Catherine K Eilert

6393455, May 21, 2002

Mar 28, 1997

08/827528

Catherine K. Eilert - Wappingers Falls NY
Peter B. Yocom - Wappingers Falls NY
Gary M. King - Millbrook NY
Jeffrey D. Aman - Poughkeepsie NY

International Business Machines Corp. - Armonk NY

G06F 900

709105, 709104

A technique is disclosed for managing a workload distributed across multiple data processing systems to enhance shared resource access to meet a common performance standard. The technique includes on at least one system, measuring performance of the work units on the system to create local performance data, and on at least some of the systems sending the local performance data to at least one other system of the multiple data processing systems. The method further includes on at least one of the systems, receiving the performance data from the sending systems to create remote performance data, and adjusting at least one control parameter for accessing shared resources in response to the local and remote performance data to modify the performance of the work units distributed across the data processing systems to achieve the common performance standard. A dynamic resource clustering process is also employed to enhance the shared resource management.

6442583, Aug 27, 2002

May 1, 1997

08/848763

Catherine Krueger Eilert - Wappingers Falls NY
Bernard Roy Pierce - Poughkeepsie NY

International Business Machines Corporation - Armonk NY

G06F 900

709104, 709105, 709103

A method for managing a workload distributed across data processing systems in accordance with a common processor consumption standard, including the steps of measuring the processor consumption of the work units to create local processor consumption data; sending the local processor consumption data to at least one other system; receiving processor consumption data from at least one other system to create remote processor consumption data; and adjusting at least one of the system control parameters to modify the remote processor consumption and the local processor consumption of the work units to achieve the common processor consumption standard is provided. Also provided is an apparatus according to the method.

6587938, Jul 1, 2003

Sep 28, 1999

09/407212

Catherine K. Eilert - Wappingers Falls NY
Jeffrey P. Kubala - Poughquag NY
Jeffrey M. Nick - West Park NY
Peter B. Yocom - Wappingers Falls NY

International Business Machines Corporation - Armonk NY

G06F 1516

712 29, 712 13, 709105, 709104

Central processing unit (CPU) resources are managed within a computing environment. When the allocation of CPU resources to a partition of the computing environment is to be adjusted, the allocation is adjusted dynamically. This dynamic adjustment is across at least two partitions of the computing environment. The adjusting includes modifying processor weights associated with the partitions.

6622177, Sep 16, 2003

Jul 27, 2000

09/626519

Catherine K. Eilert - Wappingers Falls NY
Gary M. King - Millbrook NY
Peter B. Yocom - Wappingers Falls NY
Harry M. Yudenfriend - Poughkeepsie NY

International Business Machines Corporation - Armonk NY

G06F 300

710 3, 710 9, 710 52, 709249

Disclosed is a method and computer program device for dynamically managing the assignment of alias addresses to base addresses referencing an input/output (I/O) device, such as a direct access storage device (DASD). Two distinct methods are disclosed. In one method, alias addresses are assigned based on the performance of the I/O devices. In this method, alias addresses are assigned to highly utilized devices, as indicated by device performance data, in order to maximize the efficient utilization of I/O device resources. In a second method, workload management principles are utilized to assign alias addresses. In this method, a correlation is made between each I/O device and the service classes utilizing each device. As in the first method, performance data is generated for each I/O device. Alias addresses are assigned to I/O devices experiencing queue delays as indicated by their performance data, if the device is associated with a service class that has failed to meet one or more processing goals.

6654780, Nov 25, 2003

Mar 28, 1997

08/827286

Catherine Krueger Eilert - Wappingers Falls NY
Peter Bergersen Yocom - Wappingers Falls NY

International Business Machines Corporation - Armonk NY

G06F 900

709104

Managing processor resources in a non-dedicated computer system. An amount of a processor resource is allocated to a real-time application of the computer system. The amount does not exceed a limit chosen for a group of real-time applications, wherein the group includes the real-time application being allocated the resource. A selected amount of the processor resource remains available to execute other types of applications and work on the system. During processing of the real-time application, use of the processor resource does not exceed a chosen maximum value, thereby ensuring the processor resource is not monopolized by the real-time application and allowing other types of work to be processed on the system.

6760910, Jul 6, 2004

Jul 13, 2001

09/905236

Catherine K. Eilert - Wappingers Falls NY
Peter B. Yocom - Wappingers Falls NY
Gary M. King - Millbrook NY
Jeffrey D. Aman - Poughkeepsie NY

International Business Machines Corporation - Armonk NY

G06F 900

718104, 718102, 709223, 709224, 709225, 709226

A technique is disclosed for managing a workload distributed across multiple data processing systems to enhance shared resource access to meet a common performance standard. The technique includes on at least one system, measuring performance of the work units on the system to create local performance data, and on at least some of the systems sending the local performance data to at least one other system of the multiple data processing systems. The method further includes on at least one of the systems, receiving the performance data from the sending systems to create remote performance data, and adjusting at least one control parameter for accessing shared resources in response to the local and remote performance data to modify the performance of the work units distributed across the data processing systems to achieve the common performance standard. A dynamic resource clustering process is also employed to enhance the shared resource management.

56757395, Oct 7, 1997

Feb 3, 1995

8/383168

Catherine Krueger Eilert - Wappingers Falls NY
Peter Bergersen Yocom - Wappingers Falls NY

International Business Machines Corporation - Armonk NY

G06F 1300

39520011

An apparatus for managing a workload distributed across data processing systems in accordance with a common performance standard, which includes a means for measuring the performance of the work units to create local performance data; a means for sending said local performance data to at least one other system; a means for receiving performance data from at least one other system to create remote performance data; and a means responsive to said local and remote performance data for adjusting at least one of the system control parameters to modify the performance of the work units on the system to achieve the common performance standard, is disclosed. Also disclosed is a method for managing workload as represented by the apparatus.

62301837, May 8, 2001

Mar 11, 1998

9/038573

Peter B. Yocom - Wappingers Falls NY
Catherine K. Eilert - Wappingers Falls NY
John E. Arwe - Poughkeepsie NY

International Business Machines Corporation - Armonk NY

G06F 1300

709105

A method and apparatus for controlling the number of servers in a multisystem cluster. Incoming work requests are organized into service classes, each of which has a queue serviced by servers across the cluster. Each service class has defined for it a local performance index for each particular system of the cluster and a multisystem performance index for the cluster as a whole. Each system selects one service class as a donor class for donating system resources and another service class as a receiver class for receiving system resources, based upon how well the service classes are meeting their goals. Each system then determines the resource bottleneck causing the receiver class to miss its goals. If the resource bottleneck is the number of servers, each system determines whether and how many servers should be added to the receiver class, based upon whether the positive effect of adding such servers on the performance index for the receiver class outweighs the negative effect of adding such servers on the performance measure for the donor class. If a system determines that servers should be added to the receiver class, it then determines the system in the cluster to which the servers should be added, based upon the effect on other work on that system.