Participants

This sub-section introduces various participants in the FL alliance and their respective roles and workflow.

1. Task Creator

• Stakes and creates a FL task

• Specifies the basic information of a FL task, such as the number of minimum participants, the expected number of rounds, and the initial reward amount in the pool

2. FL Nodes

FL nodes are participants in a decentralised learning system where multiple entities collaboratively train a shared machine learning model without exchanging their local data. These nodes can be any devices or servers contributing computational resources and data to the training process.

FL nodes play critical roles in ensuring the integrity and efficiency of the FL Alliance working process. They are randomly allocated the roles of proposers and voters with the goal of avoiding collusion and other malicious behaviours. By distributing these roles randomly, the system ensures a fair and unbiased approach to model training and evaluation.

Specifically, developers join as FL nodes to collaboratively train a global model while using their local data and computing power. They are randomly allocated the following roles:

• Proposers: Responsible for performing local training using their own data and proposing updates to the global model.

• Voters: Responsible for aggregating local model updates, evaluating the global model, and casting votes to either support or oppose the proposed updates.