Computer Science Qatar
School of Computer Science, Carnegie Mellon University
Making the Case for Computational Offloading
Afnan Fahim, Abderrahmen Mtibaa, Khaled A. Harras
Also appears as Computer Science Department
It is common practice for mobile devices to offload computationally heavy tasks off to a cloud, which has greater computational resources. We consider an environment in which computational offloading is made among mobile devices. We call such an environment a mobile device cloud (MDC). In this work, we first highlight the gain in computation time and energy consumption that can be achieved by offloading tasks to nearby devices inside a mobile device cloud. We do this by emulating network conditions that exist for different communication technologies provided by modern mobile devices. We then present a platform that allows creation and offloading of tasks by a mobile devices to nearby devices. Such a platform consists of an API, an accompanying Android application deployable across MDC devices, and a test bed to measure power being consumed by a mobile device. Finally, we create and utilize a testbed, which consists of four Android devices and energy measurement equipment, in order to validate our intuitions and qualify the gain in time and energy which we deduced from the emulation experiments. Using this test bed we show up to 50% gain in time and 26% gain in energy by employing task offload in MDC's versus executing tasks locally.