Mobile Databases
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Transcript Mobile Databases
Mobile Databases
J. H. Wang
May 2011
Outline
• Overview
• Issues in Mobile Databases
– Data management
– Transaction management
• Mobile Databases and Information
Retrieval
• Future Challenges and Issues
Mobile Database Systems
• Distributed system with mobile
connectivity
• Full database system capability
• Complete spatial mobility
• Wired and wireless communication
capability
Possible Applications
•
•
•
•
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Traffic control
Taxi dispatch
Emergencies services: police, medical, fire, …
Car navigation
Location-aware search and recommendation
Social applications: information / opinion sharing
and search among community
• …
An Example Application:
Taxi Dispatch
[Source: Alibaba.com]
Possible Limitations
• Limited wireless bandwidth and
communication speed
• Limited power (battery life)
• Limited screen size for output
• Limited query capability for input
• Limited computing & storage capacity
• Less secure
Capabilities
• Anywhere: can physically move around
without affecting data availability
• Anytime: can store and retrieve any data
whenever mobile connection is available
• Efficiency: can process mobile data
efficiently
• Effectiveness: can give users what they
really want (, and skip the less relevant…)
Goal
• To build a ubiquitous information
processing system given the inherent
limitations of mobile devices and wireless
communications
Architecture of a Typical Mobile
Platform
Base station
Fixed node
Wired Internet
BS
Mobile node
BS
Wireless domain
Architecture of Mobile Database
Systems
client
server
client
Internet
BS
server
Database
Issues in Mobile Databases
• Data management
– Data caching
– Representation and storage of mobile data
– Data classification
• Transaction management
– Mobile query processing
– Mobile concurrency control
– Transaction and error recovery
Data Management Issues
• How to improve data availability to user queries
in mobile database systems?
– Data caching
• Results of previous queries are cached on mobile clients
• Query log can be further used in personalization and
recommendation
– Representation and storage of mobile data
• Spatial data management
• Indexing and retrieval schemes
– Data classification
• Location-dependent
• Location-independent
Data Caching
• Results of previous queries are cached on
mobile clients
– Cache size
– Cache freshness/update frequency
– Cache consistency
• Query log can be further used in
personalization and recommendation
– User preference learning
• keywords, categories, location
– Collaborative filtering for content
recommendation
Representation and storage of
mobile data
• Spatial data management
– Location information
– Data volume, update frequency, persistency
• Indexing and retrieval schemes
– High-dimensional feature space
– Structure for improving retrieval efficiency
Data classification
• Location-dependent
– Location-based services
• E.g. nearby gas stations or restaurants within 1km,
available paths to the park, …
– Database distribution or replication must take
location into consideration
• Distributed vs. centralized
• Location-independent
– Personal name, account information, plate
number, …
An Example Location-based
Service
[Source: Google Maps Realtime Traffic]
Transaction Management Issues
• Mobile query processing
• Concurrency control
• Transaction and error recovery
Mobile Query Processing
• Query types
– Location dependent query
– Location aware query
– Location independent query
• Query constraints
– Query response time
– Search-result accuracy
– Throughput: number of queries per time unit
Location dependent query
• A query whose result depends on the
geographical location of the query origin
– E.g.
• What are the 3 nearest gas stations or restaurants?
• What is the shortest path to the park?
– GPS can facilitate this
• Outdoor only
• WLAN could cover most of the indoor locality
Example
• Find the nearest gas stations
– [Source: Google Image Search]
Location aware query
• A query whose context might be related to
locations
– E.g.
• Find out all the car plates passing through the
traffic light between 7:00-8:00pm
• Find out the current location of the bus on route
#212
• Find out the top 5 road segments that have the
most traffic in Taipei (the slowest car speed)
An Example
• Red light cameras
– [Source: St. Petersburg Times]
Query constraints
• Query response time
– Realtime query
• Search-result accuracy
– Distance, time, path, traffic flow, …
• Throughput: number of queries per time
unit
– Scalability: large number of simultaneous
queries
Mobile concurrency control
• Similar to the issues of concurrency
control in distributed systems
– Time synchronization
• Timestamps, clocks
– Latency in mobile queries
– Similar issues to cache consistency
• Size of query results
Transaction and error recovery
• Conventional transaction properties
– Atomicity
– Consistency
– Isolation
– Durability
• Too rigid for mobile database
– Flexibility can be introduced
Possible issues in mobile
transactions
• Transactions
– Wireless communication availability and
overhead
– Hard to manage locking and unlocking
operations
– Limited power
• Recovery
– Efficient logging and checkpointing
– Log duplication
Other Concerns
• In mobile e-commerce, security in mobile
data and transactions are critical
– Less support in wireless security
• WEP, IEEE 802.11i
– Identity authentication
– Privacy issues of user location
Mobile Databases and Information
Retrieval
• Mobile information retrieval
– Context awareness
– Content adaptation
• Existing mobile search services
– Mobile Web browsing
– Text messaging (SMS)
Context Awareness
• Location information
• Built-in camera
• Social networks
Possible research topics related to
context awareness
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Location-based search
Spatial data mining
Query log mining
User profiling and recommendation
Knowledge sharing
Content Adaptation
• Small screens
• Less processing power
• Less memory and storage
Possible research topics related to
content adaptation
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Automatic summarization
Information filtering
User personalization
Efficient indexing and retrieval of mobile
media
• Effective structure for mobile data storage
• Scalable algorithms
Common Types of Mobile Web
Services
• Mobile Web browsing
– Search: Web pages, images, products, local,
movies, …
• Text messaging
– SMS
• Others
– Maps
– GPS
Existing Mobile Search Services
• Google
– Google Mobile
– Google SMS
– Google Maps for Mobile
• Yahoo
– Yahoo! Mobile
– Yahoo! Go
• Others
– AOL, MSN, 4INFO, …
Google Mobile (1/2)
(XHTML)
http://mobile.google.com/
(WML)
Google Mobile (2/2)
(Images)
(Mobile Web)
Google SMS
http://www.google.com/sms/
Google Maps for Mobile
http://www.google.com/gmm/
Future Challenges and Issues
• Indexing and storage of mobile data
• Efficient query processing and retrieval of mobile
data
• Content adaptation and information presentation
for small display
• User interface design for mobile search
• Automatic summarization and personalization of
mobile data
• Scalable algorithms for large mobile databases
• Knowledge sharing among mobile peers
• Security and trusted retrieval of mobile data
• Location-based search for mobile devices
Other Resources
• Recent academic events
– Workshop on mobile information retrieval (MobIR
2008), in conjunction with SIGIR 2008
– International workshop on mobile information
retrieval for future (MIRF 2010)
– International workshop on mobile and ubiquitous
information access (MUIA 2009), in conjunction
with ECIR 2009
– International workshop on mobile multimedia
information retrieval (MoMIR 2009), in
conjunction with MoMM 2009
Other Related Fields
• Mobile Ad Hoc Network (MANET)
• Mobile Peer-to-Peer Network (P2P)
• Ubiquitous Computing or Pervasive
Computing
Thanks for Your Attention!
• Further reading:
– Vijay Kumar, “Mobile Database Systems,” WileyInterscience, 2006.
– F.S.Tsai, M. Etoh, X. Xie, W.C.Lee, and Q. Yang,
“Introduction to Mobile Information Retrieval,”
IEEE Intelligent Systems, Vol. 25, No.1, pp.11-15.
– Communications of the ACM, Vol.48, No.3, The
Disappearing Computer, Mar. 2005.
– Communications of the ACM, Vol.45, No.12,
Issues and Challenges in Ubiquitous Computing,
Dec. 2002.