Multi-State Merkle Patricia Trie (MSMPT): High-Performance Data Structures for Multi-Query Processing Based on Lightweight Blockchain

Abstract

Blockchain technology has emerged as a promising solution to secure and decentralized platforms. However, blockchain technology has high computational requirements, latency, and low throughput, particularly for single or multi-query processing. Lightweight blockchain has emerged as a solution to overcome these problems. It addresses performance and efficiency issues and can provide convenience in the query process. This paper proposed a novel high-performance data structure for multiquery processing based on a lightweight blockchain, namely Multi-State Merkle Patricia Trie (MSMPT). MSMPT combines Merkle Patricia Trie (MPT) based indexing and linked-list storage to achieve high performance. MPT has been used on the Ethereum network with a Key-Value database approach. The key field in this proposal is used as crucial user data. The value field is changed to the head of the linked list, and the following data elements will store a summary of the data based on the specified category. In this paper, a blockchain simulator was built to discover the performance of the proposed systems. This simulator will simulate creating blocks in a blockchain network using existing and modified blockchain data structures. The blocks created will be compared using the query process from the conventional and proposed systems. The experimental findings demonstrate that MSMPT outperforms existing blockchain-based data structures by requiring only about one millisecond in query processing performance and less than 500 bytes of additional storage. The MSMPT provides a promising solution for efficient and scalable data management in lightweight blockchain, particularly for multi-query processing.