Data Processing Queue Sorting for Validity and Overhead Reduction
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Solution Overview
Problem
Existing data sharing technologies face challenges in ensuring data validity while managing system resource occupancy and network overhead, as they either restrict data size, leading to incomplete data transmission, or transmit all data, resulting in excessive resource usage.
Innovation Solution
A method that acquires and processes user data queues based on user correlation relationships, sorting and marking data to ensure relevance and validity, with a focus on transmitting only valid data, using a Redis database and timestamp management to reduce unnecessary data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all data is transmitted during data exchange, then data completeness is improved, but system resource occupancy and network overhead increase
Solution Approach 1:
The patent extracts and transmits only the necessary and valid data from the user data queue based on correlation relationships, rather than transmitting all data. This extraction principle resolves the contradiction by separating essential data from redundant data, ensuring data completeness for relevant information while reducing overall data volume to minimize system resource occupancy and network overhead.
Solution Approach 2:
The patent applies partial action by transmitting a subset of data that is sufficient to meet user needs without transmitting the entire data set. By using correlation relationships to identify and transmit only the necessary portion of data, the system achieves adequate data completeness while avoiding the excessive resource consumption that would result from transmitting all available data.
2Adaptability or versatility
If data sharing is based on data coexistence, then data availability is improved, but cache occupancy and bandwidth consumption increase
Solution Approach 1:
The patent extracts only the relevant data entries from the user data queue based on correlation relationships with the requesting user. This extraction ensures that data is available for sharing when needed (improving data availability) while transmitting only the necessary portion, thereby reducing cache occupancy and bandwidth consumption compared to sharing all coexisting data.
Solution Approach 2:
The patent applies local quality by tailoring the data transmission to the specific needs of each requesting user based on their correlation relationships. Instead of uniformly sharing all data with all users, the system selectively transmits data that is locally relevant to each user, improving data availability for relevant information while reducing overall cache occupancy and network bandwidth usage.
3Reliability
If user data queue is sorted and marked with user information, then data validity is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary sorting and marking of the user data queue with user information before data transmission. This preliminary action ensures that data validity is improved by organizing and identifying relevant data in advance based on correlation relationships. The preprocessing work is done once when data is received, which reduces the complexity of subsequent data retrieval and transmission operations.
Solution Approach 2:
The sorting and marking process creates a structured data queue that provides feedback on data relevance and validity. By marking data with user information and organizing it according to correlation relationships, the system establishes a feedback mechanism that automatically identifies valid data for transmission, improving data reliability while the structured approach actually reduces processing complexity for subsequent operations compared to unstructured data handling.
Data Source
AI summary
A method, device and terminal for data processing are described. The method includes receiving a data exchange request, acquiring a responding user data queue corresponding to a requesting user according to a user correlation relationship, sorting and marking the responding user data queue with responding user information; converting the responding user data queue into a requesting user data queue, sorting and marking the requesting user data queue with requesting user information; and transmitting the requesting user data queue to a user terminal.