Research On Processing Of Geographical Semantic Data Based On P2P Network

Semantic technology can search information more intelligently and accurately,and it can assist researchers to make scientific decisions.Therefore,this technology has been introduced into geographic information processing and formed a RDF(Resource Description Framework)oriented geo-query language GeoSPARQL.However,the existing application platforms based on geographic semantic information processing adopt centralized storage and retrieval services,which will cause the disadvantages of single node failure and poor scalability.Although researchers have proposed a variety of methods to use peer-to-peer network to improve the reliability and scalability of application systems,these methods have not considered the characteristics of geographic semantic data.In view of the above problems,this thesis considers the feature of geographical semantic data and stores semantic data on the peer-to-peer networks,so as to improve the retrieval efficiency of geographic semantic data.To solve the problem of processing the geographical semantic data in the peer-to-peer network,this thesis proposes storage schemes for geographic semantic data based on a variety of pee-to-peer networks.In order to solve the problem of low efficiency of the retrieval of the semantic data,this thesis proposes a storage scheme that stores all triples related to a geographic object together in a node,and we design and implement the methods for storing triples in the peer-to-peer network based on the location of geographical objects.At the same time,we design and implement the geo semantic query mechanism based on distributed semantic storage.According to the types of geo semantic queries,this mechanism can query single object geographic information,multiple objects topological relations and so on.In this thesis,we design several sets of experiments and analyze the results.The results show that the proposed geographic semantic data processing schemes based on Chord and CAN can be used in large-scale network.In addition,for the problem of uneven data distribution in the geo-semantic processing scheme based on CAN,we also propose an optimization scheme and the experiment shows that the optimization can effectively balance the load of nodes.For the single object geographic information query and the multiple objects topological relation match,Chord-based geographic semantic data processing scheme has higher query efficiency.By mapping the real geographic information to two-dimensional space,CAN-based scheme preserves the position of geographic objects when storing geographic data,so that the scheme not only has good scalability,but also is more efficient than other schemes for querying topology relations.