Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 409-426 |
| Number of pages | 18 |
| Journal | Computer Journal |
| Volume | 61 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2018 |
Keywords
- indoor query processing
- indoor space
- spatial databases
- trip planning query
Cite this
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Trip Planning Queries in Indoor Venues. / Shao, Zhou; Cheema, Muhammad Aamir; Taniar, David.
In: Computer Journal, Vol. 61, No. 3, 2018, p. 409-426.Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - Trip Planning Queries in Indoor Venues
AU - Shao, Zhou
AU - Cheema, Muhammad Aamir
AU - Taniar, David
PY - 2018
Y1 - 2018
N2 - In this paper, we study a new type of indoor queries, called the indoor trip planning query (iTPQ). We have observed that the existing methods for outdoor spaces cannot be applied directly to indoor spaces, due to the difference in the underlying networks. Outdoor spaces, which are normally represented as spatial road networks, are commonly modelled as a graph. In contrast, indoor spaces have distinct features (e.g. rooms, doors, hallways) that do not exist in road networks. So far, no specific solutions have been proposed for iTPQ. Even if outdoor techniques are revised for iTPQ, they fail to process iTPQ efficiently. In this paper, we propose an indoor-specific technique, based on the indoor VIP-Tree, called the VIP-Tree neighbor expansion (VNE) method, that also includes new pruning techniques in both pre-processing and query processing phases. Our experimental results show that our proposed method VNE outperforms other indoor and outdoor algorithms by several orders of magnitude in terms of processing time with low indexing cost.
AB - In this paper, we study a new type of indoor queries, called the indoor trip planning query (iTPQ). We have observed that the existing methods for outdoor spaces cannot be applied directly to indoor spaces, due to the difference in the underlying networks. Outdoor spaces, which are normally represented as spatial road networks, are commonly modelled as a graph. In contrast, indoor spaces have distinct features (e.g. rooms, doors, hallways) that do not exist in road networks. So far, no specific solutions have been proposed for iTPQ. Even if outdoor techniques are revised for iTPQ, they fail to process iTPQ efficiently. In this paper, we propose an indoor-specific technique, based on the indoor VIP-Tree, called the VIP-Tree neighbor expansion (VNE) method, that also includes new pruning techniques in both pre-processing and query processing phases. Our experimental results show that our proposed method VNE outperforms other indoor and outdoor algorithms by several orders of magnitude in terms of processing time with low indexing cost.
KW - indoor query processing
KW - indoor space
KW - spatial databases
KW - trip planning query
UR - http://www.scopus.com/inward/record.url?scp=85049004951&partnerID=8YFLogxK
U2 - 10.1093/computer_journal/bxx107
DO - 10.1093/computer_journal/bxx107
M3 - Article
VL - 61
SP - 409
EP - 426
JO - Computer Journal
JF - Computer Journal
SN - 0010-4620
IS - 3
ER -