An optimal scheduling algorithm considering the transactions worst-case delay for multi-channel hyperledger fabric network

Abstract

As the most popular consortium blockchain platform, Hyperledger Fabric (Fabric for short) has released multiple versions that support different consensus protocols to address the risks faced in current and future network transactions. For example, Fabric v1.4 and v2.0 use Kafka and Raft mechanisms to complete consensus and ensure that the system can withstand failures such as crashes, network partitions, or network shutdowns. In a multi-channel Fabric network architecture, the system structure cannot guarantee the behavior of malicious nodes. Complex cooperation between peer groups on different channels can greatly affect the security and efficiency of the entire network architecture, which is challenging to estimate and optimize.

To address this challenge, we designed a Drift Plus Penalty Algorithm (DPPA) and a Transaction Worst-case Delay Algorithm (TWDA) based on peer node random scheduling using the Lyapunov optimization framework. The DPPA ensures the stability of the system and provides the maximum transaction processing rate under the minimum safety probability. The numerical results show that this algorithm can achieve a good balance between system security probability and queue accumulation. The TWDA considers discarding transactions with excessively long delay time by setting a worst-case transaction delay threshold. When considering both the security probability and queue accumulation of the Fabric system, the optimal scheduling of peer nodes is given. Numerical simulations were conducted on two types of algorithms, and the results showed that the security of the TWDA was slightly worse than that of the DPPA, but the system queue accumulation was significantly smaller. Therefore, the simulation results not only validate the effectiveness of the two types of algorithms but also provide operators with operational strategies that consider different factors.