In this paper, we propose two models for scaling the transaction throughput in Proof-of-Work (PoW) based blockchain networks. In the first approach, a mathematical model has derived for optimal transaction throughput for PoW based longest chain rule blockchain. In this approach, the blockchain Peer-to-Peer (P2P) network is considered as Erd \"o s - R \'e nyi random network topology. This approach is however limited by the block creation rate, the results suggest that the rate beyond an optimal point can result in unfairness in the system. The second approach is a new consensus protocol proposed by considering the ledger as a Directed Acyclic Graph (DAG) called blockDAG instead of a chain of blocks. In this framework, we follow a two-step strategy that makes the system robust enough to handle the double-spend attacks. The first step involves the development of an unsupervised learning graph clustering algorithm for separating the blocks created by an attacker. In the second step, the attackers blocks are eliminated and the remaining blocks are arranged in topological order by honest clients which makes the blockDAG system suitable for smart contract applications found in Internet of Things (IoT) services. The Simulation results demonstrate a significant improvement in the transaction throughput compared to bitcoin.
翻译:在本文中,我们提出了两个模型,用于在基于“劳动证据”的链条网络中扩大交易吞吐量。在第一个方法中,一个数学模型为基于“劳动证据”的链条链条链条链条链条条条条条条条的最佳交易吞吐量提供了最佳交易吞吐量。在这个方法中,链链链Per-Peer(P2P)网络被视为“Erd \'o s - R\'e ne nyi 随机网络地形学 ” 。这个方法受到区块创建率的限制,结果显示超过最佳点的费率可能导致系统不公平。第二个方法是将分类账视为“直接循环图”而称之为“块DAG”(DAG),而不是“块链条”。在这个方法中,我们遵循一个两步战略,使系统足够强大地能够处理双盘袭击。第一个步骤是开发一种不统一的学习图形组合算法,用于分离攻击者所创建的区块。在第二步中,攻击者区块会被消灭,其余的区块则由诚实的客户按顶部顺序排列为表顺序排列成一个,使BAGUAG系统能够通过SimcoI Leval的系统对智能合同应用。