PRESENTATION BY: SCOTT COREY REPORT BY: A. KHAN, V. SUBBARAJU, A. MISRA, S. SESHAN Mitigating the True Cost of Advertisement- Supported “Free” Mobile Applications

“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