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

• 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

Wired InternetBS

BS

Mobile node

Base station

Wireless domain

Fixed node

Architecture of Mobile Database Systems

Database

Internet

server

server

client

client

BS

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

• 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

• 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)

http://mobile.google.com/

(XHTML)

(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,” Wiley-

Interscience, 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.