18152970. MODEL PROCESSING METHOD FOR CLOUD SERVICE SYSTEM AND CLOUD SERVICE SYSTEM simplified abstract (Huawei Technologies Co., Ltd.)
MODEL PROCESSING METHOD FOR CLOUD SERVICE SYSTEM AND CLOUD SERVICE SYSTEM
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MODEL PROCESSING METHOD FOR CLOUD SERVICE SYSTEM AND CLOUD SERVICE SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18152970 titled 'MODEL PROCESSING METHOD FOR CLOUD SERVICE SYSTEM AND CLOUD SERVICE SYSTEM
Simplified Explanation
The abstract describes a method for processing models in a network architecture involving a cloud server, a local server, and an edge device. The local server obtains a data set from the edge device, which includes data used for computing with a model provided by the cloud server. The local server determines a gradient value based on the edge device's data set and sends it to the cloud server for updating the model.
- The method involves a local server positioned between a cloud server and an edge device.
- The local server collects a data set from the edge device, which is used for computing with a model provided by the cloud server.
- Based on the edge device's data set, the local server determines a gradient value for updating the model.
- The local server sends the gradient value to the cloud server, which uses it to update the model.
Potential Applications
- Edge computing: This method enables efficient processing of models on edge devices, reducing the need for constant communication with the cloud server.
- Internet of Things (IoT): The method can be applied to IoT devices, allowing them to perform local model updates without relying heavily on cloud resources.
- Real-time analytics: By processing models locally, the method enables faster and more responsive analytics on edge devices.
Problems Solved
- Communication overhead: The method reduces the need for frequent data transmission between the edge device and the cloud server, minimizing network latency and bandwidth usage.
- Privacy concerns: By processing models locally, sensitive data remains on the edge device, reducing the risk of data breaches or privacy violations.
- Resource efficiency: The method optimizes resource utilization by distributing model processing tasks between the edge device and the cloud server.
Benefits
- Improved performance: Local model processing reduces latency and enables real-time analytics, enhancing the overall performance of edge devices.
- Enhanced privacy and security: By keeping sensitive data on the edge device, the method mitigates privacy risks and strengthens data security.
- Efficient resource utilization: The method optimizes network bandwidth and reduces the computational burden on the cloud server, leading to more efficient resource allocation.
Original Abstract Submitted
In a model processing method, a first local server which is disposed between a cloud server and an edge device obtains a data set of the edge device. The data set comprises data used when the edge device performs computing by using a first model provided by the cloud server. The first local server determines, based on the data set of the edge device, a first gradient value for updating the first model, and sends the first gradient value to the cloud server for use by the cloud server to update the first model.
