A computer network optimization methodology is disclosed. In a computer-implemented method, components of a computing environment are automatically monitored, and have a feature selection analysis performed thereon. Provided the feature selection analysis determines that features of the components are in frequent communication and generating network latency. Provided the feature selection analysis determines that features of the components are not well defined, a similarity analysis of the features is performed. Results of the feature selection methodology are generated, and the components involved in the network traffic latency are reassigned to migrate the latency.

A method provides an information centric network with a software defined network based on an information centric networking protocol on top of a physical network based on an internet protocol. A controller in the software defined network receives a first packet of an object request in the information centric network. The controller encodes a message ID indicating an object source of the object request into a header of the first packet. The controller installs forwarding rules on forwarding elements in the physical network such that further packets of the object request are forwarded according to the installed forwarding rules by the forwarding elements rewriting headers of the further packets.

A system receives, from one or more subsystems, one or more predicted outcomes associated with a device. The system provides provide at least a subset of the predicted outcomes as input to a machine learning model trained to identify a set of resolution actions. The system receives, from the machine learning model, the set of resolution actions for the subset of the predicted outcomes, wherein each resolution action in the set of resolution actions is associated with a probability of resolving at least one of the predicted outcomes in the subset of predicted outcomes. The system identifies a first resolution action from the set of resolution actions, wherein the first resolution action has a highest probability of resolving the at least one of the predicted outcomes in the subset of predicted outcomes. The system provides a first instruction to execute the first resolution action.

A system receives, from one or more subsystems, one or more predicted outcomes associated with a device. The system provides provide at least a subset of the predicted outcomes as input to a machine learning model trained to identify a set of resolution actions. The system receives, from the machine learning model, the set of resolution actions for the subset of the predicted outcomes, wherein each resolution action in the set of resolution actions is associated with a probability of resolving at least one of the predicted outcomes in the subset of predicted outcomes. The system identifies a first resolution action from the set of resolution actions, wherein the first resolution action has a highest probability of resolving the at least one of the predicted outcomes in the subset of predicted outcomes. The system provides a first instruction to execute the first resolution action.

Network request data is collected over a time window. The network request data is filtered to generate bypass network traffic records. Network performance categories are generated from the bypass network traffic records. Sufficient statistics of network optimization parameters are calculated for the network performance categories. The sufficient statistics of the network optimization parameters are used to generate network optimization parameters to determine data download performances of web applications.

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.

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.

A computing system implementing an application service can receive network data from computing devices of clients of the application service. The system can determine, from the network data, that a network latency for a subset of the computing devices crosses above a latency threshold. Based on determining that the subset of computing devices utilize a common network service provider, the system can transmit a set of configuration signals to the subset of computing devices, which modify a set of default application configurations of the designated application to compensate for the network latency.

A computing system implementing an application service can receive network data from computing devices of clients of the application service. The system can determine, from the network data, that a network latency for a subset of the computing devices crosses above a latency threshold. Based on determining that the subset of computing devices utilize a common network service provider, the system can transmit a set of configuration signals to the subset of computing devices, which modify a set of default application configurations of the designated application to compensate for the network latency.

A computing system implementing an application service can determine, from a network dataset, that a network latency for a common network service provider crosses an upper latency threshold. Based on this determination, the system can determine a subset of the computing devices that utilize the common network service provider, and transmit a set of configuration signals to the subset of computing devices. The set of configuration signals can modify a set of default application configurations of a designated application to compensate for the network latency.