Abstract: Systems, apparatus, articles of manufacture, and methods are disclosed for adaptive platform power management. These improve energy source management through switching energy sources of an edge node by incorporating memory, machine readable instructions, and processor circuitry to execute the functions of: evaluate operational parameters of a first energy source connected to a node and a second energy source connected to the node; determine an energy source to run a workload of the edge node based on a comparison of a first renewability to a second renewability, the evaluation of the operational parameters, and a power requirement of the workload, wherein the preferred energy source is the first energy source or the second energy source; and cause the edge node to switch to the preferred energy source.

Abstract: Various systems and methods for implementing an edge computing system to realize 5G network slices with blockchain traceability for informed 5G service supply chain are disclosed. A system configured to track network slicing operations includes memory and processing circuitry configured to select a network slice instance (NSI) from a plurality of available NSIs based on an NSI type specified by a client node. The available NSIs uses virtualized network resources of a first network resource provider. The client node is associated with the selected NSI. The utilization of the network resources by the plurality of available NSIs is determined using an artificial intelligence (AI)-based network inferencing function. A ledger entry of associating the selected NSI with the client node is recorded in a distributed ledger, which further includes a second ledger entry indicating allocations of resource subsets to each of the NSIs based on the utilization.

Abstract: An architecture to allow Multi-Access Edge Computing (MEC) billing and charge tracking, is disclosed. In an example, a tracking process, such as is performed by an edge computing apparatus, includes: receiving a computational processing request for a service operated with computing resources of the edge computing apparatus from a connected edge device within the first access network, wherein the computational processing request includes an identification of the connected edge device; identifying a processing device, within the first access network, for performing the computational processing request; and storing the identification of the connected edge device, a processing device identification, and data describing the computational processes completed by the processing device in association with the computational processing request.

Abstract: Various aspects of methods, systems, and use cases include using an edge device to control power states of nodes in an edge cluster. A method may include scheduling unscheduled application pods on a set of nodes of an edge cluster. The method may include determining a change to at least one power state of the set of power states based on the schedule. The method may include causing the edge cluster to operate according to the change.

Abstract: Various systems and methods for enhancing a distributed computing environment with multiple edge hosts and user devices, including in multi-access edge computing (MEC) network platforms and settings, are described herein. A device of a lifecycle management (LCM) proxy apparatus obtains a request, from a device application, for an application multiple context of an application. The application multiple context for the application is determined. The request from the device application for the application multiple context for the application is authorized. A device application identifier based on the request is added to the application multiple context. A created response for the device application based on the authorization of the request is transmitted to the device application. The response includes an identifier of the application multiple context.

Abstract: Various systems and methods for implementing an edge computing system to realize 5G network slices with blockchain traceability for informed 5G service supply chain are disclosed. A system configured to track network slicing operations includes memory and processing circuitry configured to select a network slice instance (NSI) from a plurality of available NSIs based on an NSI type specified by a client node. The available NSIs uses virtualized network resources of a first network resource provider. The client node is associated with the selected NSI. The utilization of the network resources by the plurality of available NSIs is determined using an artificial intelligence (AI)-based network inferencing function. A ledger entry of associating the selected NSI with the client node is recorded in a distributed ledger, which further includes a second ledger entry indicating allocations of resource subsets to each of the NSIs based on the utilization.

Abstract: Cooperative scheduling of master and slave base station transmissions is disclosed. Silent and deaf intervals are scheduled in a frame format of a first network to allow transmissions to occur in a second network without interference.