Smart portable devices form the largest personal computing platform so far in human history, yet the adoption of P2P techniques has been very slow. One reason is the lack of a detailed understanding of the dynamic patterns of network connectivity and battery usage. For example, we know that when a smartphone is on a charger connected to a WiFi network behind a friendly NAT device, it can act as an unrestricted P2P node. However, we do not know how to model these 'good' intervals and so we do not know what P2P applications are possible at all if we restrict participation to only such intervals. This raises a problem similar to modeling churn in classical P2P research. We are not aware of any suitable and available measurement data sets or models. To address this problem, we developed a publicly available smart phone app that provides the user with information about the current network connection such as NAT type, public IP, and so on. The app also collects data about network connectivity and battery status in the background. The app has been downloaded by several hundred users from all over the world. Based on this data we identify and model the sessions during which a phone can participate in a P2P protocol. We also demonstrate through the simulation of gossip protocols that it is feasible to develop smartphone-friendly P2P applications. The raw data is also available for research purposes in an anonymized form upon request.