AdaChain: A Learned Adaptive Blockchain
AdaChain: A Learned Adaptive Blockchain
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DOI：
10.14778/3594512.3594531
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
Chenyuan Wu;Bhavana Mehta;Mohammad Javad Amiri;Ryan Marcus;B. T. Loo
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作者：
Chenyuan Wu;Bhavana Mehta;Mohammad Javad Amiri;Ryan Marcus;B. T. Loo
本文介绍了AdaChain，这是一个基于学习的区块链框架，它自适应地选择最佳的许可区块链架构，以优化动态交易工作负载的有效吞吐量。AdaChain解决了区块链即服务（BaaS）环境中的挑战，其中部署了各种可能的智能合约，具有不同的工作负载特征。AdaChain支持通过使用强化学习来自动适应底层动态变化的工作负载。当一个有前途的架构被确定时，AdaChain会在运行时以安全和正确的方式从当前架构切换到有前途的架构。实验表明，AdaChain可以在不断变化的工作负载下快速收敛到最佳架构，并且在成功提交的事务数量方面显著优于固定架构，同时产生较低的额外开销。
This paper presents AdaChain , a learning-based blockchain framework that adaptively chooses the best permissioned blockchain architecture to optimize effective throughput for dynamic transaction workloads. AdaChain addresses the challenge in 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 secure and correct manner. Experimentally, we show that AdaChain can converge quickly to optimal architectures under changing workloads and significantly outperform fixed architectures in terms of the number of successfully committed transactions, all while incurring low additional overhead.