The statistical properties of host load
The statistical properties of host load
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DOI：
10.1155/1999/386856
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发表时间：
1999-08
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通讯作者：
P. Dinda
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文献类型：
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作者：
P. Dinda
理解主机负载如何随时间变化对于预测任务或作业的执行时间非常有帮助，例如在动态负载均衡和分布式软实时系统中。为了增进这种理解，我们在超过35台不同的机器上收集了为期一周、分辨率为1Hz的Digital Unix 5秒指数负载平均值的跟踪数据，这些机器包括生产和研究集群机器、计算服务器以及桌面工作站。在一年中的两个不同时间分别收集了不同组的跟踪数据。这些跟踪数据捕获了这些机器上用户级程序可获得的所有动态负载信息。我们在此对这些跟踪数据进行了详细的统计分析，包括汇总统计、分布以及时间序列分析结果。两个重要的新结果是负载具有自相似性并且呈现出阶段性行为。所有跟踪数据都表现出高度的自相似性，赫斯特参数范围从0.73到0.99，强烈偏向该范围的上限。这些跟踪数据还显示出阶段性行为，即负载信号的局部频率成分在很长一段时间内（平均150 - 450秒）保持相当稳定，并在阶段边界处突然变化。尽管存在这些复杂行为，我们发现相对简单的线性模型对于短期主机负载预测已经足够。
Understanding how host load changes over time is instrumental in predicting the execution time of tasks or jobs, such as in dynamic load balancing and distributed soft real-time systems. To improve this understanding, we collected week-long, 1 Hz resolution traces of the Digital Unix 5 second exponential load average on over 35 different machines including production and research cluster machines, compute servers, and desktop workstations. Separate sets of traces were collected at two different times of the year. The traces capture all of the dynamic load information available to user-level programs on these machines. We present a detailed statistical analysis of these traces here, including summary statistics, distributions, and time series analysis results. Two significant new results are that load is self-similar and that it displays epochal behavior. All of the traces exhibit a high degree of self-similarity with Hurst parameters ranging from 0.73 to 0.99, strongly biased toward the top of that range. The traces also display epochal behavior in that the local frequency content of the load signal remains quite stable for long periods of time (150-450 s mean) and changes abruptly at epoch boundaries. Despite these complex behaviors, we have found that relatively simple linear models are sufficient for short-range host load prediction.