Using Simulation to Improve Workflow Scheduling in Heterogeneous Computing Systems

2017 ◽  
pp. 407-417 ◽  
Author(s):  
Alexey Nazarenko ◽  
Oleg Sukhoroslov
Keyword(s):  
Heterogeneous Computing ◽  
Workflow Scheduling ◽  
Computing Systems ◽  
Heterogeneous Computing Systems

scholarly journals Bi-Objective Workflow Scheduling on Heterogeneous Computing Systems Using a Memetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 209
Author(s):  
Yujian Zhang ◽  
Fei Tong ◽  
Chuanyou Li ◽  
Yuwei Xu
Keyword(s):  
Local Search ◽  
Heterogeneous Computing ◽  
Memetic Algorithm ◽  
Population Based ◽  
Feasible Region ◽  
Workflow Scheduling ◽  
Nsga Ii ◽  
Computing Systems ◽  
Similar Work ◽  
Heterogeneous Computing Systems

Due to the high power bills and the negative environmental impacts, workflow scheduling with energy consciousness has been an emerging need for modern heterogeneous computing systems. A number of approaches have been developed to find suboptimal schedules through heuristics by means of slack reclamation or trade-off functions. In this article, a memetic algorithm for energy-efficient workflow scheduling is proposed for a quality-guaranteed solution with high runtime efficiency. The basic idea is to retain the advantages of population-based, heuristic-based, and local search methods while avoiding their drawbacks. Specifically, the proposed algorithm incorporates an improved non-dominated sorting genetic algorithm (NSGA-II) to explore potential task priorities and allocates tasks to processors by an earliest finish time (EFT)-based heuristic to provide a time-efficient candidate. Then, a local search method integrated with a pruning technique is launched with a low possibility, to exploit the feasible region indicated by the candidate schedule. Experimental results on workflows from both randomly-generated and real-world applications suggest that the proposed algorithm achieves bi-objective optimization, improving makespan, and energy saving by 4.9% and 24.3%, respectively. Meanwhile, it has a low time complexity compared to the similar work HECS.

Ant colony based constrained workflow scheduling for heterogeneous computing systems

2016 ◽  
Vol 19 (3) ◽  
pp. 1053-1070 ◽  
Author(s):  
Somayeh Kianpisheh ◽  
Nasrolah Moghadam Charkari ◽  
Mehdi Kargahi
Keyword(s):  
Heterogeneous Computing ◽  
Ant Colony ◽  
Workflow Scheduling ◽  
Computing Systems ◽  
Heterogeneous Computing Systems
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