Scalable spatio-temporal continuous query processing for location-aware services

Xiaopeng Xiong, Mohamed Mokbel, Walid G. Aref, Susanne E. Hambrusch, Sunil Prabhakar

Research output: Contribution to journalConference article

32 Citations (Scopus)

Abstract

Real-time spatio-temporal query processing needs to effectively handle a large number of moving objects and continuous spatio-temporal queries. In this paper, we use shared execution as a mechanism to support scalability in location-aware servers. Our main idea is to maintain a query table that stores information about continuous spatio-temporal queries. Then, answering spatio-temporal queries is abstracted as a spatial join among the moving objects and queries. Three query join policies are proposed aiming to minimize the cost of the join operation under the shared execution paradigm, namely the Clock-triggered Join Policy, the Incremental Join Policy, and the Hot Join Policy. We introduce the concept of a No-Action Region that is used in conjunction with the hot join policy. We propose algorithms that calculate the No-Action region for objects and queries. Experimental performance demonstrates that the No-Action region is more efficient than other approaches when used along with the hot join policy. Experiments also demonstrate that the hot join policy outperforms the clock-triggered join policy and the incremental join policy in terms of both I/O and CPU costs.

Original languageEnglish
Pages (from-to)317-326
Number of pages10
JournalProceedings of the International Conference on Scientific and Statistical Database Management, SSDBM
Volume16
Publication statusPublished - 25 Oct 2004
Externally publishedYes

Fingerprint

Continuous Queries
Query processing
Query Processing
Join
Clocks
Program processors
Query
Scalability
Costs
Servers
Experiments
Moving Objects
Policy
Demonstrate
Table
Server

ASJC Scopus subject areas

  • Software
  • Applied Mathematics

Cite this

Scalable spatio-temporal continuous query processing for location-aware services. / Xiong, Xiaopeng; Mokbel, Mohamed; Aref, Walid G.; Hambrusch, Susanne E.; Prabhakar, Sunil.

In: Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM, Vol. 16, 25.10.2004, p. 317-326.

Research output: Contribution to journalConference article

@article{4e1d2184b70c4389b6c5bd08c589b4e9,
title = "Scalable spatio-temporal continuous query processing for location-aware services",
abstract = "Real-time spatio-temporal query processing needs to effectively handle a large number of moving objects and continuous spatio-temporal queries. In this paper, we use shared execution as a mechanism to support scalability in location-aware servers. Our main idea is to maintain a query table that stores information about continuous spatio-temporal queries. Then, answering spatio-temporal queries is abstracted as a spatial join among the moving objects and queries. Three query join policies are proposed aiming to minimize the cost of the join operation under the shared execution paradigm, namely the Clock-triggered Join Policy, the Incremental Join Policy, and the Hot Join Policy. We introduce the concept of a No-Action Region that is used in conjunction with the hot join policy. We propose algorithms that calculate the No-Action region for objects and queries. Experimental performance demonstrates that the No-Action region is more efficient than other approaches when used along with the hot join policy. Experiments also demonstrate that the hot join policy outperforms the clock-triggered join policy and the incremental join policy in terms of both I/O and CPU costs.",
author = "Xiaopeng Xiong and Mohamed Mokbel and Aref, {Walid G.} and Hambrusch, {Susanne E.} and Sunil Prabhakar",
year = "2004",
month = "10",
day = "25",
language = "English",
volume = "16",
pages = "317--326",
journal = "Scientific and Statistical Database Management - Proceedings of the International Working Conference",
issn = "1099-3371",
publisher = "IEEE Computer Society",

}

TY - JOUR

T1 - Scalable spatio-temporal continuous query processing for location-aware services

AU - Xiong, Xiaopeng

AU - Mokbel, Mohamed

AU - Aref, Walid G.

AU - Hambrusch, Susanne E.

AU - Prabhakar, Sunil

PY - 2004/10/25

Y1 - 2004/10/25

N2 - Real-time spatio-temporal query processing needs to effectively handle a large number of moving objects and continuous spatio-temporal queries. In this paper, we use shared execution as a mechanism to support scalability in location-aware servers. Our main idea is to maintain a query table that stores information about continuous spatio-temporal queries. Then, answering spatio-temporal queries is abstracted as a spatial join among the moving objects and queries. Three query join policies are proposed aiming to minimize the cost of the join operation under the shared execution paradigm, namely the Clock-triggered Join Policy, the Incremental Join Policy, and the Hot Join Policy. We introduce the concept of a No-Action Region that is used in conjunction with the hot join policy. We propose algorithms that calculate the No-Action region for objects and queries. Experimental performance demonstrates that the No-Action region is more efficient than other approaches when used along with the hot join policy. Experiments also demonstrate that the hot join policy outperforms the clock-triggered join policy and the incremental join policy in terms of both I/O and CPU costs.

AB - Real-time spatio-temporal query processing needs to effectively handle a large number of moving objects and continuous spatio-temporal queries. In this paper, we use shared execution as a mechanism to support scalability in location-aware servers. Our main idea is to maintain a query table that stores information about continuous spatio-temporal queries. Then, answering spatio-temporal queries is abstracted as a spatial join among the moving objects and queries. Three query join policies are proposed aiming to minimize the cost of the join operation under the shared execution paradigm, namely the Clock-triggered Join Policy, the Incremental Join Policy, and the Hot Join Policy. We introduce the concept of a No-Action Region that is used in conjunction with the hot join policy. We propose algorithms that calculate the No-Action region for objects and queries. Experimental performance demonstrates that the No-Action region is more efficient than other approaches when used along with the hot join policy. Experiments also demonstrate that the hot join policy outperforms the clock-triggered join policy and the incremental join policy in terms of both I/O and CPU costs.

UR - http://www.scopus.com/inward/record.url?scp=5444220068&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=5444220068&partnerID=8YFLogxK

M3 - Conference article

VL - 16

SP - 317

EP - 326

JO - Scientific and Statistical Database Management - Proceedings of the International Working Conference

JF - Scientific and Statistical Database Management - Proceedings of the International Working Conference

SN - 1099-3371

ER -