Mitigating the True Cost of
Advertisement- Supported
“Free” Mobile Applications
PRESENTATION BY: SCOTT COREY
REPORT BY: A. KHAN, V. SUBBARAJU, A.
MISRA, S. SESHAN
“Free” Applications
 Consumers have grown accustomed to “free”
applications supported by advertisements
 Free versions of Angry Birds earns $1 million+ a
month in advertisements
Total free apps downloaded 81%
Free apps in top grossing list 51%
Free apps in iTunes Store 63%
Free apps in Android Market 37%
Free apps in Blackberry World 82%
Data Traffic
 Consumers data usage is growing exponentially
 Many major providers now have metered data plans
 Most devices have alternative connections that are
free


Wi-Fi
Femtocell
CAMEO
 Context-Driven Advertisement Modulator and




Optimizer
The current “free” application model is
unsustainable
Inexpensive and unmetered bandwidth is readily
available
Advertisements can be prefetched during these
opportune times
The advertisement served is context-dependent
Characterization of Mobile Advertising Traffic
 Began with experiment using “free” apps on a Nexus
One
 Applications were tested with 15 minutes of runtime
(30 minutes for “Friends” games)
 Network traffic was recorded to identify and
compare usage from advertisements or the
application itself
Results
 Non-negligible amount of traffic from each
application
 Usage varied based on quantity of advertisements
Math
 Fruit Ninja – 5.61 Kbps on average
 Played for 30 minutes per day
 On Verizon Wireless
 Current data plan: $30 for 2GB per month
 The advertisements alone generate ~40MB of traffic,
roughly 56 cents of data
 Paid version is 99 cents
Trending Upwards
 Advertisements are getting larger, more interactive
 HTML5 based ads are typically 5-20 times larger
 Multiple applications can be running at one time
 “Free” applications are not free!
Key Characteristics of Mobile Advertising
 Combination of users profile and recent
environmental context
Context
 Network phone is connected to
 Ads for other carriers
 Location
 Ads for city events
 Applications used
 Ads for similar applications and same developers
 Model of the phone
 Ads for newer phones
Mechanics of Advertisement Delivery
 Advertisements were overlaid overtop applications
 Most applications used multiple advertisement
networks
 Multiple connections were necessary



Contact network
Get XHTML or Javascript code
Fetch actual advertisement
Back to CAMEO
 Must predict likely future context of the user/device
 Intelligently utilizing available alternative networks
 Serving advertisements from a local cache
Compatible with existing deployments
 Must reduce cost of current advertising methods
 Interception
 Switch to CAMEO from connecting to outside networks
 Advertisement Generation
 Must have cached appropriate advertisements in advance
 Combination of cache manager, ad-prefetcher, and context
predictor
 Cannot distinguish advertising traffic
 Cannot verify if correct advertisements were
provided
Clean-Slate Design
 Application Modifications
 Can query CAMEO components directly
 Applications verify advertisements are received and
appropriate
 Infrastructure Modifications
 Data prefetching can be done in a network-friendly fashon
 Networks can provide additional information to enhance
context
 Opens up advanced possibilities of advertising