Dynamic channel configuration system and method for multi-region short message service

By adopting a dynamic channel configuration system and a hierarchical reinforcement learning model in SMS services, the problem of lack of long-term considerations in channel selection is solved, and more efficient SMS delivery and user satisfaction are achieved.

CN119697604AActive Publication Date: 2025-03-25SIMBA NETWORK TECH (NANJING) CO LTD
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Patent Information

Application Number
CN202510214822.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-26
Publication Date
2025-03-25
Estimated Expiration
2045-02-26

AI Technical Summary

Technical Problem

Traditional SMS services lack consideration for long-term benefits when selecting channels, resulting in current channel selection that may affect future transmission effects.

Method used

The dynamic channel configuration system and method of multi-regional SMS services are adopted, and dynamic channel configuration is realized by obtaining the comprehensive quality indicators of each channel, defining the action space and return function of the agent, and using a hierarchical reinforcement learning model to optimize the channel selection strategy to achieve dynamic channel configuration.

Benefits of technology

It improves SMS delivery rate and timeliness, improves user satisfaction, takes into account long-term returns and local optimization, and overcomes the short-sightedness of traditional methods.

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Abstract

The invention discloses a dynamic channel configuration system and method for multi-region short message service, and relates to the technical field of information transmission, and the method comprises the steps: for each channel, obtaining the average time delay, the short message sending success rate and the average cost of successfully sending 10000 test short messages, calculating a price advantage coefficient, and calculating the comprehensive quality index of each channel; defining a first-layer action space and a second-layer action space based on the comprehensive quality index, defining a state s as a service attribute feature vector of a short message sending task, defining an action a of an intelligent agent, and defining a first-layer return function and a second-layer return function; a hierarchical reinforcement learning model is adopted, a channel cluster selection value function is defined, a channel cluster selection strategy objective function is designed, a channel selection Q value function is defined, a channel selection strategy objective function is designed, and the hierarchical reinforcement learning model is optimized; a channel is distributed for a real-time short message sending task based on a hierarchical reinforcement learning model, and dynamic channel configuration of multi-region short message service is realized.
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