A Hybrid Energy-Aware Scheduling for Real-Time Task Synchronization

Author(s):  
Da-Ren Chen
2016 ◽  
Vol 15 (1) ◽  
pp. 1-34 ◽  
Author(s):  
Mario Bambagini ◽  
Mauro Marinoni ◽  
Hakan Aydin ◽  
Giorgio Buttazzo

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 75110-75123 ◽  
Author(s):  
Haider Ali ◽  
Umair Ullah Tariq ◽  
Yongjun Zheng ◽  
Xiaojun Zhai ◽  
Lu Liu

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Weizhe Zhang ◽  
Hucheng Xie ◽  
Boran Cao ◽  
Albert M. K. Cheng

Energy consumption in computer systems has become a more and more important issue. High energy consumption has already damaged the environment to some extent, especially in heterogeneous multiprocessors. In this paper, we first formulate and describe the energy-aware real-time task scheduling problem in heterogeneous multiprocessors. Then we propose a particle swarm optimization (PSO) based algorithm, which can successfully reduce the energy cost and the time for searching feasible solutions. Experimental results show that the PSO-based energy-aware metaheuristic uses 40%–50% less energy than the GA-based and SFLA-based algorithms and spends 10% less time than the SFLA-based algorithm in finding the solutions. Besides, it can also find 19% more feasible solutions than the SFLA-based algorithm.


2016 ◽  
Vol 65 (4) ◽  
pp. 1297-1309 ◽  
Author(s):  
Ting-Hao Tsai ◽  
Lin-Fong Fan ◽  
Ya-Shu Chen ◽  
Tien-Shun Yao
Keyword(s):  

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