StreamNet: A DAG System with Streaming Graph Computing

• DOI: 10.48550/arxiv.1908.06405
• Publication Date: 2019-01-01
• Authors: Zhaoming Yin; Anbang Ruan; Ming Wei; Huafeng Li; Kai Yuan; Junqing Wang; Yahui Wang; Ming Ni; Andrew Martin
• Keywords: FOS: Computer and information sciences; Computer Science - Distributed, Parallel, and Cluster Computing; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; Distributed, Parallel, and Cluster Computing (cs.DC)

To achieve high throughput in the POW based blockchain systems, researchers proposed a series of methods, and DAG is one most active promising fields. We designed implemented StreamNet, aiming to engineer scalable endurable system. When attaching new block DAG, only two tips are selected. One parent tip whose definition same as Conflux[1]; another using Markov Chain Monte Carlo (MCMC) technique by which IOTA [2]. infer pivotal chain along path each epoch graph, total order graph could be calculated without centralized authority. scale up, we leveraged streaming property; transaction validation speed will achieved even if growing. out, direct signal gossip protocol help disseminate updates network, such that messages can passed network more efficiently. our system on IOTA's reference code (IRI) ran comprehensive experiments over different sizes clusters multiple topologies.