MSLTChain: A Trust Model Based on the Multi-Dimensional Subjective Logic for Tree Sharding Blockchain System

Abstract

Sharding is a popular technology for blockchain systems that addresses scalability while ensuring security and decentralization. However, there are still many issues. Firstly, the existing sharding solutions exhibit a high percentage of cross-shard transactions, which place a substantial burden on system resources and result in a significant degradation of performance. Secondly, none of these solutions adequately accounts for the inherent heterogeneity among nodes, and the interoperability of different nodes is constrained by security concerns, thereby impeding the practical advancement of blockchain applications. In this paper, a novel subjective logical trust-based tree sharding system, MSLTChain, is introduced to alleviate the processing workload of cross-shard transactions. The proposal encompasses a tree sharding structure and a trust management model, enabling the processing and validation of cross-shard transactions within the parent shard. Moreover, an adaptive algorithm is incorporated to dynamically fine-tune scalability, further augmenting system throughput. A subjective logical trust model is employed to portray the heterogeneity between nodes and enhance the system’s security level. The paper also conducts a comprehensive theoretical analysis, evaluating the security, scalability, and performance aspects. Finally, the experimental findings substantiate the capability of MSLTChain to satisfy the dual imperatives of scalability and security within the context of sharding blockchain.