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EFFICIENT UPDATES FOR CONTINUOUS QUERIES OVER MOVING
OBJECTS
by
Yu-Ling Hsueh
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful¯llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
August 2009
Copyright 2009 Yu-Ling Hsueh
Object Description
| Title | Efficient updates for continuous queries over moving objects |
| Author | Hsueh, Yuling |
| Author email | yulinghsueh@gmail.com; hsueh@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2009-03-25 |
| Date submitted | 2009 |
| Restricted until | Unrestricted |
| Date published | 2009-08-04 |
| Advisor (committee chair) | Zimmermann, Roger |
| Advisor (committee member) |
Shahabi, Cyrus Kuo, C.C.-Jay |
| Abstract | As a result of recent technological advances, mobile devices with significant computational abilities, gigabytes of storage, and wireless communication capabilities have become widely available. In addition, positioning chips are embedded in more and more of these mobile devices. The combination of Global Positioning System (GPS), 2G, 3G and in the future 4G cellular communication technologies provides a compelling environment to provide mobile users with various location-based services. These services correspond to continuous spatial queries that are posted within an environment of moving objects and produce as their results a time-varying set of objects. In the most ambitious case both queries and data objects are dynamic, making it very challenging to find an effecient query evaluation strategy. Furthermore, monitoring moving objects to maintain the correctness of the query answers often incurs frequent location updates from these moving objects. To address these two challenges we group our work into three main topics, namely (i) efficient location updates, (ii) efficient query result updates, and (iii) query approximation. We now give an overview of each group in turn.; Efficient Location Updates: The significant overhead related to frequent location updates from moving objects often results in poor performance. As the most of the location updates do not affect the query results, the network bandwidth and the battery life of moving objects are wasted. Existing solutions propose lazy updates, but such techniques generally avoid only a small fraction of all unnecessary location updates because of their basic approach (e.g., safe regions, time or distance thresholds). Furthermore, most prior work focuses on a simplified scenario where queries are either static or rarely change their positions. Two novel efficient location update strategies are proposed in this dissertation. The first strategy for a trajectory movement environment is the Adaptive Safe Region (ASR) technique that retrieves an adjustable safe region which is continuously reconciled with the surrounding dynamic queries. The communication overhead is reduced in a highly dynamic environment where both queries and data objects change their positions frequently. In addition, we design a framework that supports multiple query types (e.g., range and c-kNN queries). In this framework, our query re-evaluation algorithms take advantage of ASRs and issue location probes only to the affected data objects, without flooding the system with many unnecessary location update requests.; The second strategy for an arbitrary movement environment is the Partition-based Lazy Update (PLU, for short) algorithm that elevates this idea further by adopting Location Information Tables (LIT) which (a) allow each moving object to estimate possible query movements and issue a location update only when it may affect any query results and (b) enable smart server probing that results in fewer messages. We first define the data structure of a LIT which is essentially packed with a set of surrounding query locations across the terrain and discuss the mobile-side and server-side processes in correspondence to the utilization of LITs. In addition, we further apply three lossless compression methods that condense a LIT to reduce the data stream size.; Efficient Query Result Updates: In the second part of the dissertation, we focus on the problem of maintaining skyline queries efficiently over dynamic objects with d dimensions for totally-ordered and partially-ordered domains. Skyline queries are an important new search capability for multi-dimensional databases. For the totally-ordered domain skyline queries, we propose the ESC algorithm, an Efficient update approach for Skyline Computations, which creates a pre-computed second skyline set that facilitates an efficient and incremental skyline update strategy and results in a quicker response time. With the knowledge of the second skyline set, ESC enables (a) to efficient find the substitute skyline points from the second skyline set only when removing or updating a skyline point (which is called a first skyline point) and (b) to delegate the most time-consuming skyline update computation to another independent procedure, which is executed after the complete updated query result is reported. The basic idea of the traditional branch-and-bound skyline (BBS) algorithm is leveraged for our novel design of a two-threaded approach. The first skyline can be replenished quickly from a small set of second skylines -- hence enabling a fast query response time -- while de-coupling the computationally complex maintenance of the second skyline. Furthermore, we propose the Approximate Exclusive Data Region algorithm (AEDR) to reduce the computational complexity of determining a candidate set for second skyline updates.; For the skyline queries with partially-ordered domains, we introduce a novel approach, termed C-SKY, to reduce the latency by caching query results with their unique user preferences. The results of skyline queries performed on data sets with partially-ordered domains vary depending on users' preference profiles specified for the partially-ordered domains. Existing work has addressed the issue of handling each individual query with some efficiently. However, processing large volumes of such queries for online applications with low response time is still very challenging. Of paramount importance in this case is that cached queries with compatible preference profiles need to be utilized. For this purpose, we introduce a similarity measure that establishes how related a new query is to each of the previously cached queries and profiles. The similarity measure allows the cached entries to be efficiently ordered according to descending values and hence query processing can start with the most promising candidates. If a new query is only partially answerable from the cache, the proposed method pursues a second optimization step. The query processor utilizes the partial result sets and augments them by performing less expensive constraint skyline queries guided by constraint violations between different query preference profiles. Furthermore, to lower the space overhead, we propose a cache management scheme where only the most popular preferences are preserved. Extensive experiments are presented to demonstrate the performance and utility of our novelapproach.; Query Approximation: In existing methods, the cost of retrieving the exact c-kNN data set is expensive, particularly in highly dynamic spatio-temporal applications. The cost includes the location updates of the moving objects when the velocities change over time and the number of continuous kNN queries posed by the moving object to the server. In some applications (e.g., finding my nearest taxies while I am moving), obtaining the perfect result set is not necessary. For such applications, we introduce an AC-kNN technique that approximates the results of the classic c-kNN algorithm, but with efficient updates and while still retaining a competitive accuracy. |
| Keyword | spatio-temporal databases; moving object processing; scalable continuous query processing; spatial data indexing; location-based services |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m2469 |
| Rights | Hsueh, Yuling |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Hsueh-3091 |
| Archival file | uscthesesreloadpub_Volume51/etd-Hsueh-3091.pdf |
Description
| Title | Page 1 |
| Full text | EFFICIENT UPDATES FOR CONTINUOUS QUERIES OVER MOVING OBJECTS by Yu-Ling Hsueh A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful¯llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COMPUTER SCIENCE) August 2009 Copyright 2009 Yu-Ling Hsueh |
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