SVCC-HSR: Providing Secure Vehicular Cloud Computing for Intelligent High-Speed Rail

IEEE Network ◽  
2018 ◽  
Vol 32 (3) ◽  
pp. 64-71 ◽  
Author(s):  
Ping Dong ◽  
Tao Zheng ◽  
Xiaojiang Du ◽  
Hongke Zhang ◽  
Mohsen Guizani
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
High Speed Rail ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

Reply to comment on ‘SFVCC: Chaotic map-based security framework for vehicular cloud computing’

2020 ◽  
Vol 14 (12) ◽  
pp. 1724-1724
Author(s):  
Dheerendra Mishra ◽  
Vinod Kumar ◽  
Dharminder Dhaminder ◽  
Saurabh Rana
Keyword(s):  
Cloud Computing ◽  
Chaotic Map ◽  
Security Framework ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

scholarly journals An energy-efficient failure detector for vehicular cloud computing

PLoS ONE ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. e0191577 ◽  
Author(s):  
Jiaxi Liu ◽  
Zhibo Wu ◽  
Jian Dong ◽  
Jin Wu ◽  
Dongxin Wen
Keyword(s):  
Cloud Computing ◽  
Energy Efficient ◽  
Failure Detector ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

Vehicular Cloud Computing

2014 ◽  
pp. 262-274 ◽  
Author(s):  
Kayhan Zrar Ghafoor ◽  
Marwan Aziz Mohammed ◽  
Kamalrulnizam Abu Bakar ◽  
Ali Safa Sadiq ◽  
Jaime Lloret
Keyword(s):  
Cloud Computing ◽  
Vehicular Networks ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Performance Improvements ◽  
Potential Applications ◽  
Research Outcome ◽  
Hoc Networks

Recently, Vehicular Ad Hoc Networks (VANET) have attracted the attention of research communities, leading car manufacturers, and governments due to their potential applications and specific characteristics. Their research outcome was started with awareness between vehicles for collision avoidance and Internet access and then expanded to vehicular multimedia communications. Moreover, vehicles’ high computation, communication, and storage resources set a ground for vehicular networks to deploy these applications in the near future. Nevertheless, on-board resources in vehicles are mostly underutilized. Vehicular Cloud Computing (VCC) is developed to utilize the VANET resources efficiently and provide subscribers safe infotainment services. In this chapter, the authors perform a survey of state-of-the-art vehicular cloud computing as well as the existing techniques that utilize cloud computing for performance improvements in VANET. The authors then classify the VCC based on the applications, service types, and vehicular cloud organization. They present the detail for each VCC application and formation. Lastly, the authors discuss the open issues and research directions related to VANET cloud computing.

Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

2020 ◽  
pp. 268-296
Author(s):  
Priyanka Gaba ◽  
Ram Shringar Raw
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Fog Computing ◽  
Detailed Comparison ◽  
Fast Response ◽  
Computing Technique ◽  
Vehicular Cloud ◽  
Network Bandwidth ◽  
Real Time Applications ◽  
Safety Features

VANET, a type of MANET, connects vehicles to provide safety and non-safety features to the drivers and passengers by exchanging valuable data. As vehicles on road are increasing to handle such data cloud computing, functionality is merged with vehicles known as Vehicular Cloud Computing(VCC) to serve VANET with computation, storage, and networking functionalities. But Cloud, a centralized server, does not fit well for vehicles needing high-speed processing, low latency, and more security. To overcome these limitations of Cloud, Fog computing was evolved, extending the functionality of cloud computing model to the edge of the network. This works well for real time applications that need fast response, saves network bandwidth, and is a reliable, secure solution. An application of Fog is with vehicles known as Vehicular Fog Computing (VFC). This chapter discusses cloud computing technique and its benefits and drawbacks, detailed comparison between VCC and VFC, applications of Fog Computing, its security, and forensic challenges.

Vehicular Cloud Computing Security: A Survey

2019 ◽  
Vol 45 (4) ◽  
pp. 2473-2499
Author(s):  
Hadjer Goumidi ◽  
Zibouda Aliouat ◽  
Saad Harous
Keyword(s):  
Cloud Computing ◽  
Cloud Computing Security ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

scholarly journals A Safety Resource Allocation Mechanism against Connection Fault for Vehicular Cloud Computing

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Tianpeng Ye ◽  
Zhou Su ◽  
Jun Wu ◽  
Longhua Guo ◽  
Jianhua Li ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation System ◽  
Probability Model ◽  
Allocation Mechanism ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Resource Allocation Mechanism

The Intelligent Transportation System (ITS) becomes an important component of the smart city toward safer roads, better traffic control, and on-demand service by utilizing and processing the information collected from sensors of vehicles and road side infrastructure. In ITS, Vehicular Cloud Computing (VCC) is a novel technology balancing the requirement of complex services and the limited capability of on-board computers. However, the behaviors of the vehicles in VCC are dynamic, random, and complex. Thus, one of the key safety issues is the frequent disconnections between the vehicle and the Vehicular Cloud (VC) when this vehicle is computing for a service. More important, the connection fault will disturb seriously the normal services of VCC and impact the safety works of the transportation. In this paper, a safety resource allocation mechanism is proposed against connection fault in VCC by using a modified workflow with prediction capability. We firstly propose the probability model for the vehicle movement which satisfies the high dynamics and real-time requirements of VCC. And then we propose a Prediction-based Reliability Maximization Algorithm (PRMA) to realize the safety resource allocation for VCC. The evaluation shows that our mechanism can improve the reliability and guarantee the real-time performance of the VCC.

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