This paper presents AdaChain, a learning-based blockchain framework that adaptively chooses the best permissioned blockchain architecture in order to optimize effective throughput for dynamic transaction workloads. AdaChain addresses the challenge in the Blockchain-as-a-Service (BaaS) environments, where a large variety of possible smart contracts are deployed with different workload characteristics. AdaChain supports automatically adapting to an underlying, dynamically changing workload through the use of reinforcement learning. When a promising architecture is identified, AdaChain switches from the current architecture to the promising one at runtime in a way that respects correctness and security concerns. Experimentally, we show that AdaChain can converge quickly to optimal architectures under changing workloads, significantly outperform fixed architectures in terms of the number of successfully committed transactions, all while incurring low additional overhead.

翻译：本文提出AdaChain，一种基于学习的区块链框架，能够自适应地选择最佳许可型区块链架构，以针对动态交易工作负载优化有效吞吐量。AdaChain解决了区块链即服务（BaaS）环境中的挑战，在该环境中，大量可能的智能合约被部署并具有不同的工作负载特性。AdaChain通过使用强化学习支持自动适应底层动态变化的工作负载。当识别出有潜力的架构时，AdaChain会在运行时从当前架构切换到该有潜力的架构，同时确保正确性和安全性考虑。实验表明，AdaChain能够在变化的工作负载下快速收敛到最优架构，在执行成功提交的交易数量方面显著优于固定架构，且仅引入较低额外开销。