MFSTR-tree:An Spatio-temporal Index for Argo Floats Data
YANG Mingyuan;LIU Haiyan;ZHU Xinming;SU Chenchen;Information Engineering University;Troops 95956;
Management mode of relational database and file type database is difficult to support the data of Argo floats data. Because Argo buoy floats freely with sea current and data volume is huge in scale as the mobile object. In view of the quasi-real-time, massive nature, spatio-temporal variation and other characteristics of Argo ocean buoy data, as well as multiple query application requirements, the advantages and disadvantages of the current space-time indexing method are analyzed. The deficiencies of current spatio-temporal indexing method include:(1) The Argo buoy data has large volume and are observed over a long time span. When a STR-tree index is established on the trajectory of a buoy, the over-long trajectory tends to lead to a high overlap ratio between the MBB of the STR-tree, which further leads to the reduction of search efficiency.(2) The Argo floats data are sampled at different frequencies and with relatively stable frequency, but the influence of the update frequency on index structure optimization is often ignored. Therefore, a hybrid index structure called MFSTRtree with multi-frequency STR-tree index and grid index is proposed. First, the dynamic trajectory beam is used as the leaf node to generate the STR-tree structure in the trajectory beam layer, taking advantage of the flexibility and the less data redundancy of the STR-tree index structure. Then, the improvement of query efficiency is realized by use of the multiple frequencies of the track beam at the sampling point layer according to the construction grid index. The corresponding interpolation algorithm and query algorithm are described in this paper. To verify the construction and query efficiency of MFSTR-tree, a comparison experiment was conducted with HR-tree and STR-tree for Argo floats in 2015 from China Argo real-time data center. The experimental results show that under the premise of guaranteeing construction time efficiency and storage efficiency, HR-tree still maintains natural advantages in single-time query and is much more efficient than the other two. After optimization, the MFSTRtree had efficiency of 40% higher than the general STR-tree. The query efficiency of the HR-tree decreases significantly with the query window size expanded to 4% of the total range. MFSTR-tree is further optimized on the basis of the original STR-tree, which improves the efficiency of the sampling point selection process in the trajectory bundle. Therefore, the advantage is more obvious, and the verification of the algorithm is realized.
【Fund】： 国家自然科学基金项目(41501446);; 地理信息工程国家重点实验室开放基金项目(SKLGIE2015-M-4-3)~~
【CateGory Index】： P715.2
【CateGory Index】： P715.2