Mobile Location Indexing Based On Synthetic Moving Objects

Abstract

Today, the number of researches based on the data they move known as mobile objects indexing came out from the traditional static one. There are some indexing approaches to handle the complicated moving positions. One of the suitable ideas is pre-ordering these objects before building index structure. In this paper, a structure, a presorted-nearest index tree algorithm is proposed that allowed maintaining, updating, and range querying mobile objects within the desired period. Besides, it gives the advantage of an index structure to easy data access and fast query along with the retrieving nearest locations from a location point in the index structure. A synthetic mobile position dataset is also proposed for performance evaluation so that it is free from location privacy and confidentiality. The detail experimental results are discussed together with the performance evaluation of KDtree-based index structure. Both approaches are similarly efficient in range searching. However, the proposed approach is especially much more save time for the nearest neighbor search within a range than KD tree-based calculation.

Efficient processing of continuous spatial-textual queries over geo-textual data stream

“…Which can be used in online decision making as dynamic data items are generated [37]. A presorted-nearest index tree algorithm is introduced for nearest neighbor queries on mobile objects within desired period and outperformed in saving time compared to KD-tree approach [38]. Vantage point tree indexing with spectral clustering is used for high dimensional data for effective data retrieval for user query [39].…”