Android Based Energy Aware Framework for Porting Legacy Applications

Abstract

Trend is growing towards using complex multimedia functions on smaller devices. In this study, we explore the effect of migrating legacy signal processing software applications algorithms from large form factor devices to the smaller one such as handheld mobile devices known as Energy Conscious Mobile Computing Systems (EConMCS). We concentrate on Source Code Volatility (SCV), including inherent algorithm complexity and the developer implementation. We identify code Transformation Steering Factors (TSF), such as loop unrolling factor, decision tree grafting factor and their relation to SCV. The impact of TSF is discussed for different multimedia applications in native Digital Signal Processor (DSP) compiler optimization while switching between different transformation schemes. Our results show that SCV can be minimized by using an architecture-centric algorithm that both enables the effective use of underlying hardware architectures and the memory access required to optimize energy consumption. The coded spatial access is implicitly dependent on layout, content and location of options and legibility that relates to a developer's implementation of loops, code blocks and decision trees. The compiler-centric transformation model minimizes the effect of legacy code migration for multimedia applications. Results are exposed for the transformation of typical DSP applications and a video transcodec MPEG-4.