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A Multilevel Mobile Fog Computing Offloading Model Based on UAV-Assisted and Heterogeneous Network

机译:基于无人机辅助和异构网络的多级移动雾计算卸载模型

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摘要

The mobile fog computing (MFC) network that integrates unmanned aerial vehicles (UAV) fully exerts its advantages of flexible deployment, load balance, and rapid response. Under complex network environment, proposing a reasonable offloading model and according resource optimization of the MFC network is important to satisfy high-requirement offloading standard. In this paper, a multilevel MFC offloading model where UAV and fog nod undertake relay nodes and offloading computing nodes are established for computation-intensive and latency-critical tasks, considering heterogeneous network selection , dynamic channel quality and central cloud access . With the total system utility optimality function including reward function maximization as the goal, the MDP algorithm is applied to solve the best offloading decision of the computing task and the balanced load mode of the MFC network. Finally, the simulation section verifies the excellent performance of the proposed multilevel MFC offloading model in network resource utilization. Simulation results show that the model can optimize the relative position of service nodes in MFC network and ensure the offloading reliability of terminal equipment.
机译:整合无人驾驶飞行器(UAV)的移动雾计算(MFC)网络完全施加了灵活的部署,负载平衡和快速响应的优势。在复杂的网络环境下,提出合理的卸载模型和根据MFC网络的资源优化对于满足高需求卸载标准非常重要。本文建立了一种多级MFC卸载模型,其中UAV和FOG NOD承接中继节点和卸载计算节点的计算 - 密集型和延迟关键任务,考虑异构网络选择,动态信道质量和中央云访问。通过总系统实用程序最优性功能,包括奖励函数最大化为目标,应用MDP算法来解决计算任务的最佳卸载决定和MFC网络的平衡负载模式。最后,仿真部分验证了在网络资源利用率中提出的多级MFC卸载模型的优异性能。仿真结果表明,该模型可以优化MFC网络中服务节点的相对位置,并确保终端设备的卸载可靠性。

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