Method and apparatus of supervised learning approach for reducing latency during context switchover in 5G MEC

An edge network entity for initiating a context switchover in a wireless network, the edge network entity comprising:

• a memory;
• a processor;
• and
• a multi-access edge computing (MEC) controller, operably connected to the memory and the processor, configured to:
• identify a plurality of first parameters associated with a user equipment (UE) and a plurality of second parameters associated with the edge network entity;
• receive a data path change notification of the UE from a session management entity;
• determine a ranking for each of a plurality of edge application servers (EASs) based on the plurality of first parameters and the plurality of second parameters, in response to reception of the data path change notification;
• select at least one target EAS of the plurality of EASs based on the ranking for each of the plurality of EASs;
• and
• perform the context switchover to the at least one target EAS,
• wherein the ranking for each of the plurality of EASs is determined based on a machine learning for obtaining a correlation of the plurality of first parameters and the plurality of second parameters.

A non-transitory computer readable medium comprising program code for processing a dialog between a user and an electronic device that, when executed by at least one processor, causes an electronic device to:

• identify a plurality of first parameters associated with a user equipment (UE) and a plurality of second parameters associated with the edge network entity;
• receive a data path change notification of the UE from a session management entity;
• determine a ranking for each of a plurality of edge application servers (EASs) based on the plurality of first parameters and the plurality of second parameters, in response to reception of the data path change notification;
• select at least one target EAS of the plurality of EASs based on the ranking for each of the plurality of EASs;
• and
• perform the context switchover to the at least one target EAS,
• wherein the ranking for each of the plurality of EASs is determined based on a machine learning for obtaining a correlation of the plurality of first parameters and the plurality of second parameters.