Heterogeneous Multi-Mobile Computing

Abstract

As smartphones and tablets proliferate, there is a growing demand for multi-mobile computing, the ability to combine multiple mobile systems into more capable ones. We present M2, a system for multi-mobile computing that enables existing unmodified mobile apps to share and combine multiple devices, including cameras, displays, speakers, microphones, sensors, GPS, and input. M2 introduces a new data-centric approach that leverages higher-level device abstractions and hardware acceleration to efficiently share device data, not API calls. To support heterogeneous devices, M2 introduces device transformation, a new technique to mix and match different types of devices. Example transformations include combining multiple displays into a single larger display for better viewing, or substituting accelerometer for touchscreen input to provide a Nintendo Wii-like experience with existing mobile gaming apps. We have implemented M2 and show that it (1) operates across heterogeneous systems, including multiple versions of Android and iOS, (2) can enable unmodified Android apps to use multiple mobile devices in new and powerful ways, including supporting users with disabilities and better audio conferencing, and (3) can run apps across mobile systems with modest overhead and qualitative performance indistinguishable from using local device hardware.