Energy consumption in mobile phones: a measurement study and implications for network applications
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
A first look at traffic on smartphones
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Fine-grained power modeling for smartphones using system call tracing
Proceedings of the sixth conference on Computer systems
Analyzing inter-application communication in Android
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Profiling resource usage for mobile applications: a cross-layer approach
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Android permissions demystified
Proceedings of the 18th ACM conference on Computer and communications security
Proceedings of the 18th ACM conference on Computer and communications security
Identifying diverse usage behaviors of smartphone apps
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Mitigating the true cost of advertisement-supported "free" mobile applications
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Don't kill my ads!: balancing privacy in an ad-supported mobile application market
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Where is the energy spent inside my app?: fine grained energy accounting on smartphones with Eprof
Proceedings of the 7th ACM european conference on Computer Systems
Unsafe exposure analysis of mobile in-app advertisements
Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks
Personal cloudlets for privacy and resource efficiency in mobile in-app advertising
Proceedings of the first international workshop on Mobile cloud computing & networking
The wireless data drain of users, apps, & platforms
ACM SIGMOBILE Mobile Computing and Communications Review
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Proliferation of data-enabled mobile devices has fueled the popularity of smartphone applications (apps) at a rapid pace, and the trend is likely to continue for the foreseeable future. Along with the increase in popularity, the characteristics and concept of paid apps and free apps is also changing. In general, paid smartphone apps generate their revenue simply from the cost of downloading the app. On the other hand, free apps rely on advertisements, and/or virtual currencies, for their revenue generation. There are several variants of these generalized approaches. In this work, we focus on identifying the overhead traffic that is generated by the free apps with respect to the paid apps. The overhead traffic is not associated with the operation of the app itself and thus should not impact the usage experience of the apps. Specifically, we consider advertisements, and the transmission of analytic data, as the main components of overhead traffic. With the gradual disappearance of unlimited data plans, the overhead traffic does not come for free. The goal of this paper is quantify the cost of the overhead traffic of the popular free apps and compare it with the paid apps. We have developed an intricate methodology for identifying and measuring the bandwidth requirements of the overheads associated with the free apps. Through comprehensive measurements, we have shown that in most cases, the paid versions of the apps will indeed be a fraction of the cost to the end users when compared to the actual cost of the free versions.