  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.
