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\"os-R\'enyi 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流量。在第一个方法中,数学模型为基于“劳动证据”的链条链条链条链条链条链条条条条条条条的最佳交易流量得出了数学模型。在这一方法中,链链条Peper-Peer(P2P)网络被视为“Erd\"os-R\'enyi随机网络地形学”。但这种方法受到区块创建率的限制,结果显示超过最佳点的比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”的最佳交易流量。在这个方法中,我们遵循了两步战略,使系统足够强大,足以应对双端袭击。第一步是开发一个不受监督的图形组合组合算法,用于分离攻击者所创建的区块。第二步是消除攻击区块,其余的区块则由诚实客户按顶部顺序排列,使区块DAG系统能够通过SimLT系统对智能合同应用程序进行重大改进。