云的“时间”到了?基于时间的云资源管理系统的设计与实现

R. Ko, Yu Shyang Tan, Grace P. Y. Ng
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引用次数: 5

摘要

公共云服务提供商目前采用的按使用付费模式影响了人们对云应如何向最终用户提供资源的看法,即按需和无限量地访问资源。然而,并非所有的云都是一样的。虽然这种配置模型适用于资源丰富的公共云,但它们可能并不总是适用于预算和资源有限的私有云,如研究和教育云。私有云还会受到用户资源占用和资源滥用等问题的严重影响。这些问题通常是由以下挑战引起的:(1)有限的物理服务器/预算;(2)不断增长的用户数量;(3)无法优雅地、自动地放弃非活动用户的资源。目前,用于私有云设置的云资源管理框架,如OpenStack和CloudStack,在向用户提供资源时仅使用按使用付费模式作为基础。在本文中,我们提出了OpenStack cafeit,这是一种采用“时间”和“预订系统”概念来管理私有云资源的新方法。通过允许用户在特定时间段预订资源,我们提出的解决方案可以有效且自动地帮助管理员管理用户对资源的访问,解决资源占用问题,并在资源受限的私有云设置中优雅地将资源释放回池中。目前,将cafee作为一项功能引入OpenStack的工作正在进行中,我们的原型结果显示出了希望。在本文中,我们还提出了在设计和实施我们提出的方法过程中吸取的一些经验教训。
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'Time' for Cloud? Design and Implementation of a Time-Based Cloud Resource Management System
The current pay-per-use model adopted by public cloud service providers has influenced the perception on how a cloud should provide its resources to end-users, i.e. on-demand and access to an unlimited amount of resources. However, not all clouds are equal. While such provisioning models work for well-endowed public clouds, they may not always work well in private clouds with limited budget and resources such as research and education clouds. Private clouds also stand to be impacted greatly by issues such as user resource hogging and the misuse of resources for nefarious activities. These problems are usually caused by challenges such as (1) limited physical servers/ budget, (2) growing number of users and (3) the inability to gracefully and automatically relinquish resources from inactive users. Currently, cloud resource management frameworks used for private cloud setups, such as OpenStack and CloudStack, only uses the pay-per-use model as the basis when provisioning resources to users. In this paper, we propose OpenStack Café, a novel methodology adopting the concepts of 'time' and booking systems' to manage resources of private clouds. By allowing users to book resources over specific time-slots, our proposed solution can efficiently and automatically help administrators manage users' access to resource, addressing the issue of resource hogging and gracefully relinquish resources back to the pool in resource-constrained private cloud setups. Work is currently in progress to adopt Café into OpenStack as a feature, and results of our prototype show promises. We also present some insights to lessons learnt during the design and implementation of our proposed methodology in this paper.
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