TY - GEN
T1 - CAMEO
T2 - 11th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2013
AU - Khan, Azeem J.
AU - Jayarajah, Kasthuri
AU - Han, Dongsu
AU - Misra, Archan
AU - Balan, Rajesh
AU - Seshan, Srinivasan
PY - 2013
Y1 - 2013
N2 - Advertisements are the de-facto currency of the Internet with many popular applications (e.g. Angry Birds) and online services (e.g., YouTube) relying on advertisement generated revenue. However, the current economic models and mechanisms for mobile advertising are fundamentally not sustainable and far from ideal. In particular, as we show, applications which use mobile advertising are capable of using significant amounts of a mobile users' critical resources without being controlled or held accountable. This paper seeks to redress this situation by enabling advertisement supported applications to become significantly more "user-friendly". To this end, we present the design and implementation of CAMEO, a new framework for mobile advertising that 1) employs intelligent and proactive retrieval of advertisements, using context prediction, to significantly reduce the bandwidth and energy overheads of advertising, and 2) provides a negotiation protocol and framework that empowers applications to subsidize their data traffic costs by "bar-tering" their advertisement rights for access bandwidth from mobile ISPs. Our evaluation, that uses real mobile advertising data collected from around the globe, demonstrates that CAMEO effectively reduces the resource consumption caused by mobile advertising.
AB - Advertisements are the de-facto currency of the Internet with many popular applications (e.g. Angry Birds) and online services (e.g., YouTube) relying on advertisement generated revenue. However, the current economic models and mechanisms for mobile advertising are fundamentally not sustainable and far from ideal. In particular, as we show, applications which use mobile advertising are capable of using significant amounts of a mobile users' critical resources without being controlled or held accountable. This paper seeks to redress this situation by enabling advertisement supported applications to become significantly more "user-friendly". To this end, we present the design and implementation of CAMEO, a new framework for mobile advertising that 1) employs intelligent and proactive retrieval of advertisements, using context prediction, to significantly reduce the bandwidth and energy overheads of advertising, and 2) provides a negotiation protocol and framework that empowers applications to subsidize their data traffic costs by "bar-tering" their advertisement rights for access bandwidth from mobile ISPs. Our evaluation, that uses real mobile advertising data collected from around the globe, demonstrates that CAMEO effectively reduces the resource consumption caused by mobile advertising.
KW - Advertising
KW - Mobile
KW - Wireless
UR - http://www.scopus.com/inward/record.url?scp=84881154589&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881154589&partnerID=8YFLogxK
U2 - 10.1145/2462456.2464436
DO - 10.1145/2462456.2464436
M3 - Conference contribution
AN - SCOPUS:84881154589
SN - 9781450316729
T3 - MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services
SP - 125
EP - 137
BT - MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services
Y2 - 25 June 2013 through 28 June 2013
ER -