DRDST: Low-latency DAG Consensus through Robust Dynamic Sharding and Tree-broadcasting for IoV

TL;DR

This paper introduces DRDST, a low-latency DAG consensus protocol for IoV that employs robust dynamic sharding and tree-broadcasting to improve scalability, reduce latency, and efficiently handle cross-shard transactions in highly dynamic networks.

Contribution

The paper presents a novel DAG consensus scheme with a robust sharding model and optimized broadcast method tailored for IoV, addressing mobility and latency challenges.

Findings

DRDST outperforms existing schemes in latency and throughput.

The robust sharding model improves network stability and consensus success rate.

Optimized tree-broadcast reduces maximum broadcast latency within shards.

Abstract

The Internet of Vehicles (IoV) is emerging as a pivotal technology for enhancing traffic management and safety. Its rapid development demands solutions for enhanced communication efficiency and reduced latency. However, traditional centralized networks struggle to meet these demands, prompting the exploration of decentralized solutions such as blockchain. Addressing blockchain's scalability challenges posed by the growing number of nodes and transactions calls for innovative solutions, among which sharding stands out as a pivotal approach to significantly enhance blockchain throughput. However, existing schemes still face challenges related to a) the impact of vehicle mobility on blockchain consensus, especially for cross-shard transaction; and b) the strict requirements of low latency consensus in a highly dynamic network. In this paper, we propose a DAG (Directed Acyclic Graph) consensus leveraging Robust Dynamic Sharding and Tree-broadcasting (DRDST) to address these challenges. Specifically, we first develop a standard for evaluating the network stability of nodes, combined with the nodes' trust values, to propose a novel robust sharding model that is solved through the design of the Genetic Sharding Algorithm (GSA). Then, we optimize the broadcast latency of the whole sharded network by improving the tree-broadcasting to minimize the maximum broadcast latency within each shard. On this basis, we also design a DAG consensus scheme based on an improved hashgraph protocol, which can efficiently handle cross-shard transactions. Finally, the simulation proves the proposed scheme is superior to the comparison schemes in latency, throughput, consensus success rate, and node traffic load.