Technologies for providing attestation for function as a service flavors include a compute device including circuitry configured to obtain function definition data indicative of a set of operations to be performed in a function and a set of hardware resources to be utilized by the function, execute a benchmark operation to produce benchmark data indicative of a measured performance of the function, and sign the function definition data and the benchmark data to produce function flavor data. The circuitry is also configured to provide the function flavor data to one or more other compute devices for validation that the function, when executed on the hardware resources, provides the measured performance and write, to a distributed ledger, the function flavor data.

The present disclosure provides embodiments in which computing (e.g., edge computing) is part of base station (BS) capability. These embodiments may enable conducting computing offloading between a user equipment (UE) and BS in the radio access network (RAN), for example, compute in the RAN, and deliver “true” edge computing user experience. Other embodiments may be described and claimed.

An electronic device including an application processor and a communication processor. The communication processor, for managaging a resource memory, configured to monitor an occupancy rate of the resource memory for detecting a memory leakage, release a network connection when the electronic device is in an idle state, in response to the detecting of the memory leakage, initialize the resource memory after the network connection is released, and reconnect the network connection, wherein the idle state indicates a state when the electronic device is not occupied or used by a user, and wherein the initialization is performed at a non-flag area from among the resource memory.

Embodiments of the claimed subject matter are directed to methods and a system that allows the optimization of processes operating on a multi-platform system (such as a mainframe) by migrating certain processes operating on one platform to another platform in the system. In one embodiment, optimization is performed by evaluating the processes executing in a partition operating under a proprietary operating system, determining a collection of processes from the processes to be migrated, calculating a cost of migration for migrating the collection of processes, prioritizing the collection of processes in an order of migration and incrementally migrating the processes according to the order of migration to another partition in the mainframe executing a lower cost (e.g., open-source) operating system.

A data onboarding network includes a data onboarding configurator to generate a number of data onboarding objects, each of these data onboarding objects including subscription metadata for reading data from a data source and publication metadata for writing data to a destination data store. According to one implementation, the data on-boarding system also includes an execution engine task store to store various data onboarding tasks, where the data onboarding tasks are configured to pull data from the data source using the subscription metadata and to write data to the destination data store using the publication metadata. An execution engine executes one or more of these data onboarding tasks.

A method for identifying a second device by a first device for establishing a communication between the first device and the second device is described here. The method includes receiving, by a processor of a first device, a voice command from a worker in a workplace. In an example, the method comprises pausing, by the processor, a workflow operation executing on the first device. The method further comprises performing, by the processor, a voice recognition to analyze the voice command of the worker. The method includes activating, by the processor, a communication module of the first device based on the voice recognition, to identify a second device in proximity to the first device. The method includes terminating, by the processor, a connection between the first device and the wearable electronic device. Thus, terminating, by the processor, a second connection of the first device with the second device.

A task processing method, apparatus, and system based on a distributed system. The method comprises: obtaining, by a task processing device, task information from a master control device by initiating a task request, wherein the task information corresponding to the task request is stored in the master control device; starting, by a main process of the task processing device, a corresponding task subprocess by triggering a proxy process for executing the task information after receiving the task information; and storing, by the task processing device, task execution information to a target location through the proxy process, wherein the task execution information comprises one or more of the following pieces of information: a task identifier of the task information, process information of the task subprocess, log information and a return code generated when the task subprocess executes the task information. The present invention solves the main process of the task processing device monitors, according to the task identifier, whether the task information is started and executed, and monitor, according to the return code, whether the task information is fully executed.

Embodiments disclose techniques for migrating a logical partition from a source computing system with an inactive I/O server to another target computing system. In one embodiment, a computing system collects and stores the resource configuration of the logical partition, upon detecting a change in a resource configuration of a logical partition on the source computing system. Once the computing system detects that a I/O server on the source computing system is inactive for a migration of the logical partition, the computing system uses the collected resource configuration to configure the logical partition on the target computing system.

Techniques for solving a multi-agent plan recognition problem are provided. In one example, a computer-implemented method comprises transforming, by a device operatively coupled to a processor, a problem model and an at least partially ordered sequence of observations into an artificial intelligence planning problem through a transform algorithm. The problem model can comprises a domain description from a plurality of agents and a durative action. Furthermore, at least one of the observations of the at least partially ordered sequence of observations can be a condition that changes over time. The computer-implemented method further comprises determining, by the device, plan information using an artificial intelligence planner on the artificial intelligence planning problem. The computer-implemented method further comprises translating, by the device, the plan information into information indicative of a solution to the artificial intelligence planning problem.

Disclosed herein is a method and system for dynamically integrating a plurality of BOTs. The method comprises creating the plurality of BOTs offering one or more automated services, wherein each of the plurality of BOTs has a common BOT structure comprising one or more field parameters. One or more predefined functions are assigned to each of the plurality of BOTs, wherein at least one of the one or more predefined functions comprises a function value. A maturity score for each of the plurality of BOTs is determined based on the one or more field parameters and the function value upon assigning the one or more predefined functions to each of the plurality of BOTs. Finally, the plurality of BOTs are integrated by synchronizing data amongst the plurality of BOTs based on the maturity score.