Abstract: Described is a server monitoring technology that is scalable to large numbers of servers, e.g., in a datacenter. Agents on servers run queries to monitor data sources for that server, such as performance counters and other events. The agents monitor their resource usage and those of monitored events to stay within an administrator-specified resource budget (policy), e.g., by modifying the running queries and/or monitoring parameters. A controller receives results of the monitoring, analyzes the results, and takes action as needed with respect to server operation and monitoring. The controller may dynamically update an agent's queries, monitoring parameters and/or monitored data post-processing operations. The controller may issue alerts and reports, including alerts indicative of inter-server problems between two or more servers.

Abstract: Described is a server monitoring technology that is scalable to large numbers of servers, e.g., in a datacenter. Agents on servers run queries to monitor data sources for that server, such as performance counters and other events. The agents monitor their resource usage and those of monitored events to stay within an administrator-specified resource budget (policy), e.g., by modifying the running queries and/or monitoring parameters. A controller receives results of the monitoring, analyzes the results, and takes action as needed with respect to server operation and monitoring. The controller may dynamically update an agent's queries, monitoring parameters and/or monitored data post-processing operations. The controller may issue alerts and reports, including alerts indicative of inter-server problems between two or more servers.

Abstract: Described is a server monitoring technology that is scalable to large numbers of servers, e.g., in a datacenter. Agents on servers run queries to monitor data sources for that server, such as performance counters and other events. The agents monitor their resource usage and those of monitored events to stay within an administrator-specified resource budget (policy), e.g., by modifying the running queries and/or monitoring parameters. A controller receives results of the monitoring, analyzes the results, and takes action as needed with respect to server operation and monitoring. The controller may dynamically update an agent's queries, monitoring parameters and/or monitored data post-processing operations. The controller may issue alerts and reports, including alerts indicative of inter-server problems between two or more servers.

Abstract: Described is a server monitoring technology that is scalable to large numbers of servers, e.g., in a datacenter. Agents on servers run queries to monitor data sources for that server, such as performance counters and other events. The agents monitor their resource usage and those of monitored events to stay within an administrator-specified resource budget (policy), e.g., by modifying the running queries and/or monitoring parameters. A controller receives results of the monitoring, analyzes the results, and takes action as needed with respect to server operation and monitoring. The controller may dynamically update an agent's queries, monitoring parameters and/or monitored data post-processing operations. The controller may issue alerts and reports, including alerts indicative of inter-server problems between two or more servers.

Abstract: Described is a server monitoring technology that is scalable to large numbers of servers, e.g., in a datacenter. Agents on servers run queries to monitor data sources for that server, such as performance counters and other events. The agents monitor their resource usage and those of monitored events to stay within an administrator-specified resource budget (policy), e.g., by modifying the running queries and/or monitoring parameters. A controller receives results of the monitoring, analyzes the results, and takes action as needed with respect to server operation and monitoring. The controller may dynamically update an agent's queries, monitoring parameters and/or monitored data post-processing operations. The controller may issue alerts and reports, including alerts indicative of inter-server problems between two or more servers.

Abstract: Described is a server monitoring technology that is scalable to large numbers of servers, e.g., in a datacenter. Agents on servers run queries to monitor data sources for that server, such as performance counters and other events. The agents monitor their resource usage and those of monitored events to stay within an administrator-specified resource budget (policy), e.g., by modifying the running queries and/or monitoring parameters. A controller receives results of the monitoring, analyzes the results, and takes action as needed with respect to server operation and monitoring. The controller may dynamically update an agent's queries, monitoring parameters and/or monitored data post-processing operations. The controller may issue alerts and reports, including alerts indicative of inter-server problems between two or more servers.

Abstract: The present invention provides a method for identifying a serialisation bottleneck in a computer system (FIG. 1). The method comprises the steps of providing statistical data with regard to the actual response time (FIG. 2) of a computing resource, providing statistical data with regard to an expected response time of the computing resource and applying a mathematical formula to the actual response time to derive a relationship between the actual and expected response time. The relationship between the expected response time and the actual response time provides an indication of the presence of a serialisation problem in a computing system.

Abstract: The present invention relates to a system and method for improving the efficiency of transaction processing systems by associating each one of plurality of transaction types with a respective central processing unit.

Abstract: The present invention provides a system (10) and method (30) for estimating computing resource usage (14) for each transaction type comprising the steps of obtaining utilisation data and transaction count data, applying a linear least squares algorithm (32) to the input data (22), wherein the linear least squares algorithm (32) comprises further steps arranged to reduce the time required to perform the aforementioned linear least squares algorithm computation.

Abstract: The present invention relates to a position referencing system and method for horizontal or vertical conveyance, e.g., an elevator. The position referencing system includes a plurality of spaced apart color elements or reflectors (42) attached to a static structure (40), such as a door frame in a hoistway or guideway, a light source (12) for illuminating one of the reflectors, and a sensing device (10, 48, 48?) for capturing an image of the illuminated reflector. The image captured by the sensing device is used to determine the position and/or speed of the conveyance, e.g., an elevator car.

Abstract: The present invention provides a method and system (1) for improving the accuracy of an estimate of computing system resource usage, the method comprising the steps of obtaining utilization data of system resource and first transaction count data, obtaining further transaction count data and processing the transaction count data and further transaction data to provide an improved estimate of the number of transactions executed during a given time interval.

Abstract: The present invention provides a method and system for scheduling a transaction request to a central processing unit in a computing system (11), comprising polling at least one central processing unit to determine the current load on the least one central processing unit (10), allocating the transaction request to one the at least one central processing unit (12), or if the current load is above a predetermined threshold, delaying execution of the transaction request for a predetermined delay time (14).

Abstract: The present invention relates to an apparatus and method for improving transaction processing performance in a transaction processing system, particularly but not exclusively, in a transaction processing computing system comprising a plurality of processors.

Abstract: The present invention provides a method of estimating computing system resource usage by the process of obtaining raw utilisation data from a computing system and applying a mathematical model to the input data, thereby providing an estimate of resource usage for a individual transaction type within the computing environment.