CMU-CS-13-119
Computer Science Department
School of Computer Science, Carnegie Mellon University



CMU-CS-13-119

Making the Case for Computational Offloading
in Mobile Device Clouds

Afnan Fahim*, Abderrahmen Mtibaa*, Khaled A. Harras*

June 2013

CMU-CS-13-119.pdf

Also appears as Qatar Campus Technical Report
CMU-CS-QTR-120


Keywords: Mobile Cloud Computing, Computational Ooading, Mobile Device Cloud

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.

21 pages


*Carnegie Mellon University, Qatar Campus



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