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A Research on Data Rate and Computation Offloading in Joint Optimization for Fog Computing

机译:用于雾计算联合优化的数据速率与计算卸载研究

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Fog computing provides low-latency and low-energy computing services for user devices and is widely used in many fields, such as industry, smart cities, and smart transportation. However, the data rate is an important metric in the information field that has been little studied by previous researches. In this paper, we investigate the relationship between the data rate and the cost, the data rate and the fog-cloud resource utilization in different scenarios in joint computation offloading. Through extensive simulation experiments, it is found that the cost in the energy-sensitive scenario is the lowest among the three scenarios, and the resource utilization of cloud computing keeps rising and that of fog computing keeps falling as the data rate increases. This provides a basis for the deployment and scheduling of fog-cloud resources in the future.
机译:雾计算为用户设备提供低延迟和低电平计算服务,广泛应用于许多领域,如行业,智能城市和智能运输。 但是,数据速率是以前研究的信息领域的一个重要指标。 在本文中,我们研究了数据速率与成本之间的关系,在联合计算卸载中的不同场景中的数据速率和雾云资源利用。 通过广泛的模拟实验,发现能量敏感方案的成本是三种情况中最低的,云计算的资源利用率保持上升,并且由于数据速率的增加,雾计算的资源不断下降。 这为将来提供了雾云资源的部署和调度。

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