Leader Confirmation Replication for Millisecond Consensus in Private Chains

TL;DR

This paper introduces Leader Confirmation Replication (LCR), a novel consensus approach for private IoT blockchains that significantly improves transaction throughput and reduces latency by replicating nontransactional data on followers.

Contribution

LCR is a new consensus method that reduces leader network traffic and latency by offloading nontransactional data replication to followers in private IoT chains.

Findings

LCR achieves 1.4X-1.9X higher TPS than Raft.

Transactional response time reduced by 40%-60%.

Network traffic decreases by 20%-30%.

Abstract

The private chain-based Internet of Things (IoT) system ensures the security of cross-organizational data sharing. As a widely used consensus model in private chains, the leader-based state-machine replication (SMR) model meets the performance bottleneck in IoT blockchain applications, where nontransactional sensor data are generated on a scale. We analyzed IoT private chain systems and found that the leader maintains too many connections due to high latency and client request frequency, which results in lower consensus performance and efficiency. To meet this challenge, we propose a novel solution for maintaining low request latency and high transactions per second (TPS): replicate nontransactional data by followers and confirm by the leader to achieve nonconfliction SMR, rather than all by the leader. Our solution, named Leader Confirmation Replication (LCR), uses the newly proposed future log and confirmation signal to achieve nontransactional data replication on the followers, thereby reducing the leader's network traffic and the request latency of transactional data. In addition, the generation replication strategy is designed to ensure the reliability and consistency of LCR when meeting membership changes. We evaluated LCR with various cluster sizes and network latencies. Experimental results show that in ms-network latency (2-30) environments, the TPS of LCR is 1.4X-1.9X higher than Raft, the transactional data response time is reduced by 40%-60%, and the network traffic is reduced by 20%-30% with acceptable network traffic and CPU cost on the followers. In addition, LCR shows high portability and availability since it does not change the number of leaders or the election process.