Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: Exemplary embodiments of the present invention disclose a method, computer program product, and system for optimizing a clustered virtual computing environment. In exemplary embodiments, performance attributes are identified for a set of operating devices within the clustered virtual computing environment. Historical data of the identified performance attributes is obtained to create a historical data repository. A rulebase is developed using the historical data repository and input from user. A combined correlation pattern repository is generated using a first correlation pattern, a second correlation pattern and a scale-time invariant weight fraction.

Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: Exemplary embodiments of the present invention disclose a method, computer program product, and system for optimizing a clustered virtual computing environment. In exemplary embodiments, performance attributes are identified for a set of operating devices within the clustered virtual computing environment. Historical data of the identified performance attributes is obtained to create a historical data repository. A rulebase is developed using the historical data repository and input from user. A combined correlation pattern repository is generated using a first correlation pattern, a second correlation pattern and a scale-time invariant weight fraction.

Abstract: Embodiments of the invention provide techniques of monitoring and controlling temperature in a data center having a plurality of systems. Operating parameters of one or more cooling devices in the data center may be dynamically adjusted based on characteristics of the data center. An associated method may include monitoring in real time temperature and data flow patterns with respect to the systems in a zone of the data center, computing an optimal temperature based on the real time data and historical data collected in a repository, and activating one or more cooling devices in the zone upon determining that the temperature in the zone exceeds a predefined threshold.

Abstract: Embodiment of the invention related to characterization and optimization of tracks on a disk, magnetic or optical by determining an input/output (I/O) characteristics for a plurality of blocks on a disk by a processor, wherein the characteristics comprise at least one of a data size or data type or an association between the data files, and determining a plurality of parameters affecting operation performed on the disk for placement of the plurality of data clusters.

Abstract: Exemplary embodiments of the present invention disclose a method, computer program product, and system for optimizing a clustered virtual computing environment. In exemplary embodiments, performance attributes are identified for a set of operating devices within the clustered virtual computing environment. Historical data of the identified performance attributes is obtained to create a historical data repository. A rulebase is developed using the historical data repository and input from user. A combined correlation pattern repository is generated using a first correlation pattern, a second correlation pattern and a scale-time invariant weight fraction.

Abstract: A method, system, and computer program product for mitigating adjacent track erasures in hard disks, includes: determining input/output (I/O) characteristics for a plurality of blocks on a hard disk; assigning the plurality of blocks to a plurality of categories of I/O characteristics by the processor; and clustering content of the blocks assigned to the same category in one or more continuous tracks on the hard disk. Each block is assigned to one category. Blocks with similar I/O characteristics are clustered on one or more continuous tracks. By performing this clustering, blocks with a high number of I/O operations are grouped and stored on fewer tracks than if they were scattered across numerous tracks. This reduces the number of tracks experiencing a high number of I/O operations, and in turn, the amount of refreshing of adjacent tracks is reduced.

Abstract: Exemplary embodiments of the present invention disclose a method, computer program product, and system for optimizing a clustered virtual computing environment. In exemplary embodiments, performance attributes are identified for a set of operating devices within the clustered virtual computing environment. Historical data of the identified performance attributes is obtained to create a historical data repository. A rulebase is developed using the historical data repository and input from user. A combined correlation pattern repository is generated using a first correlation pattern, a second correlation pattern and a scale-time invariant weight fraction.

Abstract: The present invention relates to a method, system, and computer program product for determining storage device weight values to use to select one of the storage devices to use as a target storage to which data from a source storage is migrated. A determination is made, for each of the storage devices, of static parameter values for static parameters comprising attributes of the storage device and dynamic parameter values for dynamic parameters providing device health information determined by accessing the storage device to determine operational conditions at the storage device. Storage device weight values are determined as a function of the static parameter values and the dynamic parameter values of the device. The determined storage device weight values are used to select one of the storage devices as the target storage to which data from the source storage is migrated.

Abstract: Optimization of tracks on a hard disk includes: determining I/O characteristics for data clusters to be stored on the hard disk; generating a set of solutions for each possible placement configuration; for each solution, calculating a plurality of cost functions using the I/O characteristics for the plurality of data clusters; for each solution, calculating a membership value using the cost function values; for each solution, calculating a fitness value using the membership value; retaining the solutions with the fitness value greater than a predetermined threshold; determining whether at least one stopping condition has been met; if not, adding new solutions to the retained solutions to generate the next set of solutions; and repeating the calculating the membership value, the calculating the fitness value, and the retaining the solutions with the fitness value greater than the predetermined threshold until at least one stopping condition has been met.

Abstract: Optimization of tracks on a hard disk includes: determining I/O characteristics for data clusters to be stored on the hard disk; generating a set of solutions for each possible placement configuration; for each solution, calculating a plurality of cost functions using the I/O characteristics for the plurality of data clusters; for each solution, calculating a membership value using the cost function values; for each solution, calculating a fitness value using the membership value; retaining the solutions with the fitness value greater than a predetermined threshold; determining whether at least one stopping condition has been met; if not, adding new solutions to the retained solutions to generate the next set of solutions; and repeating the calculating the membership value, the calculating the fitness value, and the retaining the solutions with the fitness value greater than the predetermined threshold until at least one stopping condition has been met.

Abstract: A method, system, and computer program product for mitigating adjacent track erasures in hard disks, includes: determining input/output (I/O) characteristics for a plurality of blocks on a hard disk; assigning the plurality of blocks to a plurality of categories of I/O characteristics by the processor; and clustering content of the blocks assigned to the same category in one or more continuous tracks on the hard disk. Each block is assigned to one category. Blocks with similar I/O characteristics are clustered on one or more continuous tracks. By performing this clustering, blocks with a high number of I/O operations are grouped and stored on fewer tracks than if they were scattered across numerous tracks. This reduces the number of tracks experiencing a high number of I/O operations, and in turn, the amount of refreshing of adjacent tracks is reduced.

Abstract: Optimization of tracks on a hard disk includes: determining I/O characteristics for data clusters to be stored on the hard disk; generating a set of solutions for each possible placement configuration; for each solution, calculating a plurality of cost functions using the I/O characteristics for the plurality of data clusters; for each solution, calculating a membership value using the cost function values; for each solution, calculating a fitness value using the membership value; retaining the solutions with the fitness value greater than a predetermined threshold; determining whether at least one stopping condition has been met; if not, adding new solutions to the retained solutions to generate the next set of solutions; and repeating the calculating the membership value, the calculating the fitness value, and the retaining the solutions with the fitness value greater than the predetermined threshold until at least one stopping condition has been met.

Abstract: A method which on determination of an entity replacement request is configured to identify an optimized entity as a replacement based on a predefined set of metadata, wherein the metadata comprises a profile associated with the entity, wherein the profile of the entity is further based on a graph, such as a graphical representation of social links, associated with the entity; and provide the optimized entity as a replacement for the entity to be replaced. Other embodiments are also disclosed.