Scalable processing of multiple continuous k nearest neighbor queries in road networks

In order to efficiently process multiple continuous k nearest neighbor queries in road networks,a scalable processing of multiple continuous queries(SPMCQ) framework is proposed,which exploits pipeline strategy and decomposes the executing progress into three stages: Preprocessing,executing,and dispatching to improve the computing parallelism with multi-threading methods.SCkNN algorithm is presented based on SPMCQ frame using in-memory hash table and linear list structures to store the moving objects and describe the directional model graph respectively.Experimental results show that our algorithm outperforms existing algorithms when processing multiple continuous nearest neighbor queries.