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A NSGA-II Algorithm for Task Scheduling in UAV-Enabled MEC System
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DOI：10.1109/TITS.2021.3120019.png)
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摘要
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In this paper, we investigate the task scheduling problem in the UAV-enable Mobile Edge-Computing (MEC) system with the objectives of minimizing the cost and the completion time. A NSGA-H algorithm is proposed for the problem under study. The solution is represented as a two-dimension location sequence. Major components of NSGA-II are delicately designed including the feasible solution generation method (FSGM) and genetic operations of crossover, mutation and selection. Three strategies are introduced in FSGM. A simulated annealing local search is integrated into the crossover operation, and meanwhile two novel mutation methods are proposed. The Pareto-based metrics are introduced to evaluate the performance of the compared algorithms. Experimental results show that the proposal is more effective and robust than the three existing algorithms.
Keyword:
UAV
mobile edge-computing system
task scheduling
NSGA-II
期刊
IF:
8.4
论文数:
9.7K
被引数:
6.3W
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