• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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An investment defined transaction processing optimization
approach with collaborative storage and computation adaptation

DUAN Yucong1,SHAO Lixu1,CAO Buqing2,SUN Xiaobing3,QI Lianyong4   

  1. (1.College of Information and Technology,Hainan University,Haikou 570228;
    2.College of Computer Science and Engineering,Hunan University of Science and Technology,Xiangtan 411201;
    3.College of Information Engineering,Yangzhou University,Yangzhou 225127;
    4.College of Information Science and Engineering,Qufu Normal University,Jining 276826,China)
  • Received:2018-01-15 Revised:2018-04-10 Online:2018-08-25 Published:2018-08-25

Abstract:

Transaction processing technology is a key technology for reporting information consistency and reliability, and determines whether Web services can be applied to ecommerce. Typed resources such as data, information and knowledge are complicated and redundant, resulting in low storage and processing efficiency of resources. Processing of long transactions often lasts for a long time so that the strategy of locking resources cannot always be applied. We propose an investment defined transaction processing approach towards temporal and spatial optimization with collaborative storage and computation adaptation. In terms of resource modeling, resource processing, processing optimization and resource management, we propose a threelayer solution architecture that can be automatically abstracted and adjusted based on expanding the existing concepts of knowledge graph. The architecture includes three layers that are data graph, information graph, and knowledge graph. The key lies in the calculation of type transferring cost and storage cost on the resource storage space of search target resource objects, and the adjustment of the search mechanism and storage scheme of search target resource objects according to users’ investment, thus reducing the temporal complexity of resource searching and spatial complexity of resource storage and optimizing the temporal and spatial efficiency.
 

Key words: resource modeling, knowledge graph, transaction processing, resource optimization