基于负载预测任务的运行时间

Jingbo Yuan, Jiubin Ju, Liang Hu, Shunli Ding
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引用次数: 2

摘要

计算网格正在成为大规模分布式数据密集型应用程序的首选平台。性能测量、分析和预测在网格环境中变得越来越重要,这主要是由于资源的地理分布、异构性、动态、分布式所有权具有不同的策略和优先级、不同的负载、可靠性和可用性条件。基于性能预测的资源管理和调度可以分配更多的可用资源和调度任务,以满足用户的性能需求。资源性能包括许多因素。提出了一种处理任务运行时间的性能预测模型。该模型基于主机负载,可以在线预测任务在候选主机上的运行时间。该系统使用超过3000个随机测试用例进行评估。实验结果表明,该模型实用有效,精度较高
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of the running time of tasks based on load
The computing grid is becoming the platform of choice for large-scale distributed data-intensive applications. Performance measurement, analysis and prediction have become increasingly important in a grid environment, mainly due to resource's geographic distribution, heterogeneity, dynamic, distributed ownership with different policies and priorities, varying loads, reliability, and availability conditions. Resource management and scheduling based on performance prediction can allocate more availably resources and schedule tasks to meet user's performance requirement. Resource performance includes many factors. A performance prediction model is put forwards to deal with task running times. The model is based on host load and can online predict the running time of tasks on candidate hosts. The system is evaluated using over 3000 randomized test cases. The experimental result shows that the model is practical and effective and its precision is preferable
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