System and method for online constraint optimization in telecommunications networks

    公开(公告)号:US11954177B2

    公开(公告)日:2024-04-09

    申请号:US17101258

    申请日:2020-11-23

    CPC classification number: G06F18/2431 G06F18/285

    Abstract: Systems and methods described herein provide an online constraint optimizing service that evaluates user requests and inquiries for telecommunications services in the context of a real-time constraint-based analysis. According to an implementation, a network device receives a function for an analytic event and a constraint. The function applies different user attributes for a telecommunications network. The network device generates a training data set using offline constrained optimization of the function. The network device develops a predictive model for utilization of network resources in the telecommunications network using the training data set. The network device receives a user request that corresponds to the analytic event addressed by the predictive model and conducts an online prescriptive analysis using the predictive model. The network device optimizes allocation of the network resources to the user based on the prescriptive analysis. The network device monitors the model recommendations and adapts the predictive model for concept drift while maintaining the constraint.

    SYSTEM AND METHOD FOR ONLINE CONSTRAINT OPTIMIZATION IN TELECOMMUNICATIONS NETWORKS

    公开(公告)号:US20220164593A1

    公开(公告)日:2022-05-26

    申请号:US17101258

    申请日:2020-11-23

    Abstract: Systems and methods described herein provide an online constraint optimizing service that evaluates user requests and inquiries for telecommunications services in the context of a real-time constraint-based analysis. According to an implementation, a network device receives a function for an analytic event and a constraint. The function applies different user attributes for a telecommunications network. The network device generates a training data set using offline constrained optimization of the function. The network device develops a predictive model for utilization of network resources in the telecommunications network using the training data set. The network device receives a user request that corresponds to the analytic event addressed by the predictive model and conducts an online prescriptive analysis using the predictive model. The network device optimizes allocation of the network resources to the user based on the prescriptive analysis. The network device monitors the model recommendations and adapts the predictive model for concept drift while maintaining the constraint.

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