Abstract
Embedded system works everywhere for repeatedly performing a few particular functionalities. Well-known products include consumer electronics, smart home applications, and telematics device, and so forth. Recently, developing methodology of embedded systems is applied to conduct the design of cloud embedded system resulting in the applications of embedded system being more diverse. However, the more energy consumes result from the more embedded system works. This study presents hyperrectangle technology (HT) to embedded system for obtaining energy saving. The HT adopts drift effect to construct embedded systems with more hardware circuits than software components or vice versa. It can fast construct embedded system with a set of hardware circuits and software components. Moreover, it has a great benefit to fast explore energy consumption for various embedded systems. The effects are presented by assessing a JPEG benchmarks. Experimental results demonstrate that the HT, respectively, achieves the energy saving by 29.84%, 2.07%, and 68.80% on average to GA, GHO, and Lin.
Highlights
Smarter, smaller, and portable characteristics make embedded systems to serve diverse functionalities
Based on Task graph (TG), we propose energy-consumed task graph (ETG) as system model of hyperrectangle technology (HT) that adds a factor of energy consumption on TG
Each task is individually implemented as hardware circuit and software component form, which are designed by Verilog programming language and C programming language
Summary
Smaller, and portable characteristics make embedded systems to serve diverse functionalities. The Intel [2] predicts that there will be more than 30 billion devices constantly linked and another 150 billion fitfully connected in the end of this decade It will greatly increase the demand of energy while these devices are served. The software components, such as microcontrollers or programmable digital signal processing (DSPs), provide an environment for various application programs. Each task consumes energy regardless of the forms in either programmable hardware or software components. The dynamic energy consumption is defined while the task is working for providing functionalities. For an embedded system with n tasks, executing one task consumes dynamic energy and the other tasks arise static energy consumption. In consideration of task 2 runs, it consumes dynamic energy consumption, at the same time, task 1, task 3, task 4 till task n occur static energy consumption.
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