MARC 主機 00000nam 2200337 4500
001 AAI3425066
005 20120910130320.5
008 120910s2010 ||||||||||||||||| ||eng d
020 9781124255668
035 (UMI)AAI3425066
040 UMI|cUMI
100 1 Bamba, Bhuvan
245 10 Scaling location-based services with location privacy
constraints: Architecture and algorithms
300 241 p
500 Source: Dissertation Abstracts International, Volume: 71-
10, Section: B, page: 6217
500 Adviser: Ling Liu
502 Thesis (Ph.D.)--Georgia Institute of Technology, 2010
520 Advances in sensing and positioning technology, fueled by
wide deployment of wireless networks, have made many
devices location-aware. These emerging technologies have
enabled a new class of applications, known as Location-
Based Services (LBS), offering both new business
opportunities and a wide array of new quality of life
enhancing services. There are two important challenges for
location-based service provisioning. How do we scale LBSs
in the presence of client mobility and location dependent
constraints for the multitude of new, upcoming location-
based applications under a common framework? How do we
provide anonymous location-based services with acceptable
performance and quantifiable privacy protection in the
next generation of mobile networks, systems and
applications?
520 First, we introduce spatial alarms as the basic primitive
to represent a class of location-based services that
require location-based trigger capability. We develop a
generalized framework and a suite of optimization
techniques for server-centric scalable processing of
spatial alarms. Our architecture and algorithm development
provide significant performance enhancement in terms of
system scalability compared to naive spatial alarm
processing techniques, while maintaining high accuracy for
spatial alarm processing on the server side and reduced
communication costs and energy consumption on the client
side. Concretely, we develop safe period optimizations for
alarm processing and introduce spatial alarm grouping
techniques to further reduce the unnecessary safe period
computation costs. In addition, we introduce a distributed
alarm processing architecture that advocates the
partitioning of the alarm processing load among the server
and the relevant mobile clients to reduce the server load
and minimize the client-to-server communication cost
through intelligent distribution and parallelization. We
also explore a variety of optimization opportunities such
as incorporating non-spatial constraints into the location
-based information monitoring problem and utilizing
efficient indexing methods such as bitmap indexing to
further enhance the performance and scalability of spatial
alarm processing in the presence of mobility hotspots and
skewed spatial alarm distributions
520 Second, we develop the PrivacyGrid framework for privacy-
enhanced location service provisioning, focusing on
providing customizable and personalized location privacy
solutions while scaling the mobile systems and services to
a large number of mobile users and a large number of
service requests. The PrivacyGrid approach has three
unique characteristics. First, we develop a three-tier
architecture for scaling anonymous information delivery in
a mobile environment while preserving customizable
location privacy. Second, we develop a suite of fast,
dynamic location cloaking algorithms. It is known that
incorporation of privacy protection measures may lead to
an inherent conflict between the level of privacy and the
quality of services (QoS) provided by the location-based
services. Our location cloaking algorithms can scale to
higher levels of location anonymity while achieving a good
balance between location privacy and QoS. Last but not the
least; we develop two types of location anonymization
models under the PrivacyGrid architecture, one provides
the random way point mobility model based location
cloaking solution, and the other provides a road network-
based location privacy model powered by both location k-
anonymity and segment s-anonymity. A set of graph-based
location cloaking algorithms are developed, under the
MobiCloak approach, to provide desired levels of privacy
protection for users traveling on a road network through
scalable processing of anonymous location services
520 This dissertation, to the best of our knowledge, is the
first one that presents a systematic approach to the
design and development of the spatial alarm processing
framework and various optimization techniques. The concept
of spatial alarms and the scaling techniques developed in
this dissertation can serve as building blocks for many
existing and emerging location-based and presence based
information and computing services and applications. The
second unique contribution made in this dissertation is
its development of the PrivacyGrid architecture for
scaling anonymous location based services under the random
waypoint mobility model and its extension of the
PrivacyGrid architecture through introducing the MobiCloak
road-network based location cloaking algorithms with
reciprocity support for spatially constrained network
mobility model. Another unique feature of the PrivacyGrid
and MobiCloak development is its ability to protect
location privacy of mobile users while maintaining the end
-to-end QoS for location-based service provisioning in the
presence of dynamic and personalized privacy constraints.
(Abstract shortened by UMI.)
590 School code: 0078
650 4 Computer Science
690 0984
710 2 Georgia Institute of Technology
773 0 |tDissertation Abstracts International|g71-10B
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