A Fuzzy-Based System for Cloud-Fog-Edge Selection in VANETs

Vehicular Ad Hoc Networks (VANETs) have gained a great attention due to the rapid development of mobile internet and Internet of Things (IoT) applications. With the evolution of technology, it is expected that VANETs will be massively deployed in upcoming vehicles. However, these kinds of wireless networks face several technical challenges in deployment and management due to variable capacity of wireless links, bandwidth constrains, high latency and dynamic topology. Cloud computing, fog computing and edge computing are considered a way to deal with these communication challenges. In this paper, we propose a Fuzzy-based System for Resource Coordination and Management (FSRCM) in VANETs. The proposed system considers vehicle mobility, data size, time sensitivity and remained storage capacity to select processing layer of the VANETs application data. We evaluated the performance of proposed system by computer simulations. From the simulations results, we conclude that the vehicles choose the appropriate layer to process and keep the data based on their velocity, remained storage and data size.

[1]  Sangjin Kim,et al.  Rethinking Vehicular Communications: Merging VANET with cloud computing , 2012, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings.

[2]  Xuemin Shen,et al.  Toward Efficient Content Delivery for Automated Driving Services: An Edge Computing Solution , 2018, IEEE Network.

[3]  Stephan Olariu,et al.  Taking VANET to the clouds , 2011, Int. J. Pervasive Comput. Commun..

[4]  F. Martin McNeill,et al.  Fuzzy Logic: A Practical Approach , 1994 .

[5]  Hannes Hartenstein,et al.  A tutorial survey on vehicular ad hoc networks , 2008, IEEE Communications Magazine.

[6]  Silvia Giordano,et al.  The Next Paradigm Shift: From Vehicular Networks to Vehicular Clouds , 2013 .

[7]  Song Guo,et al.  Vehicular cloud computing: A survey , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[8]  Ivan Stojmenovic,et al.  An overview of Fog computing and its security issues , 2016, Concurr. Comput. Pract. Exp..

[9]  L. Zadeh,et al.  Fuzzy Logic for the Management of Uncertainty , 1992 .

[10]  Toshinori Munakata,et al.  Fuzzy systems: an overview , 1994, CACM.

[11]  Abraham Kandel,et al.  Fuzzy Expert Systems , 1991 .

[12]  Eylem Ekici,et al.  Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions , 2011, IEEE Communications Surveys & Tutorials.

[13]  Ebrahim H. Mamdani,et al.  A linguistic self-organizing process controller , 1979, Autom..

[14]  Xiaohu Ge,et al.  5G Software Defined Vehicular Networks , 2017, IEEE Communications Magazine.

[15]  Paolo Santi Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks , 2012 .