Mobile Advertising in Capacitated Wireless Networks

The growing number of mobile subscribers has attracted firms to invent newer strategies to reach prospective customers in innovative but nonintrusive ways. While customer mobility creates an opportunity to reach them at desired times and locations, in practice, real-time ad deliveries are difficult...

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Bibliographic Details
Published in:IEEE transactions on knowledge and data engineering 2006-09, Vol.18 (9), p.1284-1296
Main Authors: Tripathi, A.K., Nair, S.K.
Format: Article
Language:English
Subjects:
Ad targeting
Advertising
Applied sciences
Cellular phones
Computer science
control theory
systems
Customers
Europe
Exact sciences and technology
Heuristic
Information systems. Data bases
Intelligent networks
Markov decision process
Memory organisation. Data processing
Message service
Mobile advertising
Mobile communication systems
Networks
Performance analysis
Policies
Real time
Software
Strategy
Studies
Telecommunications
Telecommunications and information theory
Teleprocessing networks. Isdn
Testing
Upper bound
wireless advertising
Wireless networks
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Summary:The growing number of mobile subscribers has attracted firms to invent newer strategies to reach prospective customers in innovative but nonintrusive ways. While customer mobility creates an opportunity to reach them at desired times and locations, in practice, real-time ad deliveries are difficult due to the size of the ad-delivery decision problem. This research aims at analyzing and developing a decision policy for delivering ads on mobile devices such as cell phones. We look at the ad delivery problem from the perspective of an advertising firm, which delivers ads on behalf of its clients (merchants) to mobile customer using a wireless carrier's infrastructure. We formulate the mobile ad delivery problem as a Markov decision process (MDP) model. The ad delivery policy depends on the customer's desire and willingness to receive ads, their real-time locations, historical mobility patterns, available network capacity, and fee structure agreed upon for ad deliveries. We also develop a fast heuristic to solve larger size problems. We test our heuristic against an upper bound we developed and analyze performance using simulation
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2006.144