Method And Apparatus For Scalable ML-Based Frameworks For Resource Planning In Enterprise Networks

An apparatus for scalable machine-learning (ML)-based frameworks for resource planning in enterprise networks, wherein the enterprise network comprises a plurality of network elements operating within the enterprise network, and wherein each of the network elements have associated and corresponding resource types, comprising:

• a) an offline component, wherein the offline component identifies acceptable health parameters for each resource type and for each of the network elements;
• b) a first database, wherein the first database stores the acceptable health parameters identified by the offline component;
• c) an Analytics and Recommendation component, operatively coupled to the first database, wherein the Analytics and Recommendation component:
• quantifies the resource health of a selected network element;
• ranks network elements based upon distance metrics between the acceptable health parameters and observed network resource utilization values associated and corresponding to each selected network element;
• ranks factors that negatively impact the resource health of each of the network elements in the enterprise network;
• and provides network planning suggestions and recommendations based upon the ranking of factors;
• d) a second database coupled to the Analytics and Recommendation component, wherein the second database stores output data obtained from the Analytics and Recommendation component;
• and
• e) a User Interface coupled to the second database.

A method of standardizing and ranking network resource issues associated with a plurality of network elements in a wireless Enterprise Network (EN), wherein each network element comprises one of a plurality of network element types, and wherein each network element type has a corresponding and associated set of network resources that each network element type may consume, comprising:

• a) assigning indicator variables (IVs) to associated and corresponding network resources consumed by each network element type, wherein each IV reflects one of the following:
• i. network resource utilization observed at each network element type;
• ii. service rejection count due to resource unavailability at each network element type;
• or
• iii. service preemption count due to resource unavailability at each network element type;
• b) defining standardized values for each IV assigned in step a), wherein the IV values are greater than or equal to 0, and wherein higher IV values indicate that an associated and corresponding network resource is more highly constrained than are network resources having relatively low associated IV values;
• c) ranking factors that negatively impact the resource health of each of the network elements in the enterprise network, wherein the factors are ranked in accordance with how severely the factors impact network performance;
• and
• d) generating network planning suggestions and recommendations to improve network performance of a selected network element, wherein the suggestions and recommendations are based upon the ranking of factors as determined during the step c).