Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

Sensors

Weizhe Zhang²  Enci Bai²  Hui He²  Albert M.K. Cheng¹ 

[1] Department of Computer Science, University of Houston, Houston, TX 77004, USA; E-Mail:;School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China; E-Mails:

关键词: energy-aware scheduling;    real-time tasks;    heterogeneous multiprocessor systems;    shuffled frog leaping algorithm;   

DOI  :  10.3390/s150613778

来源: mdpi

【 摘 要 】

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.