An energy and deadline aware resource provisioning, scheduling and optimization framework for cloud systems

Yue Gao, Yanzhi Wang, S. Gupta, Massoud Pedram
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引用次数: 87

Abstract

Cloud computing has attracted significant attention due to the increasing demand for low-cost, high performance, and energy-efficient computing. Profit maximization for the cloud service provider (CSP) is a key objective in the large-scale, heterogeneous, and multi-user environment of a cloud system. This paper addresses the problem of minimizing the operation cost of a cloud system by maximizing its energy efficiency while ensuring that user deadlines as defined in Service Level Agreements are met. The workload in the cloud system can be modeled as independent batch requests or as task graphs with dependencies. This paper adopts the latter modeling approach, which provides more opportunities for energy and performance optimizations, thus enabling the CSP to meet user deadlines at lower operation costs. However, these optimizations require additional supporting efforts e.g., resource provisioning, virtual machine placement, and task scheduling, which are addressed in a holistic manner in the proposed framework. In the envisioned cloud environment, users can construct their own services and applications based on the available set of virtual machines, but are relieved from the burden of resource provisioning and task scheduling. The CSP will then exploit data parallelism in user workloads to create an energy and deadline-aware cloud platform.
云系统的能源和截止日期感知资源配置,调度和优化框架
由于对低成本、高性能和节能计算的需求不断增加,云计算引起了极大的关注。在云系统的大规模、异构和多用户环境中,云服务提供商(CSP)的利润最大化是关键目标。本文解决了通过最大化其能源效率来最小化云系统运营成本的问题,同时确保满足服务水平协议中定义的用户期限。云系统中的工作负载可以建模为独立的批处理请求或具有依赖关系的任务图。本文采用后一种建模方法,为能源和性能优化提供了更多的机会,从而使CSP能够以更低的运营成本满足用户的最后期限。然而,这些优化需要额外的支持工作,例如,资源供应、虚拟机放置和任务调度,这些都在建议的框架中以整体的方式解决。在设想的云环境中,用户可以基于可用的虚拟机集构建自己的服务和应用程序,但不必承担资源供应和任务调度的负担。然后,CSP将利用用户工作负载中的数据并行性来创建能源和截止日期感知云平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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