title: Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms.
abstract: 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.
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China. wzzhang@hit.edu.cn.
authors.forename: Weizhe
authors.initials: W
authors.lastname: Zhang
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China. encibai@hit.edu.cn.
authors.forename: Enci
authors.initials: E
authors.lastname: Bai
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China. hehui@hit.edu.cn.
authors.forename: Hui
authors.initials: H
authors.lastname: He
authors.affiliation: Department of Computer Science, University of Houston, Houston, TX 77004, USA. cheng@cs.uh.edu.
authors.forename: Albert M K
authors.initials: AM
authors.lastname: Cheng
keywords: energy-aware scheduling; heterogeneous multiprocessor systems; real-time tasks; shuffled frog leaping algorithm