Identifying upgrades to an edge network by artificial intelligence

A system comprising:

• a processor;
• and
• a computer-readable storage medium communicatively coupled to the processor and storing program instructions which, when executed by the processor, are configured to cause the processor to:
• identify, in a network, a plurality of devices, wherein each device in the network is configured to provide data on at least one other device in the network;
• determine capabilities of each device of the plurality of devices;
• monitor, for each device, capacity information and tasks performed during operation of the network;
• analyze, based on the monitoring, each use of each device, wherein the analysis is configured to generate a Quality of Service (QoS) score for each device and an overall QoS score for the network, and wherein the QoS score for each device represents an effectiveness for each device;
• recommend, in response to the analysis and by a learning model, a first upgrade to the network, wherein the first upgrade is configured to increase an efficiency of the network;
• and
• implement the first upgrade, wherein the implementing includes adding a new device to the network.

A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processing unit to cause the processing unit to:

• identify, in a network, a plurality of devices, wherein each device in the network is configured to provide data on at least one other device in the network;
• determine capabilities of each device of the plurality of devices;
• monitor, for each device, capacity information and tasks performed during operation of the network;
• analyze, based on the monitoring, each use of each device, wherein the analysis is configured to generate a Quality of Service (QoS) score for each device and an overall QoS score for the network, and wherein the QoS score for each device represents an effectiveness for each device;
• recommend, in response to the analysis and by a learning model, a first upgrade to the network, wherein the first upgrade is configured to increase an efficiency of the network;
• and
• implement the first upgrade, wherein the implementing includes adding a new device to the network.