An Energy-Aware Service Management Algorithm for Vehicular Cloud Computing

Author(s):  
Sohan Kumar Pande ◽  
Sanjaya Kumar Panda ◽  
Satyabrata Das
2021 ◽  
Vol 67 (2) ◽  
pp. 2647-2663
Author(s):  
Sohan Kumar Pande ◽  
Sanjaya Kumar Panda ◽  
Satyabrata Das ◽  
Kshira Sagar Sahoo ◽  
Ashish Kr. Luhach ◽  
...  

2020 ◽  
Vol 14 (12) ◽  
pp. 1724-1724
Author(s):  
Dheerendra Mishra ◽  
Vinod Kumar ◽  
Dharminder Dhaminder ◽  
Saurabh Rana

PLoS ONE ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. e0191577 ◽  
Author(s):  
Jiaxi Liu ◽  
Zhibo Wu ◽  
Jian Dong ◽  
Jin Wu ◽  
Dongxin Wen

Author(s):  
Kayhan Zrar Ghafoor ◽  
Marwan Aziz Mohammed ◽  
Kamalrulnizam Abu Bakar ◽  
Ali Safa Sadiq ◽  
Jaime Lloret

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.


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

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Tianpeng Ye ◽  
Zhou Su ◽  
Jun Wu ◽  
Longhua Guo ◽  
Jianhua Li ◽  
...  

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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