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.

Providing users with smooth and reliable applications in a cloud based setting is a desirable goal. An approach to pre-allocating cloud computing resources may be provided to improve user experience. A user device may monitor an environment for individual user behaviors with visual and/or audio sensors. Based on data from the visual and/or audio sensors individual behaviors may be identified. Individual behaviors may be identified and associated with a cloud computing resource request. Computing resources in the cloud may be reserved or pre-allocated based on the cloud computing resource request. The pre-allocated computing resources can improve user experience through reduced wait time and improve initial cloud-based application response.

Methods and systems are disclosed for improvements in cloud services by sharing estimated and actual usage data of cloud services recipients with the cloud services provider. The sharing of this data allows the cloud services provider to better apportion cloud resources between multiple cloud services recipients. By analyzing information included in the shared data (e.g., information about one or more applications that use the cloud resources), the cloud services provider may categorize the applications and/or the functions of those applications into authorized and unauthorized uses, the determination of which, is used to further efficiently apportion the cloud services resources.

Cloud infrastructure planning systems and methods can utilize artificial intelligence/machine learning agents for developing a plan of demand, plan of record, plan of execution, and plan of availability for developing cloud infrastructure plans that are more precise and accurate, and that learn from previous planning and deployments. Some agents include one or more of supervised, unsupervised, and reinforcement machine learning to develop accurate predictions and perform self-tuning alone or in conjunction with other agents.

Modifying quality of service treatment for data flows A method of transmitting a data flow via a network is disclosed where the network supports transmission of data in accordance with a plurality of Quality of Service, QoS, models. Prior to transmission of the data flow, a client system configures a first class of service for the data flow based on a first QoS model, and a first portion of the data flow is transmitted through the network in accordance with the first class of service. In response to detecting a renegotiation condition, the network communicates with the client system to configure a second class of service for the data flow based on a second QoS model, and a subsequent portion of the data flow is transmitted through the network using the second class of service.

A RAN node may determine an aggregate signal-to-noise ratio (SNR) of each resource block of a plurality of resource blocks, where the aggregate SNR of a given resource block of the plurality of resource blocks is based on SNRs of subcarrier frequencies of the given resource block. The RAN node may determine, based on a type of network traffic on each network slice of a plurality of network slices, an index value of each network slice of the plurality of network slices. The RAN node may map, based on the aggregate SNR of each resource block, based on the index value of each network slice, and for each resource block of the plurality of resource blocks, a resource block of the plurality of resource blocks to a network slice of the plurality of network slices.

In a computing environment, a set of executing processes each having associated resources are provided. Aggregate resources for the computing environment include multiple different types of resources. A utilization level for each of the resources within the computing environment is evaluated to determine an unconsumed capacity for each of the resources below a utilization threshold. The utilization threshold is resource-dependent. An indication of at least a portion of unconsumed capacity for each of the resources below the utilization threshold is gathered. The unconsumed portion for each of the resources below the utilization threshold is exposed for consumption by other executing processes.

Systems and methods for managing 5G networks are provided. A method for injecting analytics into a Network Repository Function (NRF) for managing a 5G slice, according to one implementation, includes a first step of obtaining parameters associated with User Plane (UP) traffic and Control Plane (CP) traffic from a Service-Based Architecture (SBA) of a 5G network. The method also includes the step of performing analytics on the obtained parameters to monitor Network Functions (NFs) associated with the 5G network. In addition, the method includes the step of providing results of the analytics to an NRF to control NFs stored in a repository associated with the NRF.

Systems and methods related to resource distribution for a fleet of machines are disclosed. A system may include a fleet of machines each having an associated resource capacity and a resource requirement to perform a task. The system may further include a controller having a resource requirement circuit to determine an aggregated amount of the resource requirement and an aggregated amount of the resource capacity. A resource distribution circuit may adaptively improve, in response to an aggregated amount of the resource capacity, an aggregated resource delivery of the resource.

As described herein, a system, method, and computer program are provided for orchestrating re-provisioning of network subscriber dedicated network slices. A request is received from an entity for use of a network. Network slice information indicating a plurality of slices of the network dedicated to a plurality of network subscribers is accessed. Provisioning of one of more slices of the plurality of slices to the entity is orchestrated, according to the request.