Abstract: In an exemplary aspect, method, apparatus, and program products are disclosed suitable for clock offset determination. One method includes performing a number of exchanges of at least single bytes with another network node, where values of the single bytes are different for the exchanges. The method also includes capturing and storing timestamps for each of the number of exchanges performed on the network node. A second method includes capturing and saving arrival timestamps for each of a number of timing messages in a set of timing messages received from another network node. This second method also includes sending the timestamps to at least the another node in response to completion of the set of timing messages.

Abstract: In an exemplary aspect, method, apparatus, and program products are disclosed suitable for clock offset determination. One method includes performing a number of exchanges of at least single bytes with another network node, where values of the single bytes are different for the exchanges. The method also includes capturing and storing timestamps for each of the number of exchanges performed on the network node. A second method includes capturing and saving arrival timestamps for each of a number of timing messages in a set of timing messages received from another network node. This second method also includes sending the timestamps to at least the another node in response to completion of the set of timing messages.

Abstract: Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.

Abstract: An autonomic computing system and method store a set of resource equivalencies in memory, select at least one resource equivalency from the set of resource equivalencies, and use the selected at least one resource equivalency for operating the selected resource as required by an autonomic computing system. The set of equivalent resources can contain a plurality of physically distinct resources that are logically equivalent. Resources are added or removed from the set automatically. Equivalent sets can be nested within an equivalent set.

Abstract: In an exemplary aspect, method, apparatus, and program products are disclosed suitable for clock offset determination. One method includes performing a number of exchanges of at least single bytes with another network node, where values of the single bytes are different for the exchanges. The method also includes capturing and storing timestamps for each of the number of exchanges performed on the network node. A second method includes capturing and saving arrival timestamps for each of a number of timing messages in a set of timing messages received from another network node. This second method also includes sending the timestamps to at least the another node in response to completion of the set of timing messages.

Abstract: A method and apparatus for and article of manufacture for simulating workloads experienced by multiple partitions in a virtualized system are provided. A master workload driver initiates, coordinates and regulates one or more workload drivers that execute one or more workload simulation tasks in a logical partition. Further, each workload driver may be configured to report a measure of performance regarding the workload to the master control driver where results of many workload drivers may be correlated and analyzed. A configuration file specifies the characteristics of each simulation. Further, the rate and nature of workloads may be adjusted dynamically during a given simulation to model the performance under different real-world scenarios of different computational loads that may be experienced by the virtualized system.

Abstract: In an exemplary aspect, method, apparatus, and program products are disclosed suitable for clock offset determination. One method includes performing a number of exchanges of at least single bytes with another network node, where values of the single bytes are different for the exchanges. The method also includes capturing and storing timestamps for each of the number of exchanges performed on the network node. A second method includes capturing and saving arrival timestamps for each of a number of timing messages in a set of timing messages received from another network node. This second method also includes sending the timestamps to at least the another node in response to completion of the set of timing messages.

Abstract: An autonomic computing system and method store a set of resource equivalencies in memory, select at least one resource equivalency from the set of resource equivalencies, and use the selected at least one resource equivalency for operating the selected resource as required by an autonomic computing system. The set of equivalent resources can contain a plurality of physically distinct resources that are logically equivalent. Resources are added or removed from the set automatically. Equivalent sets can be nested within an equivalent set.

Abstract: A system and method for application session tracking includes activating an application component for execution using an application session tracking facility (ASTF) and intercepting resource requests by the ASTF acting on behalf of this application. Resources are managed by allocating or releasing resources in accordance with resource usage profiles determined by system or application administrators of an application. The ASTF approach allows for controlling the usage of (potentially) distributed resources such as temporary space, database assets such as materialized views, directory services, shared memory segments among others during runtime and their return to their respective free pools and any necessary subsequent cleanup tasks upon a session termination.

Abstract: A method and apparatus for and article of manufacture for simulating workloads experienced by multiple partitions in a virtualized system are provided. A master workload driver initiates, coordinates and regulates one or more workload drivers that execute one or more workload simulation tasks in a logical partition. Further, each workload driver may be configured to report a measure of performance regarding the workload to the master control driver where results of many workload drivers may be correlated and analyzed. A configuration file specifies the characteristics of each simulation. Further, the rate and nature of workloads may be adjusted dynamically during a given simulation to model the performance under different real-world scenarios of different computational loads that may be experienced by the virtualized system.

Abstract: Techniques are provided for generically controlling one or more resources associated with at least one computing system. In one aspect of the invention, the technique comprises evaluating one or more performance metrics associated with the one or more resources given one or more configurations of the one or more resources. The technique then causes a change in the one or more configurations of the one or more resources based on the performance metric evaluating step. The one or more performance metrics and the one or more configurations are expressed in generic formats.

Abstract: A method and apparatus for and article of manufacture for simulating workloads experienced by multiple partitions in a virtualized system are provided. A master workload driver initiates, coordinates and regulates one or more workload drivers that execute one or more workload simulation tasks in a logical partition. Further, each workload driver may be configured to report a measure of performance regarding the workload to the master control driver where results of many workload drivers may be correlated and analyzed. A configuration file specifies the characteristics of each simulation. Further, the rate and nature of workloads may be adjusted dynamically during a given simulation to model the performance under different real-world scenarios of different computational loads that may be experienced by the virtualized system.

Abstract: An autonomic computing system and method store a set of resource equivalencies in memory, select at least one resource equivalency from the set of resource equivalencies, and use the selected at least one resource equivalency for operating the selected resource as required by an autonomic computing system. The set of equivalent resources can contain a plurality of physically distinct resources that are logically equivalent. Resources are added or removed from the set automatically. Equivalent sets can be nested within an equivalent set.

Abstract: Techniques for globally managing systems are provided. One or more measurable effects of at least one hypothetical action to achieve a management goal are determined at a first system manager. The one or more measurable effects are sent from the first system manager to a second system manager. At the second system manager, one or more procedural actions to achieve the management goal are determined in response to the one or more received measurable effects. The one or more procedural actions are executed to achieve the management goal.

Abstract: Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.

Abstract: Techniques for performing adaptive and robust prediction. Prediction techniques are adaptive in that they use a minimal amount of historical data to make predictions, the amount of data being selectable. The techniques are able to learn quickly about changes in the workload traffic pattern and make predictions, based on such learning, that are useful for proactive response to workload changes. To counter the increased variability in the prediction as a result of using minimal history, robustness is improved by checking model stability at every time interval and revising the model structure as needed to meet designated stability criteria. Furthermore, the short term prediction techniques can be used in conjunction with a long term forecaster.

Abstract: An updating capability updates a component of a computing environment, while maintaining the availability of the computing environment. In particular, a component of the computing environment which is associated with at least a portion of a unit of work is updated from one version to another version. Subsequently, the updated component emulates the original version, or operates in a compatibility mode, while other components of the computing environment, which are similarly associated with the same unit of work, remain at the original version.

Abstract: An updating capability updates a component of a computing environment, while maintaining the availability of the computing environment. In particular, a component of the computing environment which is associated with at least a portion of a unit of work is updated from one version to another version. Subsequently, the updated component emulates the original version, or operates in a compatibility mode, while other components of the computing environment, which are similarly associated with the same unit of work, remain at the original version.

Abstract: Techniques for performing adaptive and robust prediction. Prediction techniques are adaptive in that they use a minimal amount of historical data to make predictions, the amount of data being selectable. The techniques are able to learn quickly about changes in the workload traffic pattern and make predictions, based on such learning, that are useful for proactive response to workload changes. To counter the increased variability in the prediction as a result of using minimal history, robustness is improved by checking model stability at every time interval and revising the model structure as needed to meet designated stability criteria. Furthermore, the short term prediction techniques can be used in conjunction with a long term forecaster.

Abstract: Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.