Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
2-2012
Abstract
The dominant, "ad-supported free application" model for consumer-oriented mobile computing is seemingly imperiled by the growing global adoption of metered data pricing plans by mobile operators. In this paper, we explore the opportunities for addressing this emerging conflict by enabling more intelligent ad delivery to such mobile devices. One especially promising path is leveraging the increasing availability of heterogeneous wireless access technologies (e.g., WiFi, femtocells) that offer less restrictive and more energy-efficient transport substrates for such data traffic. To understand the possibilities that exist, we first profile the advertisement traffic characteristics for some of the most popular advertisement-supported consumer applications, and then analyze the key features of mobile advertisement delivery. We then outline the principles of CAMEO, a middleware that uses predictive profiling of a user's {device, network and usage} context to anticipate the advertisements that need to be served, and then modulates their delivery mechanism to enable effective mobile advertising, but at considerably lower costs. © 2012 ACM.
Discipline
Computer Sciences | Databases and Information Systems | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
HotMobile '12: Proceedings of the 12th Workshop on Mobile Computing Systems & Applications, San Diego, February 28-29
First Page
1
Last Page
6
ISBN
9781450300056
Identifier
10.1145/2162081.2162083
Publisher
ACM
City or Country
New York
Citation
KHAN, Azeem J.; SUBBARAJU, Vigneshwaran; MISRA, Archan; and SESHAN, Srinivasan.
Mitigating the true cost of advertisement-supported "free" mobile applications. (2012). HotMobile '12: Proceedings of the 12th Workshop on Mobile Computing Systems & Applications, San Diego, February 28-29. 1-6.
Available at: https://ink.library.smu.edu.sg/sis_research/3507
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/2162081.2162083