Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing

Fog computing has emerged as a promising solution for accommodating the surge of mobile traffic and reducing latency, both known to be inherent problems of cloud computing. Fog services, including computation, storage, and networking, are hosted in the vicinity of end users (edge of the network), and, as a result, reliable access is provisioned to delay-sensitive mobile applications. However, in some cases, the fog computing capacity is overwhelmed by the growing number of demands from patrons, particularly during peak hours, and this can subsequently result in acute performance degradation. In this article, we address this problem by proposing a new concept called fog vehicular computing (FVC) to augment the computation and storage power of fog computing. We also design a comprehensive architecture for FVC and present a number of salient applications. The result of implementation clearly shows the effectiveness of the proposed architecture. Finally, some open issues and envisioned directions are discussed for future research in the context of FVC.

[1]  Rajkumar Buyya,et al.  Dynamic remote data auditing for securing big data storage in cloud computing , 2017, Inf. Sci..

[2]  Eui-nam Huh,et al.  Towards task scheduling in a cloud-fog computing system , 2016, 2016 18th Asia-Pacific Network Operations and Management Symposium (APNOMS).

[3]  Ciprian Dobre,et al.  Big Data and Internet of Things: A Roadmap for Smart Environments , 2014, Big Data and Internet of Things.

[4]  Ejaz Ahmed,et al.  A review on remote data auditing in single cloud server: Taxonomy and open issues , 2014, J. Netw. Comput. Appl..

[5]  Albert Y. Zomaya,et al.  Remote Data Auditing in Cloud Computing Environments , 2015, ACM Comput. Surv..

[6]  Song Guo,et al.  Joint Optimization of Task Scheduling and Image Placement in Fog Computing Supported Software-Defined Embedded System , 2016, IEEE Transactions on Computers.

[7]  Rajkumar Buyya,et al.  A survey on vehicular cloud computing , 2014, J. Netw. Comput. Appl..

[8]  Gongjun Yan,et al.  Datacenter at the Airport: Reasoning about Time-Dependent Parking Lot Occupancy , 2012, IEEE Transactions on Parallel and Distributed Systems.

[9]  Luis Rodero-Merino,et al.  Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing , 2014, CCRV.

[10]  Qun Li,et al.  A Survey of Fog Computing: Concepts, Applications and Issues , 2015, Mobidata@MobiHoc.

[11]  Eui-Nam Huh,et al.  Fog Computing: The Cloud-IoT\/IoE Middleware Paradigm , 2016, IEEE Potentials.

[12]  Ivan Stojmenovic,et al.  Fog computing: A cloud to the ground support for smart things and machine-to-machine networks , 2014, 2014 Australasian Telecommunication Networks and Applications Conference (ATNAC).

[13]  Zhaohui Wu,et al.  Intelligent Transportation Systems , 2006, IEEE Pervasive Computing.

[14]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.