Distributed bee colony computing soft chip system

By adopting a distributed swarm computing soft chip system in a distributed computing system, the working mechanism of bee colony is simulated, the tasks are decomposed into small subtasks and distributed control is realized, and the problems of inefficiency and high cost of existing systems in large-scale data processing are solved, and efficient, flexible and reliable distributed computing is achieved.

CN119690680APending Publication Date: 2025-03-25SHENZHEN MORA TECH CO LTD
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Patent Information

Application Number
CN202411919503.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-25
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

Existing distributed computing systems face problems such as data consistency, fault tolerance, load balancing, time synchronization and high maintenance costs when processing large-scale data, resulting in inefficiency and high cost.

Method used

A distributed swarm computing soft chip system is adopted. This system simulates the natural working mechanism of bee colonies and breaks down complex computing tasks into multiple small and independent subtasks (soft chips), and allows each computing node to work efficiently through distributed control and collaboration strategies.

Benefits of technology

It improves the efficiency and accuracy of distributed computing, reduces the computational complexity, enhances the adaptability and autonomy of the system, reduces maintenance costs, and makes it more suitable for super-large-scale distributed computing scenarios.

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Abstract

A distributed bee colony computing soft chip system disclosed by the present invention comprises a data collection layer, a data processing layer, a feature engineering layer, a model training layer and a credit scoring layer, the output end of the data collection layer is in one-way connection with the data processing layer, and the output end of the data processing layer is in one-way connection with the feature engineering layer. The method has the advantages that the distributed bee colony calculation soft chip can effectively solve the problems of distributed calculation efficiency and precision. In the distributed scheduling problem, the distributed bee colony computing soft chip can fully utilize cluster resources, and the production efficiency is improved. And the algorithm structure is realized and improved by calculating automatic atomization division of labor, so that the calculation complexity of the distributed algorithm is reduced, and the method is more suitable for a super-large-scale distributed calculation scene. The distributed bee colony computing soft chip can fully utilize distributed resources in a complex environment, the adaptability of distributed computing is improved, and the cost of the distributed computing is reduced.
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