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A NSGA-II Algorithm for Task Scheduling in UAV-Enabled MEC System

delete2022-07-01
delete23
PRE
AI
J
Jie Zhu
X
Xuanyu Wang
H
Haiping Huang *
S
Shuang Cheng
吴
吴敏 (Min Wu)
DOI：10.1109/TITS.2021.3120019delete
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Abstract

Abstract

En 中文
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.
Keywords:
UAV
mobile edge-computing system
task scheduling
NSGA-II

Journal

IEEE Transactions on Intelligent Transportation Systems cover
IEEE Transactions on Intelligent Transportation Systems
IF:
8.4
Papers:
9.5K
Citations:
6.3W

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