Systems and methods to reserve resources is provided. In exemplary embodiments, a selection of a profile from a user is received. A dynamic graphical user interface is generated, using one or more processors. The dynamic graphical user interface allows the user to configure a topology based on the selected profile. The dynamic graphical user interface provides input fields in which the user may select a resource. An indication of the selected applicable topology property for configuring the topology is received. A topology is automatically generating based in part on the selected applicable topology property.

A method for managing network slices for the benefit of users monitors and obtains key performance indicators configured by a user, the indicator values being collected in real time and visually presented. When a user wants to optimize the network slices, weightings, value intervals, and variables are applied by the user to target key performance indicators. The network slices are optimized by a particle swarm algorithm configured by the user. A device and a computer readable and permanent storage medium for executing the network slices management method are also disclosed.

A sub-system and method for a media processing system including a first entity and a second entity is provided. The method includes receiving, by the first entity of the media processing system from the second entity of the media processing system, a request, including a parameter having a value, to perform an action with the first entity by using the value of the parameter; and transmitting, by the first entity of the media processing system to the second entity, an acknowledgement that indicates whether the value of the parameter is accepted by the first entity to perform the action.

Systems and methods are disclosed for managing workload among server clusters is disclosed. According to certain embodiments, the system may include a memory storing instructions and a processor. The processor may be configured to execute the instructions to determine historical behaviors of the server clusters in processing a workload. The processor may also be configured to execute the instructions to construct cost models for the server clusters based at least in part on the historical behaviors. The cost model is configured to predict a processor utilization demand of a workload. The processor may further be configured to execute the instructions to receive a workload and determine efficiencies of processing the workload by the server clusters based at least in part on at least one of the cost models or an execution plan of the workload.

Disclosed herein are system, method, and computer program product embodiments for deploying a configurable throttling library in a cloud platform that throttles requests according to fully customizable parameters across each origin and resource. An administrator can harness the full customization provided by the throttling library to specify increment, decrement, delay, threshold, expiration, and rejection policies. These policies allow administrators to specify parameters guiding throttling on a per-user and a per-resource basis, thus providing significantly enhanced configuration capabilities to the administrator to tailor the throttling to the unique requirements of their applications and the usage thereof.

Aspects of the disclosure provide for a method implemented by a smart device executing an artificial intelligence electronic assistant application. In at least some examples, the method includes receiving a request from an appliance in a same local network as the smart device, the request to transfer first data from the appliance to a first device located outside the local network. The method also includes facilitating the transfer of the first data from the appliance to the first device based at least in part on security policies of the smart device and content of the first data.

A resource allocation server including memory circuitry, processor circuitry, and an interface. The resource allocation server is configured to communicate with a plurality of resource allocation servers including a first resource allocation server of a first network. The resource allocation server is configured to receive, from a requester, a first resource allocation request indicative of a resource type. The resource allocation server is configured to negotiate, with the first resource allocation server, an allocation of a resource based on the resource type indicated in the first resource allocation request. The resource allocation server is part of a network different from the first network.

Embodiments of the present disclosure provide a method, a device, and a computer program product for edge resource aggregation. In one embodiment, a second edge device to which data associated with a first edge device will be transmitted is determined in an edge device cluster. Then, the data associated with the first edge device is transmitted to the second edge device. In this way, resources of multiple edge devices may be aggregated, thereby improving network efficiency and stability.

A system to facilitate infrastructure management is described. The system includes a plurality of management controllers each having a control function of a plurality of infrastructure devices and a state cache storing a state of the plurality of infrastructure devices, including a first management controller to initiate an operation to be performed on a first set of resources. The system also includes a plurality of infrastructure controllers, each having a state repository to maintain a state function of the plurality of infrastructure devices, including a first infrastructure controller associated with the first set of resources to perform the operation on the first set of resources, update a first state repository including an updated state of the first set of resources in response to the operation and broadcast the updated state of the first set of resources to each of the plurality of management controllers.

An example computing device is configured to receive, from a customer device, an indication of a plurality of resources and an indication of a plurality of customer services, each of the plurality of customer services being associated with a corresponding at least one requirement and a corresponding at least one constraint. The computing device is configured to automatically determine, for each requirement and each constraint, whether the requirement or the constraint can only be satisfied by a particular resource of the plurality of resources, and allocate, based on the determining, at least one resource of the plurality of resources to at least one customer service of the plurality of customer services. The example computing device is configured to provide, to the customer device and subsequent to the determining for every requirement and for every constraint, information to enable the customer device to provision the at least one customer service.