scholarly journals Task Allocation Optimization for Multicore Embedded Systems

2014 ◽  
Author(s):  
Juraj Feljan ◽  
Jan Carlson
Keyword(s):  
Embedded Systems ◽  
Task Allocation

Energy-efficient task allocation techniques for asymmetric multiprocessor embedded systems

2014 ◽  
Vol 13 (2s) ◽  
pp. 1-27 ◽  
Author(s):  
Abdullah Elewi ◽  
Mohamed Shalan ◽  
Medhat Awadalla ◽  
Elsayed M. Saad
Keyword(s):  
Embedded Systems ◽  
Task Allocation ◽  
Energy Efficient ◽  
Multiprocessor Embedded Systems

scholarly journals Energy Efficiency of Task Allocation for Embedded JPEG Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yang-Hsin Fan ◽  
Jan-Ou Wu ◽  
San-Fu Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Embedded Systems ◽  
Embedded System ◽  
Energy Saving ◽  
Task Allocation ◽  
Smart Home ◽  
Consumer Electronics ◽  
Experimental Results ◽  
Software Components

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.

Sign in / Sign up

Export Citation Format

Share Document