Index data distribution strategy in a distributed network

Abstract

Index data distribution is an important approach that provides parallelism and can improve the usability of a distributed parallel database. B + tree is a storage structure, which perfectly fits for distributed and parallel indexing, and the distributed B + tree is adopted to index the massive and rapidly increasing data available in a distributed network. This paper proposes an index data distribution strategy using distributed parallel B + tree in a distributed network environment. In our proposal, the basic data distribution strategy can improve the efficiency of a query by utilizing a data fragment method based on the scope of value, and the replica distribution can be adjusted dynamically, according to the number of system access. The performance evaluation and experiment results show that this index data distribution strategy can improve the query's efficiency and load balance.