Abstract: An approach for parallel deduplication using automatic chunk sizing. A dynamic chunk deduplicator receives a request to perform data deduplication where the request includes an identification of a dataset. The dynamic chunk deduplicator analyzes file level usage for one or more data files including the dataset to associate a deduplication chunk size with the one or more data files. The dynamic chunk deduplicator creates a collection of data segments from the dataset, based on the deduplication chunk size associated with the one or more data files. The dynamic chunk deduplicator creates a deduplication data chunk size plan where the deduplication data chunk size plan includes deduplication actions for the collection of data segments and outputs the deduplication data chunk size plan.

Abstract: A method for improving risk situations for vehicle occupants in a vehicle which includes: configuring a set of circumstances; defining a set of values for each circumstance where each value has a rate; collecting context information for the circumstances, values and rates; collecting real-time sensor measurements pertaining to a vehicle, a driver and vehicle occupants; retrieving risk patterns from a risk pattern database; matching the sensor measurements to the risk patterns to find a matching risk pattern having a risk similarity value; contextualizing the matching risk pattern by increasing the risk similarity value to result in a personalized risk value; comparing the personalized risk value to a threshold; and executing a context modifying action to lower the personalized risk value below a predefined threshold when the personalized risk value exceeds the predefined threshold.

Abstract: A system, method and program product for reclaiming storage volumes in a storage area network (SAN). A method is disclosed that includes: monitoring each of a set containers implemented by a physical host, wherein each container holds a set of storage volumes that are mapped to a storage pool via a SAN switch; determining whether unused volumes in a selected container exceed an empty capacity threshold; in response to the empty capacity threshold being exceeded, determining whether an idle time threshold for the unused volumes has been exceeded with no I/O activity; and in response to the idle time threshold being exceeded with no I/O activity, separating the unused volumes from the selected container, un-mapping the unused volumes from the physical host, and returning the unused volumes to the storage pool.

Abstract: A method for improving a global lifespan of a storage system of a computing system is provided. The method includes: automatically determining a lifespan value of the at least one storage device to assign a global lifespan of the storage system, the global lifespan being dependent on the installation time of the at least one storage device; replacing, responsive to a time-based failure event, a storage device of the at least one storage device; and subsequently modifying, using the computing system, the global lifespan of the storage system based on the time-based failure event to define, at least in part, an optimized lifespan of the storage system.

Abstract: A system, method and program product for reclaiming storage volumes in a storage area network (SAN). A method is disclosed that includes: monitoring each of a set containers implemented by a physical host, wherein each container holds a set of storage volumes that are mapped to a storage pool via a SAN switch; determining whether unused volumes in a selected container exceed an empty capacity threshold; in response to the empty capacity threshold being exceeded, determining whether an idle time threshold for the unused volumes has been exceeded with no I/O activity; and in response to the idle time threshold being exceeded with no I/O activity, separating the unused volumes from the selected container, un-mapping the unused volumes from the physical host, and returning the unused volumes to the storage pool.

Abstract: A method for improving risk situations for vehicle occupants in a vehicle which includes: configuring a set of circumstances; defining a set of values for each circumstance where each value has a rate; collecting context information for the circumstances, values and rates; collecting real-time sensor measurements pertaining to a vehicle, a driver and vehicle occupants; retrieving risk patterns from a risk pattern database; matching the sensor measurements to the risk patterns to find a matching risk pattern having a risk similarity value; contextualizing the matching risk pattern by increasing the risk similarity value to result in a personalized risk value; comparing the personalized risk value to a threshold; and executing a context modifying action to lower the personalized risk value below a predefined threshold when the personalized risk value exceeds the predefined threshold.

Abstract: A method for improving a global lifespan of a storage system of a computing system is provided. The method includes: automatically determining a lifespan value of the at least one storage device to assign a global lifespan of the storage system, the global lifespan being dependent on the installation time of the at least one storage device; replacing, responsive to a time-based failure event, a storage device of the at least one storage device; and subsequently modifying, using the computing system, the global lifespan of the storage system based on the time-based failure event to define, at least in part, an optimized lifespan of the storage system.

Abstract: A method for improving a global lifespan of a storage system of a computing system is provided. The method includes: providing a prediction engine associated with the storage system including at least one storage device, the prediction engine being initiated at an installation time of the at least one storage device; automatically determining lifespan values of the at least one storage device to assign the global lifespan of the storage system, the global lifespan being dependent on the installation time of the at least one storage device; replacing, responsive to a time-based failure event, a storage device of the at least one storage device; and subsequently monitoring, using the prediction engine, the global lifespan of the storage system based on the time-based failure event to define, at least in part, an optimized lifespan of the storage system.