置复杂性之间的差距。意图驱动的管理已经引起了电信行业、标准组织、开源软件社区和学术研究的关注。意图驱动管理的各种应用正在研究和实施中,包括意图驱动的软件定义网络(SDN)、意图驱动的无线网络配置等。 然而,意图驱动管理在云领域的应用,特别是现有研究尚未解决将与云性能相关的意图转化为云资源量的问题。在这项工作中,我们提出了一个基于意图的云服务管理(ICSM)框架,并专注于实现 RDF(资源设计功能)将与云性能相关的意图转化为能够满足云计算资源量设置的具体云计算资源量设置。预期的性能要求。此外,我们还提出了一种意图破坏预防机制,P-mode,这对于商业云服务交付至关重要。我们已经在传感器云系统中验证了这些提议,该系统旨在满足用户在有限的时间间隔内处理传感器收集的大量图像的意图。验证结果表明,该框架实现了88.93~90.63%的性能推理精度,在人力成本、时间成本和设计效果等方面均超过了常规资源方法。此外,意图泄露预防机制P-mode显着降低了泄露风险,同时保持了较高的精确度。验证结果表明,该框架实现了88.93~90.63%的性能推理精度,在人力成本、时间成本和设计效果等方面均超过了常规资源方法。此外,意图泄露预防机制P-mode显着降低了泄露风险,同时保持了较高的精确度。验证结果表明,该框架实现了88.93~90.63%的性能推理精度,在人力成本、时间成本和设计效果等方面均超过了常规资源方法。此外,意图泄露预防机制P-mode显着降低了泄露风险,同时保持了较高的精确度。
更新日期:2021-06-02
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