基于查询优化策略的语义缓存谓词化简  

Predicate Simplification Based Query Optimization Strategy for Semantic Caching

作　　者：李东[1] 陈锐[1] 徐扬[1] 

机构地区：[1]华南理工大学软件学院

出　　处：《电子学报》2013年第10期2021-2028,共8页Acta Electronica Sinica

基　　金：国家自然科学基金重大项目(No.71090403);国家留学基金委留学回国人员科研启动基金项目(No.B7110020);广州市科技局应用基础研究项目(No.B2111420)

摘　　要：语义缓存技术可以有效地支持移动计算应用.现有的语义缓存查询处理算法在时空效率和裁剪的复杂度上较高,限制了语义缓存的实用性.为此,本文提出20条逻辑规则和语义缓存动态合并策略,来降低查询裁剪的复杂性.在Android系统上的实验表明,在简单查询下,采用全合并的缓存管理策略和谓词析取式优化算法相结合的方法,能较好地优化查询处理.在复杂查询方面,基于谓词复杂度的语义缓存动态合并策略能很好地平衡缓存与查询两端的谓词复杂度,有效地提高语义缓存的查询处理效率.The semantic caching can efficiently support the applications in the context of mobile computing. Most existing al- gorithms for query trimming suffer high time and space complexity and they can＇ t be used in small mobile devices. To this end, we propose 20 rules and a dynamic semantic merging strategy to simplify the complexity of query trimming, which is me^ured by the numbers of predicates that are depicted in the description for the semantic cache or queries. Some expe ＇nments on Android system show that disjunction simplification algorithm along with Completive Merging strategy can get the best performance for simple queries among the alternatives. For complex queries, the dynamic merging strategy based on predicate simplification can balance the complexity between caches and query processing and gain a good performance in a wide range.

关 键 词：语义缓存 查询优化 查询裁剪 谓词化简 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]