Federated Learning (FL) has become an essential enabling technology for digital twin in Industrial Internet of Things (IIoT) networks. However, due to the master/slave structure of FL, it is very challenging to resist the single point of failure of the master aggregator and attacks from malicious IIoT devices while guaranteeing model convergence speed and accuracy. Recently, blockchain has been brought into FL systems transforming the paradigm to a decentralized manner thus further improving the system security and learning reliability. Unfortunately, the traditional consensus mechanism and architecture of blockchain systems can hardly handle the large-scale FL task and run on IIoT devices due to the huge resource consumption, limited transaction throughput, and high communication complexity. To address these issues, this paper proposes a two-layer blockchain-driven FL system, called ChainFL, which splits IIoT network into multiple shards as the subchain layer to limit the scale of information exchange, and adopts a Direct Acyclic Graph (DAG)- based mainchain as the mainchain layer to achieve parallel and asynchronous cross-shard validation. Furthermore, FL procedure is customized to deeply integrate with blockchain, and the modified DAG consensus mechanism is proposed to mitigate distortion caused by abnormal models. To provide a proof-of-concept implementation and evaluation, multiple subchains based on Hyperledger Fabric and the self-developed DAG-based mainchain are deployed. The extensive experimental results demonstrated that our proposed ChainFL system outperforms the existing main FL systems in terms of acceptable and fast training efficiency (by up to 14%) and stronger robustness (by up to 3 times).
翻译:联邦学习联合会(FL)已成为工业性物料互联网(IIOT)网络中数字双星的重要赋能技术,然而,由于FL的庞大资源消耗、有限的交易量和高度的通信复杂性,传统共识机制和链链系统结构很难处理大型FL任务并运行在IIOT设备上。为了解决这些问题,本文建议采用双层块链驱动FLL系统,称为链FLL系统,将IIO网络分成多块,作为次链层,以限制信息交流的规模,并采用基于直接环路图(DAG),作为主链层,以实现平行和同步的交叉验证。此外,FL程序以稳定的链链路驱动FL系统向上移动,以大幅整合现有链路段系统内部的自我调节。FLFL程序以快速链路段模式向上移动,以快速链路链路系统为主,以快速和快速链路段为基础,以快速和稳定的系统为基础,以快速、快速的系统为基础,以快速和快速的系统为基础,将FLLAFL系统升级系统升级为多种版本。