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一种基于模糊逻辑的用于云-雾-边缘计算软件定义网络-车载自组网的智能方法:不同参数对资源协调与管理的影响

An Intelligent Approach for Cloud-Fog-Edge Computing SDN-VANETs Based on Fuzzy Logic: Effect of Different Parameters on Coordination and Management of Resources.

作者信息

Qafzezi Ermioni, Bylykbashi Kevin, Ampririt Phudit, Ikeda Makoto, Matsuo Keita, Barolli Leonard

机构信息

Graduate School of Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka 811-0295, Japan.

Department of Information and Communication Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka 811-0295, Japan.

出版信息

Sensors (Basel). 2022 Jan 24;22(3):878. doi: 10.3390/s22030878.

Abstract

The integration of cloud-fog-edge computing in Software-Defined Vehicular Ad hoc Networks (SDN-VANETs) brings a new paradigm that provides the needed resources for supporting a myriad of emerging applications. While an abundance of resources may offer many benefits, it also causes management problems. In this work, we propose an intelligent approach to flexibly and efficiently manage resources in these networks. The proposed approach makes use of an integrated fuzzy logic system that determines the most appropriate resources that vehicles should use when set under various circumstances. These circumstances cover the quality of the network created between the vehicles, its size and longevity, the number of available resources, and the requirements of applications. We evaluated the proposed approach by computer simulations. The results demonstrate the feasibility of the proposed approach in coordinating and managing the available SDN-VANETs resources.

摘要

软件定义车载自组织网络(SDN-VANETs)中云-雾-边缘计算的集成带来了一种新范式,可为支持大量新兴应用提供所需资源。虽然丰富的资源可能带来诸多好处,但也会引发管理问题。在这项工作中,我们提出了一种智能方法,用于灵活高效地管理这些网络中的资源。所提出的方法利用了一个集成模糊逻辑系统,该系统能确定车辆在各种情况下应使用的最合适资源。这些情况包括车辆之间创建的网络质量、其规模和持续时间、可用资源数量以及应用需求。我们通过计算机模拟对所提出的方法进行了评估。结果证明了所提出的方法在协调和管理可用的SDN-VANETs资源方面的可行性。

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