Embedded Database Query Optimization Algorithm Based on Particle Swarm Optimization

This paper concentrates on the problem of embedded database query optimization, which is a crucial problem in embedded system design. Firstly, we describe the structure of the embedded database system, in which the database engine is a key module in the database system, and it can ensure the database system correctly and efficiently work. Secondly, the embedded database query optimization algorithm based on an improved particle swarm optimization is given. The main innovations of this paper lie in the following aspects: 1) a high inertia weight is used to find new searching space, 2) inertia weight decreases in terms of paths of different values of particle number, 3) final inertia weight is obtained after executing the max number of iterations. Thirdly, to test the effectiveness of our algorithm, we construct an experimental embedded system platform. Compared with the B+Tree, our proposed algorithm can achieve better performance in both space utilization and time cost.