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.
Highlights
According to World Health Organization, around 1.3 million people die every year because of road traffic crashes [1]
Each subfigure represents practically a different set of applications that have similar requirements. Using this configuration we can see how Layer Selection Decision (LSD) relates with the changing characteristics of the edge layer, which are represented by Neighboring Vehicles (NNV) and Average Processing Capability per Neighbor Vehicle (APCpNV)
The results show that when the vehicle is surrounded by many potentially helpful neighbors, the system selects the edge layer as the most appropriate layer for the vehicle to run its applications
Summary
According to World Health Organization, around 1.3 million people die every year because of road traffic crashes [1]. Context-awareness is expected to play a key role in VANETs, by ameliorating traffic management, and other important metrics such as the driving experience, the safety of road users, and the environmental impact [14]. The inter-vehicle communication in VANETs enables a broader horizon of awareness for the state of other vehicles in the network and the condition of the surrounding environment. Such data include information about traffic lights, weather conditions, public safety information, and so on. The paper presents an integrated system, called Integrated Fuzzy-based System for Coordination and Management of Resources (IFS-CMR), which, different from existing approaches, makes a decision following a bottom-up approach in a cloud-fog-edge architecture.
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