面向云计算环境的上下文感知作业调度

M. Assunção, M. Netto, F. Koch, S. Bianchi
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引用次数: 30

摘要

越来越仪表化的社会需要更智能的服务来帮助协调日常活动和特殊情况。随着技术的普及,应用程序变得复杂并具有上下文感知能力。为了应对基于移动环境的资源限制,将处理密集型组件委托给云计算基础设施是一种常见的做法。在此场景中,基于服务器的作业的执行仍然依赖于最终用户上下文的本地变化。我们声称需要一种高级的智能服务模型,它结合了上下文感知技术和自适应作业调度技术。该模型旨在使云计算环境中的资源利用合理化,同时显著提高服务质量。在本文中,我们介绍了这样一个模型,并通过结合社会和服务模拟描述了它的性能优势。我们通过展示在性能、服务质量、减少浪费的工作和改善整体终端用户体验方面的收益来分析结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Context-Aware Job Scheduling for Cloud Computing Environments
The more instrumented society is demanding smarter services to help coordinate daily activities and exceptional situations. Applications become sophisticated and context-aware as the pervasiveness of technology increases. In order to cope with resource limitations of mobile-based environments, it is a common practice to delegate processing intensive components to a Cloud Computing infrastructure. In this scenario, executions of server-based jobs are still dependent on the local variations of the end-user context. We claim that there is a need for an advanced model for smarter services that combines techniques of context awareness and adaptive job scheduling. This model aims at rationalising the resource utilisation in a Cloud Computing environment, while leading to significant improvement of quality of service. In this paper, we introduce such a model and describe its performance benefits through a combination of social and service simulations. We analyse the results by demonstrating gains in performance, quality of service, reduction of wasted jobs, and improvement of overall end-user experience.
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