# StreamNet: A DAG System with Streaming Graph Computing

## TL;DR

StreamNet is a scalable DAG-based blockchain system that uses streaming graph computing and efficient gossip protocols to achieve high throughput and decentralized ordering without central authority.

## Contribution

The paper introduces StreamNet, a novel DAG system that combines MCMC tip selection, streaming graph properties, and direct signal gossip for scalable blockchain performance.

## Key findings

- High transaction validation speed in growing DAGs
- Efficient message dissemination via gossip protocol
- Scalable performance demonstrated on multiple network topologies

## Abstract

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