A Smart Contract based Crowdfunding Mechanism for Hierarchical Federated Learning

TL;DR

This paper proposes a blockchain-based crowdfunding mechanism for Hierarchical Federated Learning that incentivizes participation, ensures trustworthiness, and improves social utility through a smart contract and VCG mechanism.

Contribution

It introduces a novel smart contract framework with VCG mechanism for secure, trustworthy crowdfunding in HFL, addressing high training costs and resource sharing.

Findings

Effective improvement in social utility demonstrated

Ensures authenticity and trustworthiness of crowdfunding

Prototype implementation on Ethereum blockchain

Abstract

Hierarchical Federated Learning (HFL) is introduced as a promising technique that allows model owners to fully exploit computational resources and bandwidth resources to train the global model. However, due to the high training cost, a single model owner may not be able to deploy HFL. To address this issue, we develop a smart contract based trust crowdfunding mechanism for HFL, which enables multiple model owners to obtain a crowdfunding model with high social utility for multiple crowdfunding participants. To ensure the authenticity of the crowdfunding mechanism, we implemented the Vickey-Clark-Croves (VCG) mechanism to encourage all crowdfunding participants and clients to provide realistic bids and offers. At the same time, in order to ensure guaranteed trustworthiness of crowdfunding and automatic distribution of funds, we develop and implement a smart contract to record the crowdfunding process and training results in the blockchain. We prove that the proposed scheme satisfies the budget balance and participant constraint. Finally, we implement a prototype of this smart contract on an Ethereoum private chain and evaluate the proposed VCG mechanism. The experimental results demonstrate that the proposed scheme can effectively improve social utility while ensuring the authenticity and trustworthiness of the crowdfunding process.