Patent ID: 11928715
Assignee: BESPIN GLOBAL INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system for purchasing a reserved instance from a reserved instance providing system and reselling the reserved instance to a client, the system comprising:
a processor; and
a memory configured to store program instructions,
wherein the program instructions, when executed by the processor, implements:
a learning module configured to generate a machine learning model by analyzing data;
an instance usage prediction module configured to predict instance usage of a client using the machine learning model pre-trained through the learning module in relation to the instance usage of the client who is to sell a reserved instance;
a reserved instance purchase quantity determination module configured to determine a reserved instance purchase quantity based on the instance usage;
a reserved instance purchase module configured to purchase the reserved instance based on the reserved instance purchase quantity; and
an instance reselling module configured to resell the purchased reserved instance to the client,

wherein the instance usage prediction module comprises:
an error analysis module configured to calculate weight for a plurality of machine learning models by analyzing predicted errors of the plurality of machine learning models; and
an instance usage estimation module configured to estimate the instance usage of the client by adjusting a reflection ratio of each of the machine learning models for the instance usage based on the weight for the machine learning models,
wherein the learning module is configured to generate the machine learning model by extracting variables, comprising a use pattern and the number of clients for each operating system (OS) of the instance, for each instance type, for each region, and for each available area, from learning data comprising past on-demand request data requested by the client, and
wherein the learning module is configured to generate:
a generalized linear regression (GLR) model for predicting the instance usage using the usage pattern and the number of clients for each OS, for each instance type, for each region, and for each available area as independent variables,
a multivariate spline regression (MSR) model for predicting the instance usage by applying a smoothing function to the independent variables,
a long short term memory (LSTM) model for predicting a future instance use time pattern from a past instance use time pattern, and
a multivariate regression (MR) model for predicting the instance usage through deep learning based on the independent variables.