In-path Oracles for Road Networks
Abstract
Many spatial applications benefit from the fast answering of a seemingly simple spatial query --- ``Is a point of interest (POI) `in-path’ to the shortest path between a source and a destination?’’ In-path in this case refers to POI that are either on the shortest path or can be reached within a bounded yet small detour of the shortest path. The fast answering of the in-path queries is contingent on being able to determine if a POI is in-path or not without having to compute the shortest paths during run-time. Thus, this requires a precomputation solution.
The key technical solution is the development of an in-path oracle that is based on precomputation which records pairs of sources and destinations that are in-path with respect to the given POI location. For a given road network with $n$ nodes and $m$ POIs, a $O(m \times n)$-sized oracle is envisioned based on the reduction of Well-Separated pair decomposition of the road network. Furthermore, the oracle can be indexed in a database using a B-tree and hundreds of thousands of in-path queries per second can be answered. Experimental results on real road network POI dataset showcase the superiority of this technique compared to a suitable baseline. The proposed approach can answer 1.5 million in-path queries/second compared to the few hundreds per second with existing approaches.
The key technical solution is the development of an in-path oracle that is based on precomputation which records pairs of sources and destinations that are in-path with respect to the given POI location. For a given road network with $n$ nodes and $m$ POIs, a $O(m \times n)$-sized oracle is envisioned based on the reduction of Well-Separated pair decomposition of the road network. Furthermore, the oracle can be indexed in a database using a B-tree and hundreds of thousands of in-path queries per second can be answered. Experimental results on real road network POI dataset showcase the superiority of this technique compared to a suitable baseline. The proposed approach can answer 1.5 million in-path queries/second compared to the few hundreds per second with existing approaches.