Estimador e caracterizador de consumo de energia para software embarcado

Abstract

The energy consumption in the past years became a very important issue in embedded system projects. The high production and wide application of mobile devices have forced the emergence of various restrictions to this system, such as: weight, size and lifetime of batteries and multiple functionalities. Mobile devices works under limited power source that autonomy and lifetime are directly related to energy consumption of the running applications. These concerns have contributed significantly to include the energy consumption as metric for project quality in embedded systems. The main goal of this work is to propose metrics, estimative and compare the energy consumption of programs code written in ANSI-C language, based on execution time of embedded systems. In order to support the approach it was improved a tool in algorithm level known as PESTI in multiple scenarios. It was written a program in ANSI-C language and loaded in processor of the ARM 7 family s. Then, it was added into this program flags to signalize start and stop in order to measure execution time of each track in analysis. The estimative tool already modified to attribute multiple scenarios, for a program written in ANSI-C and translated into an annotated control flow graph, with tracks assignments of probabilities. This model is probabilistically simulated by using Monte Carlo methodology. The proposed approach was validate carrying out a series of experimental in order to show the viability of the improved tool of estimation and characterization, which together will make the estimates of energy consumption somewhat more feasible.  Validate the proposed approach added;  Compare the results between simulation time and the tool for characterization PESTI with the same hardware platform embedded (ARM7). The experimental were divided in three steps:  Simulation of the code in the tool PESTI in multiple scenarios;  Characterization of the query code;  Comparison of the characterization tool and PESTI. The experiments were conducted on:  AMD Turion (tm) II Dual Core Mobile Processor M500, 2.20GHz, 4Gb of RAM;  OS Linux Mint Distribution kernel 2.6.22 32-bit; 11  OS Windows 7 32-bit.