摘要:区块链技术是目前计算机领域的研究热点，其实现了去中心化，并且能够安全地存储数字信息，有效降低现实经济的信任成本.提出一种区块链存储容量可扩展模型的高效查询方法——ElasticQM.此查询模型由用户层、查询层、存储层和数据层这4个模块组成.在用户层，模型将查询结果缓存，加快再次查询相同数据时的查询速度；在查询层，模型采用容量可扩展区块链模型的全局查询优化算法，增加了查询超级节点、查询验证节点和查询叶子节点这3种节点角色，提高了查询效率；在存储层，模型改进了区块链的容量可扩展模型ElasticChain的数据存储过程，实现了存储的可扩展性，并减少了占用的存储空间；在数据层，提出一种基于B-M树的区块链存储结构，并给出了B-M树的建立算法和基于B-M树的查找算法，基于B-M树的存储结构，区块链会在进行块内局部查找时提高区块链的查询速度.最后，通过在多节点不同数据量的区块链中查询的实验结果表明，ElasticQM查询方法具有高效的查询效率.



Abstract:Blockchain technology is a research hotspot in the field of computers today. The decentralized and secured blockchain data effectively reduces the trust costs of the real economy. This study proposes an efficient query method for the scalable model of blockchain storage capacity-ElasticQM. The ElasticQM query model consists of four layers of modules:user layer, query layer, storage layer, and data layer. The user layer model puts the query results into the cache, which speeds up the query speed when querying the same data again. In the query level, this study proposes a global query optimization algorithm for the scalable blockchain model, which increases the roles of querying super nodes, query verification nodes and querying leaf nodes. It improves the efficiency of global queries. In the storage layer, the model improves the data storage process of the ElasticChain, which supports large scale blockchain. The storage layer achieves the scalability of the blockchain's capacity and reduces the storage space. In the data layer, this study proposes a blockchain storage structure based on B-M tree, and gives the establishment algorithm of B-M tree and search algorithm based on B-M tree. Blockchains based on B-M trees will increase the speed of queries in local search within a block. The experimental results on real datasets show that the ElasticQM model has efficient query efficiency.



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