However, the length of time a cell phone waits before sleeping is partly set by cell phone networks that have other concerns than a user’s battery life, Venkataramani adds. For example, tail times are sometimes made long to reduce the work of cell towers, which must exchange control messages with devices whenever they wake or sleep. Gathering more data on user behavior may help raise the profile of the battery-life problems, says Venkataramani, but carriers are still likely to want to put their networks first.
Falaki says devices, apps, and wireless networks should be designed with more regard to how people actually use their devices, but that because smartphones are still relatively new, little is known about that. Previous studies have used data about wireless networks as a whole instead of individual user behavior, or lab-based experiments where phones transfer test data and patterns of everyday use are not encountered, he says. “In contrast, we capture real usage patterns as people used their devices normally.”
Lin Zhong, who leads the Efficient Computing Group at Rice University, points out that very little is really known about how people use smart phones. “The UCLA-Microsoft data set is small, but they have already highlighted some interesting results,” he says.
Zhong and his Rice colleagues developed tracking software that runs on hacked, or jailbroken, iPhones and can capture network data, battery information, and the times when people use specific applications or features. His research group is in the final four months of a yearlong trial using the software to capture every aspect of the way 35 people use their iPhone 3GS devices.
“It sounds like a virus in the device, but we do it in a way that preserves privacy and does not interfere with the person when they are using their phone,” says Zhong. For example, although records are logged of all phone calls, the numbers called are obfuscated.
The Rice group is using its data to create a new kind of cell-phone coverage map: one created by collecting the actual experiences of real users. “If you look at the coverage map for, say, AT&T, it will tell you there is full 3G coverage in Houston, but we know that’s not what you experience,” says Zhong. “We can collect a very fine-grained network map.”
This is an example of how cell-phone-logging apps can be of use to more than just researchers, he points out. Future phone users could benefit from an app that logs and shares the network strength experienced by their phone to build a dynamic map of cellular network coverage and Wi-Fi hot spots, he says.