Abstract
This paper discusses the potential benefits of application specific power management through remote task execution. Power management is crucial for mobile devices that have to rely on battery power for extended periods of time. Image processing and understanding is a class of applications that is important in mobile environments. Image processing can be used in autonomous robot navigation, target acquisition/classification, keyboard-less input, and aerial surveillance (Micro Air Vehicles), just to mention a few. Experimental results on an image processing application, namely a human face detection and recognition system, indicate the power savings that can be achieved for this important class of applications. We discuss a compilation strategy that generates two versions of the initial application, one to be executed on the mobile device (client), and the other on a machine connected to the mobile device via a wireless network (server). The client and server codes have to be able to deal with disconnection events. Our proposed compilation strategy uses checkpointing techniques to allow the client to monitor program progress on the server, and to request checkpoint data in order to reduce the performance penalty in case of a possible server and/or network failure. The reported results have been obtained by actual power measurements on three client systems, (1) the StrongARM based low-power SKIFF system developed at Compaq’s Cambridge Research Laboratory, (2) Compaq’s commercially available StrongARM based iPAQ H3600, and (3) a Pentium II based laptop. Initial experiments show that energy consumption can be reduced significantly, in some cases up to one order of magnitude, depending on the selected characteristics of the mobile device, remote host, and wireless network. A prototype implementation of the discussed compilation framework is underway, and preliminary results are reported.