计算机工程与应用2017，Vol.53Issue(21)：24-31,53,9.DOI:10.3778/j.issn.1002-8331.1706-0426
双目标优化的RDF图分割算法
RDF graph partitioning algorithm based on double objective optimization
摘要
Abstract
Distributed storage is a more effective method for the mass data storage. And, the data partitioning is the premise of distributed storage. In facing of the growing semantic web data, RDF Graph Partitioning algorithm is proposed by Double Objective Optimization(RGPDOO). RGPDOO fuses edge cut and load balancing together to get an objective function. According to this objective function, RGPDOO achieves static and dynamic partitioning of RDF graph. For the static partitioning, an initial partitionis executed to divide the node into three kinds:kernel nodes, boundary nodes and freedom nodes. And then, the boundary and freedom nodes are distributed to apartition with the max gain of objective function. For the dynamic partitioning, the insertion and deletion solution of triples are given by the objective function. And, RGPDOO will execute a dynamic adjustment at a certain time interval according to the balance and tightness of partitioning subgraph to satisfy the partitioning object. Finally, the algorithm is tested on synthetic and real datasets in comparison with several general graph partitioning algorithms. The experimental results show that RGPDOO is more suitable for RDF graph partitioning.关键词
RDF图/静态分割/动态分割/边割/负载均衡Key words
RDF graph/static partitioning/dynamic partitioning/edge cut/load balancing分类
信息技术与安全科学引用本文复制引用
陈志奎,冷泳林..双目标优化的RDF图分割算法[J].计算机工程与应用,2017,53(21):24-31,53,9.基金项目
国家自然科学基金(No.U1301253,No.61672123) （No.U1301253,No.61672123）
广东省科技计划(No.2015B010110006) （No.2015B010110006）
国家重点研发计划(No.2016YFD0800300) （No.2016YFD0800300）
辽宁省博士科研启动基金项目(No.201601348,No.201601349). （No.201601348,No.201601349）
