Local Data Stream Acceleration Engine for Real-Time Processing
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Solution Overview
Problem
Traditional front-end devices with limited computing power can only perform data acquisition, leading to non-real-time data processing and high costs due to extensive data transmission to remote servers, especially in scenarios requiring real-time performance and efficient data communication.
Innovation Solution
A local data stream acceleration method that dynamically configures a data stream acceleration engine for preliminary processed data streams, enabling real-time processing and reducing transmission costs by performing software and hardware configurations according to data type and application scenarios, thus eliminating the need for remote data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If data is transmitted to remote servers for processing, then data processing capability is improved, but real-time performance is degraded and transmission costs increase
Solution Approach 1:
The patent segments the data processing system into local front-end devices with acceleration engines and remote servers. The acceleration engine handles time-sensitive data stream processing locally, while the server handles non-time-sensitive batch processing, resolving the contradiction between local real-time performance and remote processing capability
Solution Approach 2:
The acceleration engine acts as an intermediary between the front-end device and remote server. It pre-processes data streams locally to extract essential information, reducing the amount of data that needs to be transmitted to the server while maintaining real-time processing capability
2Power
If data is transmitted to remote servers, then data processing capability is improved, but transmission costs increase
Solution Approach 1:
The acceleration engine extracts essential features and pre-processed results from raw data streams locally, taking out only the necessary information for transmission to the server. This reduces the volume of transmitted data and associated costs while maintaining processing capability
Solution Approach 2:
The system segments processing tasks by urgency and type, handling cost-sensitive real-time processing locally and transmitting only essential data to servers for non-urgent batch processing, thereby reducing transmission costs
3Device complexity
If front-end devices perform only data acquisition, then device complexity is reduced, but productivity is degraded
Solution Approach 1:
The acceleration engine is dynamically configured based on the type of data stream being processed. The system can adaptively adjust the engine's parameters and algorithms to match different data types (audio, video, text, sensor data), providing enhanced productivity without requiring complex manual configuration
Solution Approach 2:
The acceleration engine automatically configures itself based on data stream characteristics, performing self-service without requiring complex external configuration. This maintains device simplicity while enabling advanced processing capabilities through automated adaptation
Data Source
AI summary
Provided are a local data stream acceleration method, a data stream acceleration system, a computer device and a storage medium. The method includes the following: receiving a raw data stream collected by a data acquisition device and performing preliminary processing on the raw data stream; configuring a local data stream acceleration engine, inputting the preliminarily processed raw data stream into the data stream acceleration engine for acceleration processing, and obtaining a result of data stream acceleration processing; and outputting the result of data stream acceleration processing. The data stream acceleration engine is configured dynamically and locally according to the type of the obtained data stream, and the data stream is accelerated by the dynamically configured local data stream acceleration engine.