Multi-Device AI Task Routing Across Separate Network Connections
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Solution Overview
Problem
The varying machine performance and computing power limitations of AI devices result in inconsistent reasoning capabilities and efficiency, making it difficult for users to implement local AI reasoning functions effectively.
Innovation Solution
A data processing method that enables a client device to establish connections with a device group, determine a target processing device based on device information, and transmit tasks through different connections for secure and efficient processing, utilizing AI reasoning capabilities of multiple devices within the same or different networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If local AI reasoning is implemented on a single device, then privacy and security are improved, but computing power limitations and power consumption constraints make it difficult to achieve effective reasoning functionality
Solution Approach 1:
The system divides the AI reasoning task into segments that can be distributed across multiple processing devices in a device group. Each device handles specific computational workloads, allowing the system to overcome individual device limitations while maintaining local processing for privacy and security.
Solution Approach 2:
Multiple processing devices are combined into a collaborative device group that functions as a unified computing resource. The client device coordinates these multiple devices to collectively provide the computing power needed for effective AI reasoning, while keeping data local.
2Productivity
If AI reasoning capabilities are enhanced by using multiple devices, then reasoning efficiency is improved, but device complexity and connection management become more complicated
Solution Approach 1:
The client device acts as an intermediary that manages connections between the user and multiple processing devices. It handles the complexity of coordinating multiple devices, selecting appropriate devices from the device group, and managing data flow, thereby simplifying the user experience while maintaining high reasoning efficiency.
Solution Approach 2:
The system dynamically selects and assigns processing devices from the device group based on current task requirements, device availability, and performance characteristics. This dynamic allocation optimizes reasoning efficiency while adapting to changing conditions without requiring complex static configuration.
3Reliability
If different connections are used for device group management and task processing, then security and reliability of data transmission are improved, but system complexity increases
Solution Approach 1:
The connection system is segmented into different types: one connection type for device group management and another for task processing. This segmentation allows each connection to be optimized for its specific purpose with appropriate security measures, while the client device coordinates these separate connections to manage overall system complexity.
Data Source
AI summary
A data processing method includes: after establishing a first connection with a first device, obtaining device information of each processing device in a device group where the first device is located; establishing a second connection with a target processing device in the device group based on the device information, and sending a target processing task to the target processing device through the second connection; outputting a target processing result for the target processing task fed back by the target processing device through the second connection, where the first connection is different from the second connection, and the client device and the processing device are in a same network or different networks.