The case for cloud-enabled mobile sensing services

Abstract

We make the case for cloud-enabled mobile sensing services that support an emerging application class, one which infers near-real time collective context using sensor data obtained continuously from a large set of consumer mobile devices. We present the high-level architecture and functional requirements for such a mobile sensing service, and argue that such a service can significantly improve the scalability and energy-efficiency of large-scale mobile sensing by coordinating the sensing & processing tasks across multiple devices. We then focus specifically on the problem of energy-efficiency and provide early exemplars of how optimizing query execution jointly over multiple phones can lead to substantial energy savings.