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1. 发明授权

US07673191B2 Baselining backend component error rate to determine application performance 有权
标题翻译：基于后端组件的错误率来确定应用程序性能
公开(公告)号：US07673191B2
公开(公告)日：2010-03-02
申请号：US11559755
申请日：2006-11-14
申请人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
发明人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
IPC分类号： G06F11/00
CPC分类号： G06F11/076 , G06F11/0709 , G06F11/0748 , G06F11/2294 , G06F11/3419 , G06F11/3447 , G06F11/3495 , G06F2201/87
摘要： Deviation of an expected error rate for a backend server invoked by an application to process a request is used to characterize the backend server health. Performance data generated in response to monitoring application execution is processed to select backend error rate data. The selected data is processed to predict future values of a time series associated with backend error rates. The predicted error rate values are compared to actual error rate values in the time series to determine a deviation from the predicted value. Deviation information for the time series data of error rates is then reported to a user through an interface in a simplified manner.
摘要翻译：由应用程序调用以处理请求的后端服务器的预期错误率的偏差用于表征后端服务器运行状况。响应于监视应用执行而生成的性能数据被处理以选择后端错误率数据。处理所选数据以预测与后端错误率相关联的时间序列的未来值。将预测误差率值与时间序列中的实际误差率值进行比较，以确定与预测值的偏差。然后以简化的方式通过界面将错误率的时间序列数据的偏差信息报告给用户。

2. 发明授权

US07676706B2 Baselining backend component response time to determine application performance 有权
标题翻译：基于后端组件的响应时间来确定应用程序性能
公开(公告)号：US07676706B2
公开(公告)日：2010-03-09
申请号：US11559750
申请日：2006-11-14
申请人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
发明人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
IPC分类号： G06F11/00
CPC分类号： G06F11/3447 , G06F11/3419 , G06F2201/88
摘要： Deviation of expected response times is used to characterize the health of one or more backend machines invoked by an application to process a request. Performance data generated in response to monitoring application execution is processed to select backend response time data. The selected data is processed to predict future values of a time series associated with backend response time. The predicted response time values are compared to actual response time values in the time series to determine a deviation from the predicted value. Deviation information for the time series data of response times is then reported to a user through an interface in a simple manner.
摘要翻译：预期响应时间的偏差用于表征应用程序调用以处理请求的一个或多个后端机器的运行状况。响应于监视应用执行而生成的性能数据被处理以选择后端响应时间数据。所选择的数据被处理以预测与后端响应时间相关联的时间序列的未来值。将预测的响应时间值与时间序列中的实际响应时间值进行比较，以确定与预测值的偏差。响应时间的时间序列数据的偏差信息则以简单的方式通过接口向用户报告。

3. 发明申请

US20080126413A1 BASELINING BACKEND COMPONENT ERROR RATE TO DETERMINE APPLICATION PERFORMANCE 有权
标题翻译：基线后端组件错误率来确定应用性能
公开(公告)号：US20080126413A1
公开(公告)日：2008-05-29
申请号：US11559755
申请日：2006-11-14
申请人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
发明人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
IPC分类号： G06F17/30
CPC分类号： G06F11/076 , G06F11/0709 , G06F11/0748 , G06F11/2294 , G06F11/3419 , G06F11/3447 , G06F11/3495 , G06F2201/87
摘要： Deviation of an expected error rate for a backend server invoked by an application to process a request is used to characterize the backend server health. Performance data generated in response to monitoring application execution is processed to select backend error rate data. The selected data is processed to predict future values of a time series associated with backend error rates. The predicted error rate values are compared to actual error rate values in the time series to determine a deviation from the predicted value. Deviation information for the time series data of error rates is then reported to a user through an interface in a simplified manner.
摘要翻译：由应用程序调用以处理请求的后端服务器的预期错误率的偏差用于表征后端服务器运行状况。响应于监视应用执行而生成的性能数据被处理以选择后端错误率数据。处理所选数据以预测与后端错误率相关联的时间序列的未来值。将预测误差率值与时间序列中的实际误差率值进行比较，以确定与预测值的偏差。然后以简化的方式通过界面将错误率的时间序列数据的偏差信息报告给用户。

4. 发明授权

US08402468B2 Capacity planning based on resource utilization as a function of workload 有权
标题翻译：基于资源利用的容量规划作为工作负载的函数
公开(公告)号：US08402468B2
公开(公告)日：2013-03-19
申请号：US12049840
申请日：2008-03-17
申请人： David Isaiah Seidman , Mark Jacob Addleman
发明人： David Isaiah Seidman , Mark Jacob Addleman
IPC分类号： G06F9/46 , G06F15/173
CPC分类号： G06F11/3452 , G06F11/3442 , G06F11/3466 , G06F11/3476 , G06F2201/865
摘要： Capacity planning based on resource utilization as a function of workload is disclosed. The workload may include different types of requests such as login requests, requests to visit web pages, requests to purchase an item on an online shopping site, etc. In one embodiment, data is determined for each of a plurality of workloads. The data includes characteristics of a workload and resource utilization due at least in part processing that workload. Based on the data, utilization of each of the resources as a function of workload characteristics is estimated. Further, based on the estimated resource utilization, workload characteristics that are expected to cause each respective resource to reach a certain level are predicted. That level could be 100 percent utilization, but could be another level. Capacity planning is performed based on the workload characteristics that are expected to cause each respective resource to reach a certain level.
摘要翻译：披露了基于资源利用作为工作负载的功能的容量规划。工作负载可以包括不同类型的请求，例如登录请求，访问网页的请求，在网络购物站点上购买项目的请求等。在一个实施例中，为多个工作负载中的每一个确定数据。数据包括工作负载和资源利用率的特征，至少部分地处理该工作负载。根据数据，估计作为工作负载特性的函数的每个资源的利用。此外，基于估计的资源利用率，预测预期使各个资源达到一定水平的工作量特性。该水平可能是100％的利用率，但可能是另一个水平。基于预期导致每个相应资源达到一定水平的工作负载特征来执行容量规划。

5. 发明申请

US20090031066A1 CAPACITY PLANNING BY TRANSACTION TYPE 有权
标题翻译：通过交易类型进行能力规划
公开(公告)号：US20090031066A1
公开(公告)日：2009-01-29
申请号：US11782346
申请日：2007-07-24
申请人： Jyoti Kumar Bansal , David Isaiah Seidman , Mark Jacob Addleman
发明人： Jyoti Kumar Bansal , David Isaiah Seidman , Mark Jacob Addleman
IPC分类号： G06F13/36
CPC分类号： G06F11/3476 , G06F9/5011 , G06F9/5027 , G06F9/5077 , G06F9/5083 , G06F11/3409 , G06F11/3419 , G06F2201/87 , G06F2209/5019 , G06F2209/508
摘要： Capacity planning is performed based on expected transaction load and the resource utilization for each expected transaction. Resource usage is determined for one or more transactions or URLs based on transaction specific and non-transaction specific resource usage. Once the resource usage for each transaction is known, the expected resource usage may be determined for an expected quantity of each transaction. The actual resources needed to meet the expected resource usage are then determined. Resources may include hardware or software, such as a central processing unit, memory, hard disk bandwidth, network bandwidth, and other computing system components. The expected resource usage for a transaction may based on the usage directly related to the transaction and usage not directly related to the transaction but part of a process associated with the performed transactions.
摘要翻译：基于预期的事务负载和每个预期事务的资源利用率进行容量规划。基于特定交易和非交易资源使用情况，为一个或多个交易或URL确定资源使用情况。一旦知道每个事务的资源使用情况，就可以针对每个事务的预期数量确定预期的资源使用情况。然后确定满足预期资源使用所需的实际资源。资源可以包括诸如中央处理单元，存储器，硬盘带宽，网络带宽和其他计算系统组件的硬件或软件。事务的预期资源使用可以基于与事务直接相关的使用和与事务直接相关的使用，而是与执行的事务相关联的过程的一部分。

6. 发明授权

US08631401B2 Capacity planning by transaction type 有权
标题翻译：按交易类型进行容量规划
公开(公告)号：US08631401B2
公开(公告)日：2014-01-14
申请号：US11782346
申请日：2007-07-24
申请人： Jyoti Kumar Bansal , David Isaiah Seidman , Mark Jacob Addleman
发明人： Jyoti Kumar Bansal , David Isaiah Seidman , Mark Jacob Addleman
IPC分类号： G06F9/455
CPC分类号： G06F11/3476 , G06F9/5011 , G06F9/5027 , G06F9/5077 , G06F9/5083 , G06F11/3409 , G06F11/3419 , G06F2201/87 , G06F2209/5019 , G06F2209/508
摘要： Capacity planning is performed based on expected transaction load and the resource utilization for each expected transaction. Resource usage is determined for one or more transactions or URLs based on transaction specific and non-transaction specific resource usage. Once the resource usage for each transaction is known, the expected resource usage may be determined for an expected quantity of each transaction. The actual resources needed to meet the expected resource usage are then determined. Resources may include hardware or software, such as a central processing unit, memory, hard disk bandwidth, network bandwidth, and other computing system components. The expected resource usage for a transaction may based on the usage directly related to the transaction and usage not directly related to the transaction but part of a process associated with the performed transactions.
摘要翻译：基于预期的事务负载和每个预期事务的资源利用率进行容量规划。基于特定交易和非交易资源使用情况，为一个或多个交易或URL确定资源使用情况。一旦知道每个事务的资源使用情况，就可以针对每个事务的预期数量确定预期的资源使用情况。然后确定满足预期资源使用所需的实际资源。资源可以包括诸如中央处理单元，存储器，硬盘带宽，网络带宽和其他计算系统组件的硬件或软件。事务的预期资源使用可以基于与事务直接相关的使用和与事务直接相关的使用，而是与执行的事务相关联的过程的一部分。

7. 发明申请

US20090235268A1 CAPACITY PLANNING BASED ON RESOURCE UTILIZATION AS A FUNCTION OF WORKLOAD 有权
标题翻译：基于资源利用的能力规划作为工作的功能
公开(公告)号：US20090235268A1
公开(公告)日：2009-09-17
申请号：US12049840
申请日：2008-03-17
申请人： David Isaiah Seidman , Mark Jacob Addleman
发明人： David Isaiah Seidman , Mark Jacob Addleman
IPC分类号： G06F9/50
CPC分类号： G06F11/3452 , G06F11/3442 , G06F11/3466 , G06F11/3476 , G06F2201/865
摘要： Capacity planning based on resource utilization as a function of workload is disclosed. The workload may include different types of requests such as login requests, requests to visit web pages, requests to purchase an item on an online shopping site, etc. In one embodiment, data is determined for each of a plurality of workloads. The data includes characteristics of a workload and resource utilization due at least in part processing that workload. Based on the data, utilization of each of the resources as a function of workload characteristics is estimated. Further, based on the estimated resource utilization, workload characteristics that are expected to cause each respective resource to reach a certain level are predicted. That level could be 100 percent utilization, but could be another level. Capacity planning is performed based on the workload characteristics that are expected to cause each respective resource to reach a certain level.
摘要翻译：披露了基于资源利用作为工作负载的功能的容量规划。工作负载可以包括不同类型的请求，例如登录请求，访问网页的请求，在网络购物站点上购买项目的请求等。在一个实施例中，为多个工作负载中的每一个确定数据。数据包括工作负载和资源利用率的特征，至少部分地处理该工作负载。根据数据，估计作为工作负载特性的函数的每个资源的利用。此外，基于估计的资源利用率，预测预期使各个资源达到一定水平的工作量特性。该水平可能是100％的利用率，但可能是另一个水平。基于预期导致每个相应资源达到一定水平的工作负载特征来执行容量规划。

8. 发明申请

US20080109684A1 BASELINING BACKEND COMPONENT RESPONSE TIME TO DETERMINE APPLICATION PERFORMANCE 有权
标题翻译：基准组件响应时间来确定应用性能
公开(公告)号：US20080109684A1
公开(公告)日：2008-05-08
申请号：US11559750
申请日：2006-11-14
申请人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
发明人： Mark Jacob Addleman , David Isaiah Seidman , John B. Bley , Carl Seglem
IPC分类号： G06F11/30 , G06F11/00
CPC分类号： G06F11/3447 , G06F11/3419 , G06F2201/88
摘要： Deviation of expected response times is used to characterize the health of one or more backend machines invoked by an application to process a request. Performance data generated in response to monitoring application execution is processed to select backend response time data. The selected data is processed to predict future values of a time series associated with backend response time. The predicted response time values are compared to actual response time values in the time series to determine a deviation from the predicted value. Deviation information for the time series data of response times is then reported to a user through an interface in a simple manner.
摘要翻译：预期响应时间的偏差用于表征应用程序调用以处理请求的一个或多个后端机器的运行状况。响应于监视应用执行而生成的性能数据被处理以选择后端响应时间数据。所选择的数据被处理以预测与后端响应时间相关联的时间序列的未来值。将预测的响应时间值与时间序列中的实际响应时间值进行比较，以确定与预测值的偏差。响应时间的时间序列数据的偏差信息则以简单的方式通过接口向用户报告。

9. 发明授权

US07917911B2 Automated grouping of messages provided to an application using execution path similarity analysis 有权
标题翻译：使用执行路径相似性分析自动分组提供给应用程序的消息
公开(公告)号：US07917911B2
公开(公告)日：2011-03-29
申请号：US11565723
申请日：2006-12-01
申请人： Jyoti Kumar Bansal , David Isaiah Seidman , Mark J. Addleman
发明人： Jyoti Kumar Bansal , David Isaiah Seidman , Mark J. Addleman
IPC分类号： G06F15/163
CPC分类号： G06F11/3612 , G06F11/3409 , G06F11/3447 , G06F2201/87 , G06F2201/875
摘要： An application is monitored to identify different execution paths, e.g., sequences of invoked components, which occur due to the receipt of messages by the application. Similarities between the execution paths are determined based on a distance algorithm, in one approach, and execution paths which are similar are assigned to a common group. Additionally, application runtime data such as response times is obtained for the execution paths and aggregated for the group. The messages can also be grouped based on the grouping of the execution paths. Further, a representative execution path can be determined for each execution path group for comparison to subsequent execution paths. A representative message can similarly be determined for each message group. Results can be reported which include a group identifier, representative message, representative execution path, count, and aggregated runtime data.
摘要翻译：监视应用程序以识别不同的执行路径，例如由于应用程序接收到消息而发生的被调用组件的序列。在一种方法中，基于距离算法确定执行路径之间的相似性，并且将相似的执行路径分配给公共组。此外，获取应用程序运行时数据，例如响应时间，用于执行路径并为组聚合。消息也可以基于执行路径的分组来分组。此外，可以为每个执行路径组确定代表执行路径，以便与后续执行路径进行比较。可以类似地为每个消息组确定代表消息。可以报告包括组标识符，代表性消息，代表性执行路径，计数和聚合运行时数据的结果。

10. 发明授权

US07743380B2 Monitoring clustered software applications 有权
标题翻译：监控群集软件应用程序
公开(公告)号：US07743380B2
公开(公告)日：2010-06-22
申请号：US11040768
申请日：2005-01-21
申请人： David Isaiah Seidman , Piotr Findeisen
发明人： David Isaiah Seidman , Piotr Findeisen
IPC分类号： G06F9/46 , G06F9/44
CPC分类号： G06F11/3616 , G06F11/3466 , G06F2201/81 , G06F2201/865
摘要： Embodiments of the invention distribute profiling responsibilities for a clustered application to various instances of the application that generally run on different computer hosts. In an embodiment, the profiling responsibility is measured in terms of metrics wherein each profiling agent of an instance collects metrics about that instance. The metrics are prioritized and assigned to instances such that the highest priority metrics are assigned if possible. Each metric is associated with an expected performance overhead, and the assignment of metrics to an instance is done such that the performance overhead on that instance and/or host does not exceed a threshold. Other embodiments are also disclosed.
摘要翻译：本发明的实施例将集群应用的分布责任分配给通常在不同计算机主机上运行的应用的各种实例。在一个实施例中，分析责任是根据度量来衡量的，其中实例的每个分析代理收集关于该实例的度量。度量被优先排列并分配给实例，以便尽可能分配最高优先权度量。每个度量与期望的性能开销相关联，并且完成对实例的指标分配，使得该实例和/或主机上的性能开销不超过阈值。还公开了其他实施例。

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