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Multi-task offloading scheme for UAV-enabled fog computing networks

机译:支持无人机的雾计算网络的多任务卸载方案

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In unmanned aerial vehicle (UAV)-enabled fog computing networks, how to efficiently offload multiple tasks to the computing nodes is a challenging combinatorial optimization problem. In this paper, in order to optimize the total delay for the UAV-enabled fog computing networks, a simple scheduling algorithm and a multi-task offloading scheme based on fireworks algorithm (FWA) are proposed. First, the system model of multiple tasks offloading in UAV-enabled fog computing networks is described in detail. Then, a simple scheduling algorithm is proposed to optimize the delay of the tasks allocated to a single node. Based on the scheduling algorithm, a multi-task offloading scheme for all tasks and all computing nodes is presented. Finally, simulation results show that the performance of a proposed scheduling algorithm and offloading strategy outperforms than that of a genetic algorithm and a random algorithm. This result can provide an effective optimization for multi-task offloading in UAV-enabled fog computing networks.
机译:在无人驾驶飞行器(UAV)的雾计算网络中,如何有效地卸载到计算节点的多个任务是一个具有挑战性的组合优化问题。在本文中,为了优化支持无人动型的雾计算网络的总延迟,提出了一种基于烟花算法(FWA)的简单调度算法和多任务卸载方案。首先,详细描述了在支持UAV的雾计算网络中卸载多个任务的系统模型。然后,提出了一种简单的调度算法来优化分配给单个节点的任务的延迟。基于调度算法,呈现了所有任务和所有计算节点的多任务卸载方案。最后,仿真结果表明,所提出的调度算法和卸载策略的性能优于遗传算法和随机算法的性能。此结果可以在支持无人机的雾计算网络中提供有效优化的多任务卸载。

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