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The following requirements have been expressed.
- - APIs should be accessible through a unified and structured namespace to ensure ease of understanding.
- - APIs should provide operation for cancellation and error handling to improve resilience and controllability.
- - APIs should be designed for supporting compatibility across various platforms and devices.
- - The API architecture should be extensible, allowing for upgrade and management without breaking existing functionality.
+ - APIs should be accessible through a unified and structured namespace to ensure ease of understanding.
+ - APIs should provide operation for cancellation and error handling to improve resilience and controllability.
+ - APIs should be designed for supporting compatibility across various platforms and devices.
+ - The API architecture should be extensible, allowing for upgrade and management without breaking existing functionality.
- The API should allow devices or clients to securely register themselves with the federated learning system.
- The API should allow devices or clients to securely register themselves with the federated learning system.
- The API should provide endpoints for device registration, including necessary parameters and data formats.
-
+ The following requirements have been expressed.
+
+ - The API must provide secure endpoints to support registration for client devices with the server of federated learning system.
+ - The server should validate client credentials and maintain a registry of authorized client devices.
+
- The API should enable clients to securely upload their locally held data to the central server or coordinator for model training.
- It should support various data formats and provide guidelines for data serialization and transmission.
- The API should include endpoints for data submission, metadata specification, and possibly data encryption or anonymization.
-
+ The following requirements have been expressed.
+
+ - The API should enable clients to upload data securely to the server by support encryption mechanism or data anonymization
+ - The API must support multiple data formats to provide efficient data transmission.
+ - The API should provide metadata specification for various data formats.
+
- The API should handle the communication and synchronization of model parameters between the central server and client devices.
- It should provide endpoints for retrieving the current model state, sending model updates from clients to the server, and distributing updated models back to the clients.
- The API should support efficient and secure transmission of model parameters, taking into account bandwidth limitations and data privacy requirements.
-
+ The following requirements have been expressed.
+
+ - The API must offer endpoints for clients to download global model and upload local model updates.
+ - The API must offer endpoints for the server to send back aggregated model updates.
+ - The API should ensure secure and efficient transmission of model parameters (or gradients), considering network status including bandwidth and latency.
+ - The API must facilitate version control of models to manage different iterations of the training process.
+
- The API should include endpoints for clients to request model evaluation on their local data.
- It should support the transmission of evaluation requests and relevant data securely to the server.
- The API should allow clients to retrieve evaluation metrics or results from the server.
-
+ The following requirements have been expressed.
+
+ - The API should allow model evaluation and provide the reports of evaluation results.
+ - The API must enable the server to process evaluation requests on user demand.
+ - The API should ensure that the evaluation metrics are consistent and accurately to measure model performance.
+
- The API should enable clients to retrieve the final trained model or other relevant results from the central server.
- It should provide endpoints for requesting and downloading the trained model or aggregated results.
- The API should ensure secure transmission of results and provide mechanisms for access control to protect sensitive information.
-
+ The following requirements have been expressed.
+
+ - The API must provide secure endpoints for clients to retrieve and search the final model or aggregated results.
+ - The API should support versioning and tracking of different model iterations.
+ - The API must include mechanisms for access control and verification of client authorization.
+
- The API should allow for controlling the federated learning process, such as starting, pausing, or terminating model training.
- It should provide endpoints for managing training sessions, setting training parameters, and monitoring the progress of training.
- The API should support error handling and provide appropriate status codes for different training control operations.
-
+ The following requirements have been expressed.
+
+ - The API should provide endpoints for control model training process including initiating, pausing, and terminating the process.
+ - The API must allow clients and the server to monitor training process and log of training status.
+ - The API should enable dynamic adjustment of training hyper-parameters based on real-time feedback.
+
- The API should incorporate security measures, such as authentication, encryption, and access control, to protect the federated learning system.
- It should ensure the privacy and confidentiality of data during transmission and storage.
- The API should adhere to privacy regulations and best practices for handling sensitive information.
-
+ The following requirements have been expressed.
+
+ - The API must incorporate end-to-end encryption for data and model transmission.
+ - The API should implement robust authentication for client-server interactions.
+ - The API must adhere to data privacy standards and allow for compliance of new regulations.
+
- The API should be designed with extensibility in mind, allowing for the addition of new functionalities or endpoints in the future.
- It should be compatible with existing web standards and frameworks, facilitating integration with different software platforms and tools.
-
+ The following requirements have been expressed.
+
+ - The API should be designed to facilitate the addition of new functionalities or endpoints.
+ - The API must ensure backward compatibility with existing federated learning models and systems.
+ - The API should support integration with a variety web standards, framework, platforms, and tools.
+