Building Efficient Parallel Endorsement Node on Blockchain Systems

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Yaoyi Deng, Mingxuan Li, Hailong Zhang, Dongdong Huo, Yanqiu Zhang, Shuai Yun, Yu Wang, Zhen Xu

Published: 2023, Last Modified: 12 Jan 2026CSCWD 2023EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: With blockchain technology taking the world by storm, Hyperledger Fabric has large potential for application, but low throughput hinders its development. Especially Fabric endorsement phase serves as the upper process of transaction lifestyle, and its low throughput can diminish the performance of the entire system. In this paper, we focus on performance optimization in the endorsement phase. We design an efficient parallel endorsement node (EPEN) and implement the optimization in two steps. The first is parallel endorsement architecture, which improves the concurrency of endorsements and increases the scalability of peer nodes. Then we propose a load balancing algorithm based on consistent hash and design multilayer consistent hash load minimization (MCHLM) to load balance the chaincode containers and improve its utilization. In addition, we implement these optimizations scheme in Hyperledger Fabric 2.2 LTS and conduct a series of evaluation experiments. The experimental results demonstrated that EPEN improves Fabric system throughput by 204.3% and reduces transaction latency by 77.8%, with a 7.9% increase in CPU overhead.