Systems and methods for distribution of application logic in digital networks

A system comprising:

• a non-transitory memory;
• and
• one or more hardware processors configured to read instructions from the non-transitory memory, wherein executing the instructions causes the one or more hardware processors to perform operations comprising:
• receiving a request from a first device in a wireless network to initiate a service instance associated with a service, the service instance being associated with application logic;
• identifying a portion of the application logic to distribute to either mobile edge computing (MEC) servers or an internet location, wherein the MEC servers reside in a user plane site that directly services the first device and that is separate from an Internet and the internet location;
• generating an application logic distribution from the request utilizing a machine-learning algorithm that parses the request into multiple parameters and processes the multiple parameters to indicate how to distribute portions of the application logic between the MEC servers and the internet location;
• determining to distribute the portion of the application logic to the MEC servers utilizing the application logic distribution generated by the machine-learning algorithm;
• and
• distributing the portion of the application logic to a first MEC server of the MEC servers to cause the first MEC server to provide the service instance to the first device.

A non-transitory computer readable medium storing instructions that, when executed by one or more hardware processors, cause the one or more hardware processors to carry out operations comprising:

• receiving a request from a first device of a wireless network to initiate a service instance associated with a service, the service instance being associated with application logic;
• identifying a portion of the application logic to distribute to either mobile edge servers or an internet location, wherein the mobile edge servers reside in a user plane site that directly services the first device and that is separate from an Internet and the internet location;
• generating an application logic distribution from the request utilizing a machine-learning algorithm that parses the request into multiple parameters and processes the multiple parameters to indicate how to distribute portions of the application logic between the mobile edge servers and the internet location;
• determining to distribute the portion of the application logic to the mobile edge servers utilizing the application logic distribution generated by the machine-learning algorithm;
• and
• distributing the portion of the application logic to a first mobile edge server of the mobile edge servers to cause the first mobile edge server to provide the service instance to the first device.