From c7e5305e835c01f39a0986ded8aae3afb4d735dd Mon Sep 17 00:00:00 2001 From: Wonsuk Lee Date: Thu, 28 Dec 2023 14:40:42 +0900 Subject: [PATCH] Revised texts for overall requirements parts --- reports/index.html | 87 +++++++++++++++++++++++++++------------------- 1 file changed, 52 insertions(+), 35 deletions(-) diff --git a/reports/index.html b/reports/index.html index 261235a..a90f1d6 100644 --- a/reports/index.html +++ b/reports/index.html @@ -450,75 +450,92 @@

Table of Contents

The following requirements have been expressed.

5.2 Device Registration

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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.

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The following requirements have been expressed.

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5.3 Data Upload

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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.

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The following requirements have been expressed.

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5.4 Model Synchronization

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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.

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The following requirements have been expressed.

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5.5 Model Evaluation

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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.

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The following requirements have been expressed.

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5.6 Result Retrieval

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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.

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The following requirements have been expressed.

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5.7 Training Control

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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.

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The following requirements have been expressed.

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5.8 Security and Privacy

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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.

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The following requirements have been expressed.

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5.9 Extensibility and Compatibility

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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.

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The following requirements have been expressed.

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