SYSTEMS AND METHODS FOR DYNAMIC MULTI-ACCESS EDGE ALLOCATION USING ARTIFICIAL INTELLIGENCE

Provided are systems and methods that use artificial intelligence and/or machine learning to dynamically allocate services at different times and at different network edge locations within a Multi-Access Edge (“MEC”) enhanced network based on a multitude of factors that change the priorities of the services at the different times and at the different edge locations. For instance, a MEC controller, controlling the allocation of resources at a particular edge location, may modify the allocation of services at that particular edge location at different times based on time and/or location sensitive events that occur at different times and that relate to different services, changing usage patterns that are derived from prior service utilization, and/or categorization of the services as permanent, time insensitive, or other categories of services with permissions to execute at different times from different edge locations.