Various methods and systems for implementing request scheduling and processing in a multi-tenant distributed computing environment are provided. Requests to utilize system resources in the distributed computing environment are stored in account queues corresponding to tenant accounts. If storing a request in an account queue would exceed a throttling threshold such as a limit on the number of requests stored per account, the request is dropped to a throttling queue. A scheduler prioritizes processing requests stored in the processing queue before processing requests stored in the account queues. The account queues can be drained using dominant resource scheduling. In some embodiments, a request is not picked up from an account queue if processing the request would exceed a predefined hard limit on system resource utilization for the corresponding tenant account. In some embodiments, the hard limit is defined as a percentage of threads the system has to process requests.

A system for provisioning an elastic computing infrastructure is provided. The system includes a memory and at least one processor coupled to the memory. The system also includes a management component executed by the at least one processor and configured to instantiate an objective object having a resource collection and instructions that specify processing performed by the objective object, the resource collection identifying at least one resource object that controls a capacity of at least one resource provided by at least one computer system, the capacity being sufficient for processing to be performed at a predetermined performance level.

A method of allocating cloud computing resources in a cloud computing environment to a user is disclosed. The method comprises determining a prediction accuracy score for each user indicative of their user predictability, and allocating cloud computing resources to each user dependent on their user predictability.

The present disclosure relates to devices, methods, and computer-readable medium for providing recommendations for alternate resources to use for cloud services. The devices, methods, and computer-readable medium may receive a resource allocation request for a new resource of a computing system and may predict an occurrence of a capacity related allocation for the resource allocation request. The devices, methods, and computer-readable medium may identify alternate resources to use for the resource allocation request and may provide recommendations with the alternate resources.

Device group partitions and a settlement platform are provided. In some embodiments, device group partitions (e.g., partitions of devices based on associated device groups) are provided. In some embodiments, a settlement platform service is provided. In some embodiments, a settlement platform service is provided for partitioned devices. In some embodiments, collecting device generated service usage information for one or more devices in wireless communication on a wireless network; and aggregating the device generated service usage information for a settlement platform for the one or more devices in wireless communication on the wireless network is provided. In some embodiments, a settlement platform implements a service billing allocation and/or a service/transactional revenue share among one or more partners. In some embodiments, service usage information includes micro-CDRs, which are used for CDR mediation or reconciliation that provides for service usage accounting on any device activity that is desired. In some embodiments, each device activity that is desired to be associated with a billing event is assigned a micro-CDR transaction code, and a service processor of the device is programmed to account for that activity associated with that transaction code. In some embodiments, a service processor executing on a wireless communications device periodically reports (e.g., during each heartbeat or based on any other periodic, push, and/or pull communication technique(s)) micro-CDR usage measures to, for example, a service controller or some other network element for CDR mediation or reconciliation.

Technologies for switching network traffic include a network switch. The network switch includes one or more processors and communication circuitry coupled to the one or more processors. The communication circuity is capable of switching network traffic of multiple link layer protocols. Additionally, the network switch includes one or more memory devices storing instructions that, when executed, cause the network switch to receive, with the communication circuitry through an optical connection, network traffic to be forwarded, and determine a link layer protocol of the received network traffic. The instructions additionally cause the network switch to forward the network traffic as a function of the determined link layer protocol. Other embodiments are also described and claimed.

A router architecture that facilitates cloud exchange point routing is disclosed. The architecture relies upon B-nodes to connect branch network to cloud, S-nodes to connect services, and V-nodes to connect cloud to cloud. The nodes can be essentially stateless with node configuration stored outside a router, which facilitates ripping and replacement of nodes. Multiple virtual private clouds can be implemented with respective pluralities of Kubernetes pods and a master Kubernetes cluster. Consumer premises equipment is coupled to a first virtual private cloud that forms a virtual extensible local area network with a second private cloud.

Embodiments of this application disclose a radio frequency resource allocation method, apparatus, device, system, and a storage medium. The method includes: obtaining radio frequency information of an access point AP (for example, RSSI signal strength between the AP and each neighboring AP, and data traffic of the AP in a data collection period), predicting, based on the radio frequency information of the AP, load of the AP that is in target duration after a current moment, and allocating a radio frequency resource to the AP based on the load of the AP. This implementation can reduce actual interference on an entire network and improve user experience.

Systems and methods to support flexible scaling and dynamic resource allocation for virtualized cable data plane applications. The system includes a head end together with a node to provide data to customer devices. A container operating that includes a data plane application that provides packets of data for transmission to the node. The data plane application is instantiated with at least one of a virtual networking function and a computing resource function.

A system for provisioning an elastic computing infrastructure is provided. The system includes a memory and at least one processor coupled to the memory. The system also includes a management component executed by the at least one processor and configured to instantiate an objective object having a resource collection and instructions that specify processing performed by the objective object, the resource collection identifying at least one resource object that controls a capacity of at least one resource provided by at least one computer system, the capacity being sufficient for processing to be performed at a predetermined performance level.