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1. 发明授权

US08684802B1 Method and apparatus for balancing thermal variations across a set of computer systems 有权
标题翻译：用于平衡一组计算机系统的热变化的方法和装置
公开(公告)号：US08684802B1
公开(公告)日：2014-04-01
申请号：US11588788
申请日：2006-10-27
申请人： Kenny C. Gross , Keith A. Whisnant , Ramakrishna C. Dhanekula , Steven F. Zwinger
发明人： Kenny C. Gross , Keith A. Whisnant , Ramakrishna C. Dhanekula , Steven F. Zwinger
IPC分类号： H05K7/20 , G05B13/00
CPC分类号： H05K7/20836 , G06F1/206
摘要： A system that balances thermal variations within a set of computer systems in a datacenter. During operation, the system obtains a thermal flux map for the set of computer systems. The system then analyzes the thermal flux map to determine whether imbalances exist in the thermal flux across the set of computer systems. If so, the system can adjust: (1) the scheduling of loads across the set of computer systems, and/or (2) air conditioning within the datacenter, so that the thermal flux is more balanced across the set of computer systems.
摘要翻译：一种平衡数据中心内的一组计算机系统内的热变化的系统。在操作期间，系统获得该组计算机系统的热通量图。然后，该系统分析热通量图，以确定跨越该组计算机系统的热通量中是否存在不平衡。如果是这样，系统可以调整：（1）跨计算机系统集中的负载调度，和/或（2）数据中心内的空调，以使整个计算机系统的热通量更加平衡。

2. 发明申请

US20090099821A1 MODEL-DIVERSITY TECHNIQUE FOR IMPROVED PROACTIVE FAULT MONITORING 有权
标题翻译：用于改进的主动故障监测的模型多样性技术
公开(公告)号：US20090099821A1
公开(公告)日：2009-04-16
申请号：US11871365
申请日：2007-10-12
申请人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
发明人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
IPC分类号： G06G7/48
CPC分类号： G06F11/008
摘要： A computer system to predict a value of a signal from a sensor schedule loads across a set of processor cores is described. During operation, the computer system generates N models to predict the value of the signal based on a set of quantized telemetry signals, where a given model produces a value of the signal using a subset of the set of quantized telemetry signals, and where the subset is selected from the set of quantized telemetry signals based on an objective criterion. Next, the computer system predicts the value of the signal by aggregating the values produced by the N models.
摘要翻译：描述了一种用于预测来自传感器计划的信号的值在一组处理器核心之间的计算机系统。在操作期间，计算机系统产生N个模型以基于一组量化遥测信号预测信号的值，其中给定模型使用量化的遥测信号集合的子集产生信号的值，并且其中子集基于客观标准从该组量化遥测信号中选出。接下来，计算机系统通过聚合由N个模型产生的值来预测信号的值。

3. 发明申请

US20080001777A1 Camouflaging business-activity information in a telemetry signal through randomization 有权
标题翻译：通过随机化在遥测信号中伪装业务活动信息
公开(公告)号：US20080001777A1
公开(公告)日：2008-01-03
申请号：US11471204
申请日：2006-06-20
申请人： Kenny C. Gross , Keith A. Whisnant , Ramakrishna C. Dhanekula
发明人： Kenny C. Gross , Keith A. Whisnant , Ramakrishna C. Dhanekula
IPC分类号： G08C19/16
CPC分类号： H04L63/0428 , H04L67/125
摘要： One embodiment of the present invention provides a system that camouflages business-activity information in telemetry signals from a computer system. During operation, the system monitors telemetry signals from the computer system to obtain a time series containing a telemetry metric which provides business-activity information. Next, the system computes a serial correlation between data values in the time series. The system then determines if the computed serial correlation between the data values in the time series is above a predetermined threshold level. If so, the system performs frequency domain analysis on the time series. The system then generates artificial activity on the computer system which causes the frequency spectra of the time series to reduce the serial correlation between the data values in the time series.
摘要翻译：本发明的一个实施例提供一种从计算机系统伪装遥测信号中的业务活动信息的系统。在操作期间，系统监视来自计算机系统的遥测信号，以获得包含提供业务活动信息的遥测度量的时间序列。接下来，系统计算时间序列中的数据值之间的串行相关性。然后，系统确定所计算的时间序列中的数据值之间的串行相关性是否高于预定的阈值水平。如果是这样，系统会对时间序列进行频域分析。然后，该系统在计算机系统上产生人为活动，其导致时间序列的频谱以减少时间序列中的数据值之间的串行相关性。

4. 发明授权

US07482947B2 Camouflaging business-activity information in a telemetry signal through randomization 有权
标题翻译：通过随机化在遥测信号中伪装业务活动信息
公开(公告)号：US07482947B2
公开(公告)日：2009-01-27
申请号：US11471204
申请日：2006-06-20
申请人： Kenny C. Gross , Keith A. Whisnant , Ramakrishna C. Dhanekula
发明人： Kenny C. Gross , Keith A. Whisnant , Ramakrishna C. Dhanekula
IPC分类号： H04K3/00
CPC分类号： H04L63/0428 , H04L67/125
摘要： One embodiment of the present invention provides a system that camouflages business-activity information in telemetry signals from a computer system. During operation, the system monitors telemetry signals from the computer system to obtain a time series containing a telemetry metric which provides business-activity information. Next, the system computes a serial correlation between data values in the time series. The system then determines if the computed serial correlation between the data values in the time series is above a predetermined threshold level. If so, the system performs frequency domain analysis on the time series. The system then generates artificial activity on the computer system which causes the frequency spectra of the time series to reduce the serial correlation between the data values in the time series.
摘要翻译：本发明的一个实施例提供一种从计算机系统伪装遥测信号中的业务活动信息的系统。在操作期间，系统监视来自计算机系统的遥测信号，以获得包含提供业务活动信息的遥测度量的时间序列。接下来，系统计算时间序列中的数据值之间的串行相关性。然后，系统确定所计算的时间序列中的数据值之间的串行相关性是否高于预定的阈值水平。如果是这样，系统会对时间序列进行频域分析。然后，该系统在计算机系统上产生人为活动，其导致时间序列的频谱以减少时间序列中的数据值之间的串行相关性。

5. 发明授权

US08150655B2 Characterizing a computer system using a pattern-recognition model 有权
标题翻译：使用模式识别模型来表征计算机系统
公开(公告)号：US08150655B2
公开(公告)日：2012-04-03
申请号：US12240211
申请日：2008-09-29
申请人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
发明人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
IPC分类号： G06F11/30
CPC分类号： G06F1/206 , G06F11/0706 , G06F11/0751 , G06F11/3428 , G06F11/3476
摘要： Some embodiments of the present invention provide a system that characterizes a computer system using a pattern-recognition model. First, values for an environmental parameter are monitored from a set of sensors associated with the computer system. Then, a baseline for the environmental parameter is calculated based on the monitored values from a subset of the set of sensors. Next, the baseline is subtracted from the monitored values from sensors in the set of sensors to produce compensated values. Then, the compensated values are used as inputs to the pattern-recognition model, which produces estimates for the compensated values based on correlations between the compensated values learned during a training phase. Next, residuals are calculated by subtracting the estimates for the compensated values from the compensated values. Then, the residuals are analyzed to characterize the computer system.
摘要翻译：本发明的一些实施例提供一种表征使用模式识别模型的计算机系统的系统。首先，从与计算机系统相关联的一组传感器监测环境参数的值。然后，基于来自传感器组的子集的监视值来计算环境参数的基线。接下来，从传感器组中的传感器的监视值中减去基线，以产生补偿值。然后，补偿值被用作模式识别模型的输入，其基于在训练阶段期间学习的补偿值之间的相关性而产生对补偿值的估计。接下来，通过从补偿值中减去补偿值的估计值来计算残差。然后，分析残差以表征计算机系统。

6. 发明授权

US07912685B1 Mitigating quantization effects in computer telemetry signals 有权
标题翻译：减轻计算机遥测信号中的量化效应
公开(公告)号：US07912685B1
公开(公告)日：2011-03-22
申请号：US11656736
申请日：2007-01-22
申请人： Ramakrishna C. Dhanekula , Kenny C. Gross , Keith A. Whisnant
发明人： Ramakrishna C. Dhanekula , Kenny C. Gross , Keith A. Whisnant
IPC分类号： G06G7/48
CPC分类号： G06F11/3072 , G06F11/3006 , G06F11/3058 , G06F11/3089
摘要： A system that mitigates quantization effects in quantized telemetry signals. During operation, the system monitors a set of quantized telemetry signals. For a given quantized telemetry signal in the set of quantized telemetry signals, the system uses a set of models to generate a set of estimates for the given quantized telemetry signal from the other monitored quantized telemetry signals, wherein each model in the set of models was initialized using a different randomly selected subset of a training dataset. The system then averages the set of estimates to produce an estimated signal for the given quantized telemetry signal.
摘要翻译：一种减轻量化遥测信号量化效应的系统。在操作期间，系统监视一组量化遥测信号。对于一组量化遥测信号中的给定的量化遥测信号，系统使用一组模型来生成来自其他监测的量化遥测信号的给定量化遥测信号的一组估计，其中该组模型中的每个模型为使用训练数据集的不同随机选择的子集进行初始化。然后，系统对该组估计值进行平均，以产生给定量化遥测信号的估计信号。

7. 发明授权

US07840391B2 Model-diversity technique for improved proactive fault monitoring 有权
标题翻译：用于改进主动故障监测的模型分集技术
公开(公告)号：US07840391B2
公开(公告)日：2010-11-23
申请号：US11871365
申请日：2007-10-12
申请人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
发明人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
IPC分类号： G06F17/50 , G06F11/00
CPC分类号： G06F11/008
摘要： A computer system to predict a value of a signal from a sensor schedule loads across a set of processor cores is described. During operation, the computer system generates N models to predict the value of the signal based on a set of quantized telemetry signals, where a given model produces a value of the signal using a subset of the set of quantized telemetry signals, and where the subset is selected from the set of quantized telemetry signals based on an objective criterion. Next, the computer system predicts the value of the signal by aggregating the values produced by the N models.
摘要翻译：描述了一种用于预测来自传感器计划的信号的值在一组处理器核心之间的计算机系统。在操作期间，计算机系统产生N个模型以基于一组量化遥测信号预测信号的值，其中给定模型使用量化的遥测信号集合的子集产生信号的值，并且其中子集基于客观标准从该组量化遥测信号中选出。接下来，计算机系统通过聚合由N个模型产生的值来预测信号的值。

8. 发明申请

US20100082299A1 CHARACTERIZING A COMPUTER SYSTEM USING A PATTERN-RECOGNITION MODEL 有权
标题翻译：使用模式识别模型表征计算机系统
公开(公告)号：US20100082299A1
公开(公告)日：2010-04-01
申请号：US12240211
申请日：2008-09-29
申请人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
发明人： Ramakrishna C. Dhanekula , Keith A. Whisnant , Kenny C. Gross
IPC分类号： G06F15/00
CPC分类号： G06F1/206 , G06F11/0706 , G06F11/0751 , G06F11/3428 , G06F11/3476
摘要： Some embodiments of the present invention provide a system that characterizes a computer system using a pattern-recognition model. First, values for an environmental parameter are monitored from a set of sensors associated with the computer system. Then, a baseline for the environmental parameter is calculated based on the monitored values from a subset of the set of sensors. Next, the baseline is subtracted from the monitored values from sensors in the set of sensors to produce compensated values. Then, the compensated values are used as inputs to the pattern-recognition model, which produces estimates for the compensated values based on correlations between the compensated values learned during a training phase. Next, residuals are calculated by subtracting the estimates for the compensated values from the compensated values. Then, the residuals are analyzed to characterize the computer system.
摘要翻译：本发明的一些实施例提供一种表征使用模式识别模型的计算机系统的系统。首先，从与计算机系统相关联的一组传感器监测环境参数的值。然后，基于来自传感器组的子集的监视值来计算环境参数的基线。接下来，从传感器组中的传感器的监视值中减去基线，以产生补偿值。然后，补偿值被用作模式识别模型的输入，其基于在训练阶段期间学习的补偿值之间的相关性而产生对补偿值的估计。接下来，通过从补偿值中减去补偿值的估计值来计算残差。然后，分析残差以表征计算机系统。

9. 发明授权

US07349823B2 Using a genetic technique to optimize a regression model used for proactive fault monitoring 有权
标题翻译：使用遗传技术优化用于主动故障监测的回归模型
公开(公告)号：US07349823B2
公开(公告)日：2008-03-25
申请号：US11359672
申请日：2006-02-22
申请人： Keith A. Whisnant , Ramakrishna C. Dhanekula , Kenny C. Gross
发明人： Keith A. Whisnant , Ramakrishna C. Dhanekula , Kenny C. Gross
IPC分类号： G06F11/00
CPC分类号： G06F11/0751 , G06F11/0748
摘要： Embodiments of the present invention provides a system that optimizes a regression model which predicts a signal as a function of a set of available signals. These embodiments use a genetic technique to optimize the regression model, which involves using a portion of the sample signals used to generate each parent regression model from a pair of best-fit parent regression models to generate a child regression model. In addition, in embodiments of the present invention, the system introduces “mutations” to the set of sample signals used to create the child regression model in an attempt to create more robust child regression models during the optimization process.
摘要翻译：本发明的实施例提供了一种优化回归模型的系统，该回归模型预测作为一组可用信号的函数的信号。这些实施例使用遗传技术来优化回归模型，其包括使用用于从一对最佳拟合父回归模型生成每个父回归模型的样本信号的一部分以生成子回归模型。此外，在本发明的实施例中，系统将“突变”引入用于创建儿童回归模型的样本信号集合，以在优化过程中创建更健壮的儿童回归模型。

10. 发明授权

US07975175B2 Risk indices for enhanced throughput in computing systems 有权
标题翻译：计算系统增强吞吐量的风险指数
公开(公告)号：US07975175B2
公开(公告)日：2011-07-05
申请号：US12170239
申请日：2008-07-09
申请人： Lawrence G. Votta , Keith A. Whisnant , Kenny C. Gross
发明人： Lawrence G. Votta , Keith A. Whisnant , Kenny C. Gross
IPC分类号： G06F11/00
CPC分类号： G06F11/004 , G06F11/008 , G06F11/1438 , G06F11/2028 , G06F11/3495
摘要： Embodiments of a system that adjusts a checkpointing frequency in a distributed computing system that executes multiple jobs are described. During operation, the system receives signals associated with the operation of the computing nodes. Then, the system determines risk metrics for the computing nodes using a pattern-recognition technique to identify anomalous signals in the received signals. Next, the system adjusts a checkpointing frequency of a given checkpoint for a given computing node based on a comparison of a risk metric associated with the given computing node and a threshold, thereby implementing holistic fault tolerance, in which prediction and prevention of potential faults occurs across the distributed computing system.
摘要翻译：描述了调整执行多个作业的分布式计算系统中的检查点频率的系统的实施例。在操作期间，系统接收与计算节点的操作相关联的信号。然后，系统使用模式识别技术来确定计算节点的风险度量，以识别接收信号中的异常信号。接下来，系统基于与给定计算节点相关联的风险度量与阈值的比较来调整给定计算节点的给定检查点的检查点频率，从而实现全局容错，其中发生潜在故障的预测和预防跨越分布式计算系统。

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