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Energy-AwareWorkflow Scheduling in Grid Under QoS Constraints

机译:在QoS限制下网格中的能量知识工作计划

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In this study, we have considered the problem of scheduling precedence-constraint parallel applications (workflows) in heterogeneous grid-computing environment. Recently many heuristics have been devoted to grid scheduling typically restricted to optimizing the execution time (makespan) only without paying much concentration on energy consumption. Reducing energy consumption can bring various advantages like reducing operating costs, environmental perspective and increase in system reliability. This paper aims to develop energy-aware task scheduling algorithm in grid based on the dynamic voltage and frequency scaling (DVFS) technique. The user negotiates with the service provider on their quality of service (QoS) requirements along with green computing specifications to reach the service level agreement. With the use of DVFS, the algorithm minimizes the energy consumption of task execution while satisfying the QoS constraints (deadline).The proposed static scheduling algorithm works in three phases: deadline distribution, tasks ordering and then assigning the best services to tasks along with selecting the appropriate voltage levels while meeting its sub-deadline. The simulation results using randomly generated task graphs and task graphs corresponding to real-world problems exhibit that the proposed algorithm achieves energy efficiency and reduces energy consumption up to 68% with the increase in 30% of the execution time.
机译:在本研究中,我们考虑了在异构网格计算环境中调度优先级约束并行应用(工作流)的问题。最近许多启发式谱都专门用于电网调度,通常仅限于优化执行时间(MakEspan)而不支付大量集中能耗。降低能耗可以带来各种优势,如降低运营成本,环境视角和系统可靠性的增加。本文旨在基于动态电压和频率缩放(DVFS)技术在网格中开发电网中的能量感知任务调度算法。用户可以与服务提供商协商他们的服务质量(QoS)要求以及绿色计算规范,以达到服务级别协议。通过使用DVFS,该算法可以在满足QoS约束(截止日期)的同时最小化任务执行的能量消耗。建议的静态调度算法在三个阶段工作:截止日期分布,订购任务和选择的最佳服务符合其子截止日期时适当的电压电平。使用随机生成的任务图和对应于实际问题的任务图表的仿真结果表明,该算法实现了能量效率,并将能源消耗降低了68%,随着执行时间的30%增加。

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