Indoor location-based services (LBS), such as POI search and routing, are often built on top of typical indoor spatial queries. To support such queries and indoor LBS, multiple techniques including model/indexes and search algorithms have been proposed. In this work, we conduct an extensive experimental study on existing proposals for indoor spatial queries. We survey five model/indexes, compare their algorithmic characteristics, and analyze their space and time complexities. We also design an in-depth benchmark with real and synthetic datasets, evaluation tasks and performance metrics. Enabled by the benchmark, we obtain and report the performance results of all model/indexes under investigation. By analyzing the results, we summarize the pros and cons of all techniques and suggest the best choice for typical scenarios.
@article{arxiv.2010.03910,
title = {An Experimental Analysis of Indoor Spatial Queries: Modeling, Indexing, and Processing},
author = {Tiantian Liu and Huan Li and Hua Lu and Muhammad Aamir Cheema and Lidan Shou},
journal= {arXiv preprint arXiv:2010.03910},
year = {2020}
}