SPADE: scheduler for parallel and distributed execution from mobile devices

Abstract

Mobile computing devices, such as mobile phones or even ultra-mobile PC's, are becoming more and more powerful. Because of this fact, users are starting to use these devices to execute tasks that until a few years ago would only be executed on a desktop PC, e.g. picture manipulation, or text editing. Furthermore, these devices, are by now almost continuously connected, either by Wi-Fi or 3G UMTS links. Nevertheless power consumption is still a major factor on these mobile devices usage, restricting autonomy. While users should be able to employ mobile computing devices to perform these tasks with convenience, it would improve performance and reduce battery drain if the bulk processing of such tasks could be offloaded to remote hosts accessible by the same user. To accomplish this, we present SPADE, a middleware to deploy remote and parallel execution of some commodity applications to solve complex problems, from mobile devices, without any special programming effort, and by simply defining several data input sets. In SPADE, jobs are composed of simpler tasks that will be executed on remote computers. The user states what files should be processed by each task, what application will be launched and defines the application arguments. By using SPADE any user can, for instance, accelerate a batch image manipulation by using otherwise idle remote computers, while releasing the mobile device for other tasks. In order to make SPADE usable by a wide set of computer users we implemented two ideas: i) the execution code is a commodity piece of software already installed on the remote computers (e.g. image processing applications), and ii) the definition of the data sets to be remotely processed is done in a simple and intuitive way. The results are promising as the speedups accomplished are near optimal, while reducing power consumption, and SPADE allows the easy and efficient deployment of jobs on remote hosts.