Abstract: The present disclosure pertains to a system for providing model-based treatment recommendation via individual-specific machine learning models. In some embodiments, the system (i) obtains an audio recording of an individual, (ii) determines, from the audio recording, one or more utterance-related features of the individual; (iii) performs one or more queries based on the one or more utterance-related features to obtain health information (e.g., utterance-related conditions and treatments provided for the utterance-related conditions) associated with similar individuals having similar utterance-related conditions as the subject; (iv) provides the health information associated with the similar individuals to a machine learning model to train the machine learning model; and (v) provides, subsequent to the training of the machine learning model, the one or more utterance-related features to the machine learning model to determine one or more treatments for the individual.

Abstract: Embodiments are described for performing an uninterrupted restore in a storage system in view of one or more abort events. A restore agent receives writes one or more data blocks to a conditional construction container. A parent interrupt service routine (ISR) polls for abort events. In response to an abort event, an intermediate interrupt is generated that spawns a child processes for each process of the restore. The intermediate ISR logs each child ISR, the process it is responsible for, and the intermediate interrupt, for later restoration of the restore state. After a recovery of the above event, then each child ISR can be called to restore its state. After restoring the state, the restore agent resumes the restore from where the abort event was detected. The child ISRs are re-entrant. If another abort event is detected, the restore state can again be saved and later resumed from that state.

Abstract: Methods and systems for backing up data to a target device are described. According to some embodiments, the method receives a first set of data packets for backup, where the first set of data packets includes a multiplicity of data chunks. The method further captures footprints of the first set of data packets in a cache disk array. In response to receiving an acknowledgement from the cache disk array indicating the footprints have been captured, the method further initiates a write operation to write each data chunk of the first set of data packets to the target device. In response to receiving an acknowledgement indicating the data chunk is successfully written, the method further flushes the respective footprint of the data chunk from the cache disk array.

Abstract: Methods and systems for restoring data from a target device are described. According to some embodiments, the method receives a first set of data packets for restore, where the first set of data packets includes a multiplicity of data chunks. The method further captures footprints of the first set of data packets in a cache disk array. In response to receiving an acknowledgement from the cache disk array indicating the footprints of the first set of data packets have been captured, the method pushes each data chunk of the first set of data packets to a construction container for reconstruction of backup data. In response to receiving an acknowledgement from the construction container indicating the data chunk is successfully pushed, the method flushes the respective footprint of the data chunk from the cache disk array.

Abstract: Embodiments are described for performing an uninterrupted backup in a storage system in view of one or more abort events. A backup agent receives writes one or more data blocks to a write latch. A parent interrupt service routine (ISR) polls for abort events. In response to an abort event, an intermediate interrupt is generated that spawns a child processes for each process of the backup. The intermediate ISR logs each child ISR, the process it is responsible for, and the intermediate interrupt, for later restoration of the backup state. After a recovery of the above event, then each child ISR can be called to restore its state. After restoring the state, the backup agent resumes the backup from where the abort event was detected. The child ISRs are re-entrant. If another abort event is detected, the backup state can again be saved and later resumed from that state.

Abstract: Embodiments are described for performing an uninterrupted backup in a storage system in view of one or more abort events. A backup agent receives writes one or more data blocks to a write latch. A parent interrupt service routine (ISR) polls for abort events. In response to an abort event, an intermediate interrupt is generated that spawns a child processes for each process of the backup. The intermediate ISR logs each child ISR, the process it is responsible for, and the intermediate interrupt, for later restoration of the backup state. After a recovery of the above event, then each child ISR can be called to restore its state. After restoring the state, the backup agent resumes the backup from where the abort event was detected. The child ISRs are re-entrant. If another abort event is detected, the backup state can again be saved and later resumed from that state.

Abstract: An apparatus for performing backup operations for data packets by a backup agent is provided. The apparatus predicts a first backup time period of completing a first backup operation for the data packets and determines a second backup time period of performing the first backup operation until the first backup operation is stopped at a point of time. The apparatus also identifies an incomplete status of the first backup operation at the point of time based on a comparison between the first backup time period and the second backup time period, and collects information describing the incomplete status. The apparatus further starts a second backup operation for the data packets from the incomplete status based on the information.

Abstract: An apparatus for performing restore operations for data packets by a restore agent is provided. The apparatus predicts a first time period of completing a first restore operation for the data packets and determines a second time period of performing the first restore operation until the first restore operation is stopped at a point of time. The apparatus also identifies an incomplete status of the first restore operation at the point of time based on a comparison between the first time period and the second time period, and collects information describing the incomplete status. The apparatus further starts a second restore operation for the data packets from the incomplete status based on the information.

Abstract: A method for performing a restoration operation includes obtaining a restoration request, wherein the restoration request specifies a virtual machine (VM) set to be restored, and in response to the restoration request: identifying a first set of virtual machines (VMs), performing a critical VM prioritization on the first set of VMs using a trained machine learning model to obtain an ordered list of critical VMs, performing a non-critical VM prioritization on a second set of VMs using the trained machine learning model to obtain an ordered list of non-critical VMs, consolidating the ordered list of critical VMs and the ordered list of non-critical VMs to obtain a final list, and initiating a restoration of virtual machines using the final list.

Abstract: A method for managing backups includes obtaining a plurality of parameters for a data item, filtering the plurality of parameters to obtain a plurality of filtered parameters, evaluating each filtered parameter of the plurality of filtered parameters to obtain a plurality of evaluated parameters, updating a promotion parameter register based on the plurality of evaluated parameters, and processing a backup request using the promotion parameter register, wherein the backup request specifies the data item.

Abstract: A method and system for prioritizing critical data object storage during backup operations. Specifically, the method and system disclosed herein entail reordering data objects, awaiting being written to storage and thus queued in one or more data object queues, in accordance with a nearest-critical based sequential order. The nearest-critical based sequential order may be derived through modified weight-based Euclidean distances calculated between adjacent data object pairs queued in any given data object queue. Further, the calculated modified weight-based Euclidean distances incorporate data criticality factors associated with the adjacent data object pairs. By reordering data objects in a nearest-critical based sequential order, critical data objects may be written into storage first, thereby avoiding possible critical data loss should a disaster occur during backup operations.

Abstract: A method and system for prioritizing critical data object recovery during restore operations. Specifically, the method and system disclosed herein entail reordering data objects, awaiting being read from backup storage and thus queued in one or more data object queues, in accordance with a nearest-critical based sequential order. The nearest-critical based sequential order may be derived through modified weight-based Euclidean distances calculated between adjacent data object pairs queued in any given data object queue. Further, the calculated modified weight-based Euclidean distances incorporate data criticality factors associated with the adjacent data object pairs. By reordering data objects in a nearest-critical based sequential order, critical data objects may be recovered first, thereby avoiding possible critical data loss should a disaster occur during restore operations.

Abstract: A backup agent for generating backups includes a persistent storage and a backup manager. The persistent storage stores backup/restoration policies. The backup manager obtains production host computing resource characteristics associated with production hosts; performs a computing resource analysis of the production host computing resource characteristics to obtain resource profiles for each of the production hosts; performs an availability analysis of the obtained resource profiles to determine an application-level computing resources distribution for generating the backups; coordinates generating the backups using the application-level computing resource distribution and the backup/restoration policies to obtain the backups; and stores the obtained backups in backup storage.

Abstract: A method, apparatus, and system for regulating resource usage of a backup application is disclosed. The operations comprise: continuously monitoring and obtaining system resource usage, process states, and backup policy parameters; generating a normalized band value based on the system resource usage, the process states, and the backup policy parameters; generating a straight line plot based on the band value, a total CPU value, and a deviation value; calculating a slope of the straight line plot, wherein the slope is utilized to generate a deviation value based further on a first value and a second value received from a user, and wherein the deviation value is fed back to the generation of the straight line plot to normalize the slope; generating control values based on the slope; and adjusting performance of the backup application based on the control values to regulate system resource usage of the backup application.

Abstract: Systems and methods for determining retention periods or policies for backups are disclosed. A rule book stores relationships between rules and recommended retention periods. Data related to a backup is collected and organized. A query is generated from the organized data and used to identify a rule from the rule book. The retention period corresponding to the identified rule in the rule book is then applied to the corresponding backup.

Abstract: A method, apparatus, and system for regulating resource usage of a backup application is disclosed. The operations comprise: continuously monitoring and obtaining system resource usage, process states, and backup policy parameters; generating a normalized band value based on the system resource usage, the process states, and the backup policy parameters; generating a straight line plot based on the band value, a total CPU value, and a deviation value; calculating a slope of the straight line plot, wherein the slope is utilized to generate a deviation value based further on a first value and a second value received from a user, and wherein the deviation value is fed back to the generation of the straight line plot to normalize the slope; generating control values based on the slope; and adjusting performance of the backup application based on the control values to regulate system resource usage of the backup application.

Abstract: A backup agent for generating backups includes a persistent storage and a backup manager. The persistent storage stores backup/restoration policies. The backup manager obtains production host computing resource characteristics associated with production hosts; performs a computing resource analysis of the production host computing resource characteristics to obtain resource profiles for each of the production hosts; performs an availability analysis of the obtained resource profiles to determine an application-level computing resources distribution for generating the backups; coordinates generating the backups using the application-level computing resource distribution and the backup/restoration policies to obtain the backups; and stores the obtained backups in backup storage.

Abstract: A decoupled backup solution for distributed databases across a failover cluster. Specifically, a method and system disclosed herein improve upon a limitation of existing backup mechanisms involving distributed databases across a failover cluster. The limitation entails restraining backup agents, responsible for executing database backup processes across the failover cluster, from immediately initiating these aforementioned processes upon receipt of instructions. Rather, due to this limitation, these backup agents must wait until all backup agents, across the failover cluster, receive their respective instructions before being permitted to initiate the creation of backup copies of their relative distributed database. Subsequently, the limitation imposes an initiation delay on the backup processes, which the disclosed method and system omit, thereby granting any particular backup agent the capability to immediately (i.e., without delay) initiate those backup processes.

Abstract: The present disclosure pertains to a system for providing model-based treatment recommendation via individual-specific machine learning models. In some embodiments, the system (i) obtains an audio recording of an individual, (ii) determines, from the audio recording, one or more utterance-related features of the individual; (iii) performs one or more queries based on the one or more utterance-related features to obtain health information (e.g., utterance-related conditions and treatments provided for the utterance-related conditions) associated with similar individuals having similar utterance-related conditions as the subject; (iv) provides the health information associated with the similar individuals to a machine learning model to train the machine learning model; and (v) provides, subsequent to the training of the machine learning model, the one or more utterance-related features to the machine learning model to determine one or more treatments for the individual.

Abstract: Aspects of the present invention provide an approach for optimizing a presentation of content on a display of a user device for n identified user. Application behavior metrics and user behavior metrics are tracked over time for the particular user based on the applications executing on the user device and the users interactions with the content presented by each application. Sections of content are assigned a priority based on the collected metrics which identify content sections (i.e., focus areas) most likely relevant to the user. Based on the assigned priorities, content from one or more applications is presented to the user in an optimal manner (e.g., not overlaid or obscured).