| The use of mobile devices has been steadily increasing, for example, smartphones are expected to be used by 69.4% of people worldwide by 2017 [1]. User expectations have also increased as the computational capabilities of mobile devices improve. As a result, software applications need to perform ever more complex and data-intensive tasks to address user expectations. Because of resource limitations in mobile devices (e.g., battery, limited network connectivity) we investigate the cloud computing paradigm as a means of augmenting mobile device capabilities.;In this thesis, we first study the potential reduction in computation time for a mobile device application that offloads part or all of its execution to remote resources, such as a tablet, a laptop, a desktop, or a private/public cloud. Second, we apply the actor model of concurrent computation to reconfigure a distributed application from the mobile device to the cloud. Specifically, we use the SALSA actor programming language, which allows developers to easily create computationally intensive applications that can be broken apart and migrated to various computational resources. Since SALSA programs compile down to Java byte code, we can readily run them in the Android Operating System through an extension to the SALSA language. Lastly, we aim for a separation of concerns by specifying policies that govern when and where to move actors, separately from the functional application code.;Using our Mobile Cloud Computing using Actors (MobileCCA) approach, as applied to a face recognition task, we observed speedups on average of ~5x in the private cloud with respect to doing the computation on the mobile device. Furthermore, we were able to perform the face recognition task on a database of 1000 faces for 400 people, a task beyond the resource capabilities of the mobile device alone. MobileCCA therefore illustrates not only the potential to speedup computations in mobile devices and save battery, but also to enhance the power of mobile applications. |
