Embodiments include methods for managing the processing of data and performing computing tasks of a wireless device using computing resources of a remote network computing device. A wireless device and a network computing device may dynamically track factors affecting a round-trip latency of a computing task. The wireless device and the network computing device may generate and send metadata including the factors and a latency budget for the computing task. The wireless device and the network computing device may adjust a processing time for processing data related to the computing task based the received metadata and the latency budget.

A method for configuring a radio access network (RAN) process onto a communications network having a plurality of nodes is disclosed. The method includes converting the RAN process into a service function chain having a plurality of functions, and distributing each function of the plurality of functions between the plurality of nodes in the communications network.

A method includes determining, by one or more processing entities associated with at least one of: one or more low voltage drive circuits (LVDCs) and one or more other LVDCs, an initial data conveyance scheme and an initial communication scheme for each communication of a plurality of communications on one or more lines of a bus. The method further includes determining a desired number of channels for each communication of the plurality of communications based on the initial data conveyance scheme and the initial communication scheme, a desired total number of channels for the plurality of communications based on the desired number of channels, determining whether the desired total number of channels for the plurality of communications exceeds a total number of available channels. If not, allocating the desired number of channels to each communication of the plurality of communications in accordance with the channel allocation mapping.

The technology relates to allocating the resource costs of a sensor network. In particular, an auction model is used to control the demand-side of sensor network utilization. Users bid for fractional sensor network utilization over particular variables such as time, geography, and data type. During the bidding process, the available sensor network resources may be unknown. Therefore, users bid on the predicted fractional sensor network utilization, which can be estimated using historical sensor network trends and models. Throughout this process, device performance is preserved while providing for user experience, privacy, and security.

Systems and methods for synchronizing cloud resources are disclosed. An example method may include receiving a first request to synchronize first target cloud resources to a first specified state defined in a configuration repository, generating one or more first configuration commands corresponding to the first request, the one or more first configuration commands associated with a first cloud provider and a first cloud configuration framework, and executing the one or more first configuration commands to set a state of the first target cloud resources to the first specified state.

Various approaches for allocating resources to an application having multiple application components, with at least one executing one or more functions, in a serverless service architecture include identifying one or more pods having multiple containers organized as a cluster in a container system capable of executing the function(s); identifying one or more routing paths in the serverless service architecture, the routing path being associated with one or more serverless execution entities capable of executing the function(s) thereon; determining (i) traffic information on the routing path(s), (ii) a cost or a performance characteristic associated with a computer resource bundle for the pod(s), and/or (iii) a cost or a performance characteristic associated with the serverless execution entity(entities); and based thereon, determining whether to (i) terminate execution of the function(s) on the pod(s) and (ii) cause execution of the function(s) on the serverless execution entity (entities).

Examples of the present disclosure describe systems and methods of providing cloud-based activity information. In aspects, a notification may be generated on a client device of a user. The notification may be transmitted to a cloud-based server via an activity feed. The cloud-based server may use the notification to identify a mapping of the user to multiple devices associated with the user. The cloud-based server may then forward the notification to one or more of the identified devices. In at least one example, when the user dismisses the notification using any of the identified devices, the notification is automatically dismissed on the remaining identified devices.

The present disclosure discloses a method and apparatus for changing a resource state, a terminal, and a storage medium, which belong to the field of smart home. A system for changing a resource state that includes a first collection resource, a first intermediate-level resource, and leaf node resources can be established. By making the first collection resource obtain link information of each leaf node resource whose resource state needs to be changed, a request that includes a default interface of the leaf node resource may be generated for the leaf node resource, such that a state of the leaf node resource can be changed accurately by the system. Therefore, the present disclosure enables the control request issued by a client to be recognized and executed by each leaf node resource, thereby increasing reliability and stability of system control.

A virtual data center resource mapping method and device. The method includes: S202: receiving a VDC resource request, where the VDC resource request carries a virtual machine distribution identifier, and the virtual machine distribution identifier is used to indicate a maximum quantity K of virtual machines that can be borne by a single physical server; S204: selecting, from an unmapped virtual machine set Q in the VDC resource request, M virtual machines to form a partition P; S206: selecting a target physical server that can provide a physical resource required by the partition P, and mapping the partition P to the target physical server; and S208: removing, from the set Q, the M virtual machines on which resource mapping has been performed, and repeatedly performing steps 204, 206 and 208 until no virtual machine on which resource mapping has not been performed exists in the set Q.

Methods and systems for introducing self-contained intent functionality into decentralized computer networks is described. Specifically, the methods and systems for encoding user intent (e.g., what functions a value may be used for) into data structures for computer programs and/or transaction protocols intended to automatically execute, control, or record events and actions according to predetermined terms or criteria are described herein. For example, the methods and systems may include using a permission structure native to one or more cryptocurrencies to provide additional functionality that allows for an intent to be introduced into the computer program and/or transaction protocol. This intent may be introduced using a routing data structure indicating exchange eligibility of resource sources.