TY - JOUR
T1 - Towards Indoor Temporal-Variation Aware Shortest Path Query
AU - Liu, Tiantian
AU - Feng, Zijin
AU - Li, Huan
AU - Lu, Hua
AU - Cheema, Muhammad Aamir
AU - Cheng, Hong
AU - Xu, Jianliang
N1 - ©2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. [LIB 2021-11-19]
Funding Information:
This work was supported in part by Independent Research Fund Denmark under Grant 8022-00366B, in part by Australian Research Council under Grants FT180100140 and DP180103411, in part by Hong Kong RGC Projects under Grants 12200817 and C6030-18GF, and in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2019B1515130001.
Publisher Copyright:
© 1989-2012 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - The recent years have witnessed the growing popularity of indoor location-based services (LBS) in practice and research. Among others, indoor shortest path query (ISPQ) is of fundamental importance for indoor LBS. However, existing works on ISPQ ignore indoor temporal variations, e.g., the open and close times associated with entities like doors and rooms. In this paper, we define a new type of query called Indoor Temporal-variation aware Shortest Path Query (ITSPQ). It returns the valid shortest path based on the up-to-date indoor topology at the query time. A set of techniques is designed to answer ITSPQ efficiently. We design a graph structure (IT-Graph) that captures indoor temporal variations. To process ITSPQ using IT-Graph, we design two algorithms that check a door's accessibility synchronously and asynchronously. Furthermore, we propose a novel index structure (IT-Index) that extends the state-of-the-art index significantly by storing dynamic door-to-door distances in a compact distance cube associated with tree nodes. When processing ITSPQ using IT-Index, we make use of the distance cube to avoid time-consuming indoor distance computation on-the-fly. We evaluate the proposed techniques using extensive experiments on synthetic and real data. The results show that our IT-Index based method is the most efficient for processing ITSPQ at a modest cost of index memory consumption.
AB - The recent years have witnessed the growing popularity of indoor location-based services (LBS) in practice and research. Among others, indoor shortest path query (ISPQ) is of fundamental importance for indoor LBS. However, existing works on ISPQ ignore indoor temporal variations, e.g., the open and close times associated with entities like doors and rooms. In this paper, we define a new type of query called Indoor Temporal-variation aware Shortest Path Query (ITSPQ). It returns the valid shortest path based on the up-to-date indoor topology at the query time. A set of techniques is designed to answer ITSPQ efficiently. We design a graph structure (IT-Graph) that captures indoor temporal variations. To process ITSPQ using IT-Graph, we design two algorithms that check a door's accessibility synchronously and asynchronously. Furthermore, we propose a novel index structure (IT-Index) that extends the state-of-the-art index significantly by storing dynamic door-to-door distances in a compact distance cube associated with tree nodes. When processing ITSPQ using IT-Index, we make use of the distance cube to avoid time-consuming indoor distance computation on-the-fly. We evaluate the proposed techniques using extensive experiments on synthetic and real data. The results show that our IT-Index based method is the most efficient for processing ITSPQ at a modest cost of index memory consumption.
KW - indoor space indexing
KW - shortest path query
KW - Temporal variation
UR - http://www.scopus.com/inward/record.url?scp=85105059062&partnerID=8YFLogxK
U2 - 10.1109/TKDE.2021.3076144
DO - 10.1109/TKDE.2021.3076144
M3 - Journal article
AN - SCOPUS:85105059062
SN - 1041-4347
VL - 35
SP - 998
EP - 1012
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
IS - 1
ER -