Tree Index Nearest Neighbor Search of Moving Objects along a Road Network

Abstract

With the widespread application of location-based service (LBS) technology in the urban Internet of Things, urban transportation has become a research hotspot. One key issue of urban transportation is the nearest neighbor search of moving objects along a road network. The fast-updating operations of moving objects along a road network suppress the query response time of urban services. Thus, a tree-indexed searching method is proposed to quickly find the answers to user-defined queries on frequently updating road networks. First, a novel index structure, called the double tree-hash index, is designed to reorganize the corresponding relationships of moving objects and road networks. Second, an index-enhanced search algorithm is proposed to quickly find the k -nearest neighbors of moving objects along the road network. Finally, an experiment shows that compared with state-of-the-art algorithms, our algorithm shows a significant improvement in search efficiency on frequently updating road networks.

Exploiting hashing for concurrent query processing and indexing of current location of moving objects

“…2. Most of the indices in the literature utilize separate structures for handling updates and query operations, [7][8][9] updates are processed in batch and indices are eventually updated. In contrast to it, in this article, we are interested to explore those indices that use same structure for handling both the query and update operations.…”

“…Details of query operations with respect to timelines is discussed in Table 2.Further, the data model supported by most of the tree‐based solutions comprises of lines (to represent trajectories) and polygons (to represent regions). Our scope is primarily on data model consisting of points. Most of the indices in the literature utilize separate structures for handling updates and query operations, 7–9 updates are processed in batch and indices are eventually updated. In contrast to it, in this article, we are interested to explore those indices that use same structure for handling both the query and update operations.…”