Blockchain Storage Optimisation With Multi-Level Distributed Caching

【Author】 Heo, Jun Wook; Ramachandran, Gowri Sankar; Dorri, Ali; Jurdak, Raja

【Source】IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT

【影响因子】4.758

【Abstract】Distribution, security, and immutability have led to the great success of blockchain in many applications, while contributing to major increases in ledger size. The storage challenge is one of the major barriers to the adoption of blockchain in the Internet of Things (IoT), which consists of many resource constrained devices. In this paper, we propose Multi-Level Distributed Caching (MLDC) for blockchain storage optimisation which reduces data replication based on data access patterns in a decentralised manner. For storage optimisation of data-centric blockchains, MLDC introduces a hierarchical storage class (SC), in which every node is assigned to an SC with its own Access Frequency (AF) threshold based on node availability. To reduce the number of replications shared among participant nodes, each node in a SC continues to remove unaccessed data from local storage based on a threshold time determined by the AF threshold of the SC, while maintaining all block hashes for consistency. Eventually, all nodes in MLDC store the most frequently accessed data in their local storage, so MLDC effectively reduces the storage and query costs while minimising network overhead. We also analyse the security of MLDC and quantitatively evaluate its performance for both the uniform access and exponentially decaying access patterns. The evaluation was carried out on a representative blockchain simulator with 15 storage nodes. Our results from 11 hours of experiments producing 6667 blocks and 39997 transactions show good performance for MLDC. The results of the experimentation for the exponentially decaying assess pattern show that MLDC can reduce the total storage cost by 83% compared to conventional blockchain systems, while maintaining blockchain consistency and data availability with a slight increase in network overhead and query cost.

【Keywords】Blockchains; Security; Optimization; Costs; Internet of Things; Computer science; Australia; Blockchain; Internet of Things (IoT); storage optimisation; distributed caching

【发表时间】2022 DEC

【收录时间】2023-05-14

【文献类型】理论模型

【主题类别】

区块链技术-核心技术-存储策略