Toward vehicular cloud/fog communication: A survey on data dissemination in vehicular ad hoc networks using vehicular cloud/fog computing

被引:28
作者
Gaouar, Nihal [1 ]
Lehsaini, Mohamed [1 ]
机构
[1] Tlemcen Univ, Dept Comp Sci, STIC Lab, Tilimsen, Algeria
关键词
cloud computing; fog computing; VANETs; vehicular cloud computing; vehicular fog computing; ROUTING PROTOCOL; VANET; MANAGEMENT; MULTICAST; SECURITY;
D O I
10.1002/dac.4906
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The digitization of objects has given birth to the concept of the Internet of Things (IoT) which is revolutionizing traditional objects by replacing them with intelligent objects such as smart vehicles, smartphones, smart home horizontal ellipsis etc. In this context, and with the emergence of vehicle networks, is born the need to increase the vehicular resources in order to benefit from several applications facilitating driving and ensuring the drivers safety, even going to think of the automated driving. The use of cloud computing has become the key solution to the lack of resources required to run compute-intensive applications and the lack of storage space to back up all data related to roads and applications. In addition, we are witnessing the birth of the fog computing paradigm, which brings the functionalities of cloud computing at the edge of the network, thereby solving the latency problem for some time-sensitive applications and also saving the bandwidth of the network because vehicle requests will not need to cross the entire network to be processed at the cloud level. In this paper, we discuss the different principles of cloud/fog computing and compare the two paradigms. We present a classification of data dissemination schemes in vehicular ad hoc networks (VANETs), vehicular cloud, and vehicular fog computing with their different architectures proposed. We finally present several cloud/fog computing applications.
引用
收藏
页数:27
相关论文
共 87 条
[1]  
Aazam M, 2015, 2015 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATION WORKSHOPS (PERCOM WORKSHOPS), P518, DOI 10.1109/PERCOMW.2015.7134091
[2]  
Abualigah L.M.Q, 2019, STUDIES COMPUTATIONA, P1
[3]   Hybrid clustering analysis using improved krill herd algorithm [J].
Abualigah, Laith Mohammad ;
Khader, Ahamad Tajudin ;
Hanandeh, Essam Said .
APPLIED INTELLIGENCE, 2018, 48 (11) :4047-4071
[4]   A new feature selection method to improve the document clustering using particle swarm optimization algorithm [J].
Abualigah, Laith Mohammad ;
Khader, Ahamad Tajudin ;
Hanandeh, Essam Said .
JOURNAL OF COMPUTATIONAL SCIENCE, 2018, 25 :456-466
[5]  
Agarwal Yash, 2018, International Journal of Transportation Science and Technology, V7, P60, DOI 10.1016/j.ijtst.2017.12.001
[6]   Characterizing the role of vehicular cloud computing in road traffic management [J].
Ahmad, Iftikhar ;
Noor, Rafidah Md ;
Ali, Ihsan ;
Imran, Muhammad ;
Vasilakos, Athanasios .
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2017, 13 (05)
[7]   Collaborative Vehicle Location Management Service for Enhanced Hybrid Reactive and Proactive Multicast in VANETs [J].
Al-Ezaly, Esraa ;
Abu-Elkeir, Mervat ;
Riad, Alaa .
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2017, 42 (02) :691-704
[8]   A comprehensive survey on vehicular Ad Hoc network [J].
Al-Sultan, Saif ;
Al-Doori, Moath M. ;
Al-Bayatti, Ali H. ;
Zedan, Hussien .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2014, 37 :380-392
[9]  
Alhamad M., 2010, 2010 4th IEEE International Conference on Digital Ecosystems and Technologies (DEST 2010), P606, DOI 10.1109/DEST.2010.5610586
[10]  
[Anonymous], 2011, P 4 INT S APPL SCI B