A Comparative Evaluation of Computation Offloading for Mobile Applications

With the increasing availability of mobile applications, the usage of mobile devices, especially smart phones and tablets, has become popular nowadays. However, mobile devices are limited in battery, memory, storage, and processing capabilities. These constraints prevent mobile devices from widely running all kinds of rich mobile applications. Computation offloading is believed to be a potential solution to the hardware limitations of mobile devices for higher performance and/or energy savings. Computation offloading is often conducted on a remote server, typically in the cloud as reported in the literature. In this paper, we consider that it is not always necessary to offload all computations to a remote cloud server from a mobile device mainly due to the high communication delay that may be generated. Instead, the offloading target can be a nearby PC via a lower communication cost mechanism, such as Bluetooth, depending on the computation demands. We have examined the impact of various factors, such as computation workload, file size, and wireless communication protocols, and have investigated insights on power consumption through offloading to a nearby PC or a remote cloud server. Finally, we develop an adaptive algorithm based on experimental results to automatically select a computation resource which has capacity to execute computationally intensive applications and thus to save energy consumption of mobile devices.