基于多目标离散粒子群优化的云环境下物化视图选择  

Materialized View Selection Based on Multi-objective Discrete Particle Swarm Optimization in Cloud Environment

作　　者：孙洋洋 姚俊萍 李晓军 王伊靖 SUN Yang-yang;YAO Jun-ping;LI Xiao-jun;WANG Yi-jing(Rocket Forece University of Engineering,Xi'an 710025,China)

机构地区：[1]火箭军工程大学,陕西西安710025

出　　处：《中国电子科学研究院学报》2021年第7期661-668,共8页Journal of China Academy of Electronics and Information Technology

摘　　要：针对目前云环境下物化视图选择算法的查询回答性能低下,以及无法同时优化面向企业与消费者的查询回答性能问题,文中开展基于多目标离散粒子群优化的云环境下物化视图选择研究。采用基于多视图处理计划的表式结构进行候选视图的数据结构表示,建立候选视图物化代价模型,设计基于多目标离散粒子群优化的云环境下物化视图选择算法。实验结果表明,文中提出的算法在查询回答性能方面优于现有的算法,实现了同时优化面向企业与消费者的查询回答性能。In view of the low query answering performance of materialized view selection algorithms in cloud environment and the inability to optimize query answering performance for enterprises and consumers at the same time,this paper studies materialized view selection in cloud environment based on multiobjective discrete particle swarm optimization. The table structure based on multi-view processing plan is used to represent the data structure of candidate views,the materialized cost model of candidate views is established,and the materialized view selection algorithm based on multi-objective discrete particle swarm optimization in cloud environment is designed. Experimental results show that the algorithm proposed in this paper is superior to the existing algorithms in query answering performance,and realizes the optimization of query answering performance for enterprises and consumers at the same time.

关 键 词：云环境 物化视图选择 多目标离散粒子群优化 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]