Abstract: An approach for managing workload deployment in a distributed network, including edge computing is provided. The approach includes deploying several modules, such as, EMM (energy management module), LDM (localized deployment manager) and EDM (edge deployment manager). These modules will be constantly monitoring and managing the energy consumption at the edge nodes under their purview and communicate with other modules to develop a holistic energy management system (e.g., energy policies, energy algorithms, energy plans, etc.) to ensure the most effective energy management of workload is implemented.

Abstract: Systems and methods are described for managing communications amongst mobile computing units. The invention includes location detection, three-dimensional proximity detection and alert systems for and amongst mobile units, through the utilization of low-power local communications protocols. The systems and methods minimize power consumption by the mobile units, and enable for robust, reconfigurable real-time location and asset tracking.

Abstract: Apparatuses and methods of operating a flexible and optimized power management unit (PMU) for multiple power supply scenarios are described. One integrated circuit includes a first terminal to couple to an unregulated power supply, a second terminal to couple to a regulated power supply, a first regulator, and a second regulator. The first regulator outputs a first supply voltage in a first configuration, and the second regulator outputs a second supply voltage in a second configuration. The first and second regulators do not operate concurrently.

Abstract: An illustrative efficient failover process and system in virtualized environment to reduce costs and resources associated with maintaining live stand-by failover scheduling and maintenance system is described herein. The illustrative embodiment uses incremental backup data to maintain a failover or passive virtualized computing platforms comprising of one or more virtual machines that are configured to and ready to be scaled up and initiated to take over the tasks and operations of a lost storage manager. Each virtualized failover or passive node is initially configured to use minimal computing resources to maintain a live backup of the active storage manager. During a failover, a passive virtual node will initiate the failover process. In an embodiment, the failover process comprises restoring a secondary copy of the lost storage manager, initiating a scale up process to increase computing resources, and continuing scheduled tasks and operations of the lost storage manager.

Abstract: An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.

Abstract: Aspects relate to random access channel procedures. In some examples, if a user equipment (UE) has not successfully received a random access channel (RACH) downlink message prior to the end of a random access window for a first RACH attempt, the UE may elect to proceed with a second RACH attempt. For example, the UE may determine whether there are any remaining downlink symbols available during the random access window to receive the RACH downlink message. If not, the UE may retransmit a physical RACH (PRACH) preamble.

Abstract: Some embodiments provide a two-tier DNS (Domain Name System) service for processing DNS requests. In some embodiments, the two-tier DNS service deploys first and second tiers of service machines, with the second-tier having several groups of service machines each of which is configured to resolve DNS requests for a different set of domain names than the other second-tier group(s). Each service machine in the first-tier is configured to identify the second-tier group responsible for each particular DNS request that the service machine receives for each particular domain name, and to forward the particular DNS request to the second-tier group that it identifies for the particular DNS request. The first-tier DNS service in some embodiments has only one group of service machines. Each first or second service machine group in some embodiments can have one or more service machines, and can be scaled up or down to add or remove service machines to the group (e.g., through an active/active layer 3 scaleout with BGP).

Abstract: Some embodiments provide a two-tier DNS (Domain Name System) service for processing DNS requests. In some embodiments, the two-tier DNS service deploys first and second tiers of service machines, with the second-tier having several groups of service machines each of which is configured to resolve DNS requests for a different set of domain names than the other second-tier group(s). Each service machine in the first-tier is configured to identify the second-tier group responsible for each particular DNS request that the service machine receives for each particular domain name, and to forward the particular DNS request to the second-tier group that it identifies for the particular DNS request. The first-tier DNS service in some embodiments has only one group of service machines. Each first or second service machine group in some embodiments can have one or more service machines, and can be scaled up or down to add or remove service machines to the group (e.g., through an active/active layer 3 scaleout with BGP).

Abstract: Some embodiments provide a two-tier DNS (Domain Name System) service for processing DNS requests. In some embodiments, the two-tier DNS service deploys first and second tiers of service machines, with the second-tier having several groups of service machines each of which is configured to resolve DNS requests for a different set of domain names than the other second-tier group(s). Each service machine in the first-tier is configured to identify the second-tier group responsible for each particular DNS request that the service machine receives for each particular domain name, and to forward the particular DNS request to the second-tier group that it identifies for the particular DNS request. The first-tier DNS service in some embodiments has only one group of service machines. Each first or second service machine group in some embodiments can have one or more service machines, and can be scaled up or down to add or remove service machines to the group (e.g., through an active/active layer 3 scaleout with BGP).

Abstract: Apparatuses and methods of operating a flexible and optimized power management unit (PMU) for multiple power supply scenarios are described. One integrated circuit includes a first terminal to couple to an unregulated power supply, a second terminal to couple to a regulated power supply, a first regulator, and a second regulator. The first regulator outputs a first supply voltage in a first configuration, and the second regulator outputs a second supply voltage in a second configuration. The first and second regulators do not operate concurrently.

Abstract: A UE may obtain an indication of a first subset of PRACH resources in a set of PRACH resources, the first subset of PRACH resources having a set of channel metrics that is greater than or equal to a first threshold value, select a first PRACH resource from the first subset of PRACH resources based on a first set of channel metrics of the first PRACH resource or a first RO associated with the first PRACH resource, and transmit a RACH message to a network node in the first RO. The UE may evaluate the multiple qualifying SSBs/CSI-RSs and select one SSB/CSI-RS among the qualifying SSBs/CSI-RSs based on a scheduling opportunity of the associated ROs and a power usage on the UE side.

Abstract: Natural disasters, such as cyclones, earthquakes, landslides, etc., or manmade damages, such as structural member's theft, terrorist attacks, etc., can cause collapse of transmission line towers. If these are not restored in time, there will be monetary loss to utilities as well as loss of service to consumers leading to societal impact. Generally, permanent restoration takes several weeks. Hence, a temporary solution for quick retrieval of power transmission is required. This invention provides a temporary support structural system comprising light weight guyed masts (1) made of readymade robust modules (6 and 7), easy to connect connection system, two pin gimbal joint (8) and easy to construct foundation system (9 and 10). The invention is flexible enough to develop various configurations for single or double circuit transmission lines. It is also scalable and can be used for 33 to 800 kV transmission lines.

Abstract: Systems and methods provide techniques for more effective and efficient predictive monitoring of a software application framework. For example, various embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to enable effective and efficient predictive monitoring of a software application framework using alert signatures for the software application that are generated by using at least one of first-order alert classification machine learning models, temporal-sequential alert classification machine learning models, categorical-sequential alert classification machine learning models, alert classification machine learning models, and second-order alert classification machine learning models.

Abstract: Various embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to effectively and efficiently generate one or more abstractive summaries of one or more multi-section documents. For example, certain embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to generate an abstractive summary of a multi-section document comprising one or more sections, by generating one or more section summaries, section input batches for each selected section, model outputs created by one or more text summarization machine learning models through the performance of a batch processing operation sequence, abstractive summaries, and then storing the abstractive summaries.

Abstract: A method of synchronously executing input/output operations (IOs) for a plurality of applications using a storage device with a file system includes the steps of: receiving a first write IO including an instruction to write first data at a first address of the file system; determining that, within a first range of the file system comprising the first address, there are no pending unmap IOs for deallocating storage space of the storage device from files of the plurality of applications; after determining that there are no pending unmap IOs within the first range, locking the first range to prevent incoming unmap IOs from deallocating storage space within the first range from the files of the plurality of applications; after locking the first range, writing the first data to the storage device at the first address; and after writing the first data, unlocking the first range.

Abstract: Methods, apparatuses, systems, and computer program products are disclosed for generating content for presentation at a collaborative content interface based on a captured content source.

Abstract: A method of synchronously executing input/output operations (IOs) for a plurality of applications using a storage device with a file system includes the steps of: receiving a first write IO including an instruction to write first data at a first address of the file system; determining that, within a first range of the file system comprising the first address, there are no pending unmap IOs for deallocating storage space of the storage device from files of the plurality of applications; after determining that there are no pending unmap IOs within the first range, locking the first range to prevent incoming unmap IOs from deallocating storage space within the first range from the files of the plurality of applications; after locking the first range, writing the first data to the storage device at the first address; and after writing the first data, unlocking the first range.

Abstract: Methods, apparatuses, or computer program products provide for generating a service risk analysis score data object. A service risk analysis request associated with an unreleased code object is received. One or more service risk analysis attributes are extracted using a service risk analysis layer based at least in part on the unreleased code object. A service risk analysis score data object is generated using a service risk analysis machine learning model based at least in part on the one or more service risk analysis attributes. The service risk analysis score data object is output.

Abstract: A method of deleting a first pointer block of a plurality of pointer blocks of a file system from a storage device used by a plurality of applications, wherein the plurality of pointer blocks are each subdivided into sub-blocks, includes the steps of: determining that a first sub-block of the first pointer block is marked as being empty of any addresses of the file system at which storage space is allocated to files of the applications; determining that a second sub-block of the first pointer block has not been marked as being empty; in response to the determining that the second sub-block has not been marked as being empty, determining that the second sub-block does not contain any addresses of the file system at which storage space is allocated to the files of the applications; and deleting the first pointer block from the storage device.

Abstract: Various embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to effectively and efficiently generate one or more abstractive summaries of one or more multi-section documents. For example, certain embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to generate an abstractive summary of a multi-section document comprising one or more sections, by generating one or more section summaries, section input batches for each selected section, model outputs created by one or more text summarization machine learning models through the performance of a batch processing operation sequence, abstractive summaries, and then storing the abstractive summaries.