Journal of Computer Science and Technology ›› 2019, Vol. 34 ›› Issue (4): 869-886.doi: 10.1007/s11390-019-1947-3

Special Issue: Surveys; Computer Architecture and Systems; Computer Networks and Distributed Computing

• Computer Networks and Distributed Computing • Previous Articles     Next Articles

Edge Computing Based Applications in Vehicular Environments: Comparative Study and Main Issues

Leo Mendiboure1, Student Member, IEEE, Mohamed-Aymen Chalouf2, Francine Krief3   

  1. 1 LaBRI Laboratory, University of Bordeaux, Talence 33400, France;
    2 IRISA Laboratory, University of Rennes 1, Lannion 22300, France;
    3 LaBRI Laboratory, Bordeaux INP, Talence 33400, France
  • Received:2018-08-20 Revised:2019-05-15 Online:2019-07-11 Published:2019-07-11

Despite the expanded efforts, the vehicular ad-hoc networks (VANETs) are still facing many challenges such as network performances, network scalability and context-awareness. Many solutions have been proposed to overcome these obstacles, and the edge computing, an extension of the cloud computing, is one of them. With edge computing, communication, storage and computational capabilities are brought closer to end users. This could offer many benefits to the global vehicular network including, for example, lower latency, network off-loading and context-awareness (location, environment factors, etc.). Different approaches of edge computing have been developed:mobile edge computing (MEC), fog computing (FC) and cloudlet are the main ones. After introducing the vehicular environment background, this paper aims to study and compare these different technologies. For that purpose their main features are compared and the state-ofthe-art applications in VANETs are analyzed. In addition, MEC, FC, and cloudlet are classified and their suitability level is debated for different types of vehicular applications. Finally, some challenges and future research directions in the fields of edge computing and VANETs are discussed.

Key words: cloud computing; edge computing; fog computing; cloudlet; vehicular network;

[1] Vijayakumar P, Azees M, Kannan A, Deborah L J. Dual authentication and key management techniques for secure data transmission in vehicular ad hoc networks. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(4):1015-1028.
[2] Zheng K, Zheng Q, Chatzimisios P, Xiang W, Zhou Y. Heterogeneous vehicular networking:A survey on architecture, challenges, and solutions. IEEE Communications Surveys & Tutorials, 2015, 17(4):2377-2396.
[3] Bouali T, Senouci S M. A fuzzy logic-based communication medium selection for QoS preservation in vehicular networks. In Proc. the 5th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications, November 2015, pp.101-108.
[4] He D, Zeadally S, Xu B, Huang X. An efficient identitybased conditional privacy-preserving authentication scheme for vehicular ad hoc networks. IEEE Transactions on Information Forensics and Security, 2015, 10(12):2681-2691.
[5] La Vinh H, Cavalli A. Security attacks and solutions in vehicular ad hoc networks:A survey. International Journal on Ad Hoc Networking Systems, 2014, 4(2):1-20.
[6] Raw R S, Kumar M, Singh N. Security challenges, issues and their solutions for VANET. International Journal of Network Security & Its Applications, 2013, 5(5):95-105.
[7] Liang W, Li Z, Zhang H, Wang S, Bie R. Vehicular ad hoc networks:Architectures, research issues, methodologies, challenges, and trends. International Journal of Distributed Sensor Networks, 2015, 11:Article No. 745303.
[8] Rasheed A, Gillani S, Ajmal S, Qayyum A. Vehicular ad hoc network (VANET):A survey, challenges, and applications. In Proc. the 2nd Int. Workshop on Vehicular Ad-Hoc Networks for Smart Cities, April 2016, pp.39-51.
[9] Hussain R, Son J, Eun H, Kim S, Oh H. Rethinking vehicular communications:Merging VANET with cloud computing. In Proc. the 4th IEEE International Conference on Cloud Computing Technology and Science, December 2012, pp.606-609.
[10] Jabbarpour M R, Marefat A, Jalooli A, Zarrabi H. Couldbased vehicular networks:A taxonomy, survey, and conceptual hybrid architecture. Wireless Networks, 2019, 25(1):335-354.
[11] Shi W, Cao J, Zhang Q, Li Y, Xu L. Edge computing:Vision and challenges. IEEE Internet of Things Journal, 2016, 3(5):637-646.
[12] Ha K, Pillai P, Lewis G, Simanta S, Clinch S, Davies N, Satyanarayanan M. The impact of mobile multimedia applications on data center consolidation. In Proc. the 2013 IEEE International Conference on Cloud Engineering, March 2013, pp.166-176.
[13] Dolui K, Datta S K. Comparison of edge computing implementations:Fog computing, cloudlet and mobile edge computing. In Proc. the 2017 Global Internet of Things Summit, June 2017, Article No. 77.
[14] Baktir A C, Ozgovde A, Ersoy C. How can edge computing benefit from software-defined networking:A survey, use cases, and future directions. IEEE Communications Surveys & Tutorials, 2017, 19(4):2359-2391.
[15] Wang S, Zhang X, Zhang Y, Wang L, Yang J, Wang W. A survey on mobile edge networks:Convergence of computing, caching and communications. IEEE Access, 2017, 5:6757-6779.
[16] Borcoci E, Vochin M, Obreja S. Mobile edge computing versus fog computing in Internet of Vehicles. In Proc. the 10th International Conference on Advances in Future Internet, September 2018, pp.8-15.
[17] Yaqoob I, Ahmad I, Ahmed E, Gani A, Imran M, Guizani N. Overcoming the key challenges to establishing vehicular communication:Is SDN the answer? IEEE Communications Magazine, 2017, 55(7):128-134.
[18] Huang X, Yu R, Kang J, He Y, Zhang Y. Exploring mobile edge computing for 5G-enabled software defined vehicular networks. IEEE Wireless Communications, 2017, 24(6):55-63.
[19] Anaya J J, Merdrignac P, Shagdar O, Nashashibi F, Naranjo J E. Vehicle to pedestrian communications for protection of vulnerable road users. In Proc. the 2014 IEEE Intelligent Vehicles Symposium, June 2014, pp.1037-1042.
[20] Ota Y, Taniguchi H, Nakajima T, Liyanage K M, Baba J, Yokoyama A. Autonomous distributed V2G (vehicle-togrid) satisfying scheduled charging. IEEE Transactions on Smart Grid, 2012, 3(1):559-564.
[21] Tomar R, Prateek M, Sastry G H. Vehicular ad hoc network (vanet)-An introduction. International Journal of Control Theory and Applications, 2016, 9(18):8883-8888.
[22] Bergenhem C, Shladover S, Coelingh E, Englund C, TsugAwa S. Overview of platooning systems. In Proc. the 19th ITS World Congress, October 2012, Article No. EU-00336.
[23] Fagnant D J, Kockelman K M. The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transportation Research Part C:Emerging Technologies, 2014, 40:1-13.
[24] Umamaheswari S, Priya R M. An efficient healthcare monitoring system in vehicular ad hoc networks. International Journal of Computer Applications, 2013, 78(7):45-49.
[25] Liu L, Zhang X, Qiao M, Shi W. SafeShareRide:Edgebased attack detection in ridesharing services. In Proc. the 2018 IEEE/ACM Symposium on Edge Computing, October 2018, pp.17-29.
[26] Satyanarayanan M, Bahl P, Cáceres R, Davies N. The case for VM-based cloudlets in mobile computing. IEEE Pervasive Computing, 2009, 8(4):14-23.
[27] Satyanarayanan M. The emergence of edge computing. IEEE Computer, 2017, 50(1):30-39.
[28] Bilal K, Khalid O, Erbad A, Khan S U. Potentials, trends, and prospects in edge technologies:Fog, cloudlet, mobile edge, and micro data centers. Computer Networks, 2018, 130:94-120.
[29] Jelassi S, Bouzid A, Youssef H. QoE-driven video streaming system over cloud-based VANET. In Proc. the 8th International Workshop on Communication Technologies for Vehicles, May 2015, pp.84-93.
[30] Garai M, Rekhis S, Boudriga N. Communication as a service for cloud VANETs. In Proc. the 2015 IEEE Symposium on Computers and Communication, July 2015, pp.371-377.
[31] Yu R, Ding J, Huang X, Zhou M T, Gjessing S, Zhang Y. Optimal resource sharing in 5G-enabled vehicular networks:A matrix game approach. IEEE Transactions on Vehicular Technology, 2016, 65(10):7844-7856.
[32] Otomo M, Sato G, Shibata Y. In-vehicle cloudlet computing based on delay tolerant network protocol for disaster information system. In Proc. the 11th International Conference on Broad-Band and Wireless Computing, Communication and Applications, November 2016, pp.255-266.
[33] Hagenauer F, Sommer C, Higuchi T, Altintas O, Dressler F. Vehicular micro clouds as virtual edge servers for efficient data collection. In Proc. the 2nd ACM International Workshop on Smart, Autonomous, and Connected Vehicular Systems and Services, October 2017, pp.31-35.
[34] Wang C, Li Y, Jin D, Chen S. On the serviceability of mobile vehicular cloudlets in a large-scale urban environment. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(10):2960-2970.
[35] Li L, Li Y, Hou R. A novel mobile edge computing-based architecture for future cellular vehicular networks. In Proc. the 2017 IEEE Wireless Communications and Networking Conference, March 2017, Article No. 352.
[36] Yuan Q, Zhou H, Li J, Liu Z, Yang F, Shen X S. Toward efficient content delivery for automated driving services:An edge computing solution. IEEE Network, 2018, 32(1):80-86.
[37] Liu J, Wan J, Zeng B, Wang Q, Song H, Qiu M. A scalable and quick-response software defined vehicular network assisted by mobile edge computing. IEEE Communications Magazine, 2017, 55(7):94-100.
[38] Zhang K, Mao Y, Leng S, He Y, Zhang Y. Mobileedge computing for vehicular networks:A promising network paradigm with predictive off-loading. IEEE Vehicular Technology Magazine, 2017, 12(2):36-44.
[39] Huang C M, Chiang M S, Dao D T, Su W L, Xu S, Zhou H. V2V data offloading for cellular network based on the software defined network (SDN) inside mobile edge computing (MEC) architecture. IEEE Access, 2018, 6:17741-17755.
[40] Vigneri L, Spyropoulos T, Barakat C. Quality of experienceaware mobile edge caching through a vehicular cloud. In Proc. the 20th ACM International Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems, November 2017, pp.91-98.
[41] Datta S K, Bonnet C, Haerri J. Fog computing architecture to enable consumer centric Internet of things services. In Proc. the 2015 International Symposium on Consumer Electronics, June 2015, Article No. 15.
[42] Wang X, Ning Z, Wang L. Offloading in Internet of Vehicles:A fog-enabled real-time traffic management system. IEEE Transactions on Industrial Informatics, 2018, 14(10):4568-4578.
[43] Sookhak M, Yu F R, He Y, Talebian H, Safa N S, Zhao N, Khan M K, Kumar N. Fog vehicular computing:Augmentation of fog computing using vehicular cloud computing. IEEE Vehicular Technology Magazine, 2017, 12(3):55-64.
[44] Hou X, Li Y, Chen M, Wu D, Jin D, Chen S. Vehicular fog computing:A viewpoint of vehicles as the infrastructures. IEEE Transactions on Vehicular Technology, 2016, 65(6):3860-3873.
[45] Zhang W, Zhang Z, Chao H C. Cooperative fog computing for dealing with big data in the Internet of Vehicles:Architecture and hierarchical resource management. IEEE Communications Magazine, 2017, 55(12):60-67.
[46] Darwish T S, Bakar K A. Fog based intelligent transportation big data analytics in the Internet of Vehicles environment:Motivations, architecture, challenges, and critical issues. IEEE Access, 2018, 6:15679-15701.
[47] Yu R, Zhang Y, Gjessing S, Xia W, Yang K. Toward cloudbased vehicular networks with efficient resource management. IEEE Network, 2013, 27(5):48-55.
[48] Grover J, Jain A, Singhal S, Yadav A. Real-time VANET applications using fog computing. In Proc. the 1st International Conference on Smart System, Innovations and Computing, April 2017, pp.683-691.
[49] Hasrouny H, Samhat A E, Bassil C, Laouiti A. VANet security challenges and solutions:A survey. Vehicular Communications, 2017, 7:7-20.
[50] Wang L, Liu G, Sun L. A secure and privacy-preserving navigation scheme using spatial crowdsourcing in fog-based VANETs. Sensors, 2017, 17(4):Article No. 668.
[51] Mukherjee M, Matam R, Shu L, Maglaras L, Ferrag M A, Choudhury N, Kumar V. Security and privacy in fog computing:Challenges. IEEE Access, 2017, 5:19293-19304.
[52] Huang C, Lu R, Choo K K R. Vehicular fog computing:Architecture, use case, and security and forensic challenges. IEEE Communications Magazine, 2017, 55(11):105-111.
[53] Shaukat U, Ahmed E, Anwar Z, Xia F. Cloudlet deployment in local wireless networks:Motivation, architectures, applications, and open challenges. Journal of Network and Computer Applications, 2016, 62:18-40.
[54] Alouache L, Nguyen N, Aliouat M, Chelouah R. Nouveau protocole robuste pour les communications dans l'IoV. Internet des objets, 2017, 17-1(1):3-19. (in French)
[55] Oliveira R, Montez C, Boukerche A, Wangham M S. Reliable data dissemination protocol for VANET traffic safety applications. Ad Hoc Networks, 2017, 63:30-44.
[56] Rasool I U, Zikria Y B, Kim S W. A review of wireless access vehicular environment multichannel operational medium access control protocols:Quality-of-service analysis and other related issues. International Journal of Distributed Sensor Networks, 2017, 13(5):Article No. 23.
[57] Li H, Shou G, Hu Y, Guo Z. Mobile edge computing:Progress and challenges. In Proc. the 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, March 2016, pp.83-84.
[58] Mekki T, Jabri I, Rachedi A, ben Jemaa M. Vehicular cloud networks:Challenges, architectures, and future directions. Vehicular Communications, 2017, 9:268-280.
[59] Skarlat O, Nardelli M, Schulte S, Dustdar S. Towards QoSaware fog service placement. In Proc. the 1st IEEE International Conference on Fog and Edge Computing, May 2017, pp.89-96.
[60] Jiang Y, Huang Z, Tsang D H. Challenges and solutions in fog computing orchestration. IEEE Network, 2018, 32(3):122-129.
[61] Ahmed E, Rehmani M H. Mobile edge computing:Opportunities, solutions, and challenges. Future Generation Computer Systems, 2017, 70:59-63.
[62] Zhang H, Liu N, Chu X, Long K, Aghvami A H, Leung V C. Network slicing based 5G and future mobile networks:Mobility, resource management, and challenges. IEEE Communications Magazine, 2017, 55(8):138-145.
[63] Chang C Y, Alexandris K, Nikaein N, Katsalis K, Spyropoulos T. MEC architectural implications for LTE/LTEA networks. In Proc. the 2016 Workshop on Mobility in the Evolving Internet Architecture, October 2016, pp.13-18.
[1] Jiang Rong, Tao Qin, Bo An. Competitive Cloud Pricing for Long-Term Revenue Maximization [J]. Journal of Computer Science and Technology, 2019, 34(3): 645-656.
[2] Fateh Boucenna, Omar Nouali, Samir Kechid, M. Tahar Kechadi. Secure Inverted Index Based Search over Encrypted Cloud Data with User Access Rights Management [J]. Journal of Computer Science and Technology, 2019, 34(1): 133-154.
[3] Yang Li, Wen-Zhuo Song, Bo Yang. Stochastic Variational Inference-Based Parallel and Online Supervised Topic Model for Large-Scale Text Processing [J]. Journal of Computer Science and Technology, 2018, 33(5): 1007-1022.
[4] Bao-Kun Zheng, Lie-Huang Zhu, Meng Shen, Feng Gao, Chuan Zhang, Yan-Dong Li, Jing Yang. Scalable and Privacy-Preserving Data Sharing Based on Blockchain [J]. , 2018, 33(3): 557-567.
[5] An-Zhen Zhang, Jian-Zhong Li, Hong Gao, Yu-Biao Chen, Heng-Zhao Ma, Mohamed Jaward Bah. CrowdOLA: Online Aggregation on Duplicate Data Powered by Crowdsourcing [J]. , 2018, 33(2): 366-379.
[6] Qin Liu, Yuhong Guo, Jie Wu, Guojun Wang. Effective Query Grouping Strategy in Clouds [J]. Journal of Computer Science and Technology, 2017, 32(6): 1231-1249.
[7] Wei-Qing, Liu Jing Li. An Approach to Automatic Performance Prediction for Cloud-enhanced Mobile Applications with Sparse Data [J]. , 2017, 32(5): 936-956.
[8] Yuhun Jun, Jaemin Lee, Euiseong Seo. Evaluation of Remote-I/O Support for a DSM-Based Computation Offloading Scheme [J]. , 2017, 32(5): 957-973.
[9] Dong-Gang Cao, Bo An, Pei-Chang Shi, Huai-Min Wang. Providing Virtual Cloud for Special Purposes on Demand in JointCloud Computing Environment [J]. , 2017, 32(2): 211-218.
[10] Zuo-Ning Chen, Kang Chen, Jin-Lei Jiang, Lu-Fei Zhang, Song Wu, Zheng-Wei Qi, Chun-Ming Hu, Yong-Wei Wu, Yu-Zhong Sun, Hong Tang, Ao-Bing Sun, Zi-Lu Kang. Evolution of Cloud Operating System: From Technology to Ecosystem [J]. , 2017, 32(2): 224-241.
[11] Bin-Lei Cai, Rong-Qi Zhang, Xiao-Bo Zhou, Lai-Ping Zhao, Ke-Qiu Li. Experience Availability: Tail-Latency Oriented Availability in Software-Defined Cloud Computing [J]. , 2017, 32(2): 250-257.
[12] Xian-Mang He, Xiaoyang Sean Wang, Member, CCF, ACM, IEEE, Dong Li, Yan-Ni Hao. Semi-Homogenous Generalization:Improving Homogenous Generalization for Privacy Preservation in Cloud Computing [J]. , 2016, 31(6): 1124-1135.
[13] Farrukh Nadeem, Rizwan Qaiser. An Early Evaluation and Comparison of Three Private Cloud Computing Software Platforms [J]. , 2015, 30(3): 639-654.
[14] Claudia Canali, Riccardo Lancellotti. Improving Scalability of Cloud Monitoring Through PCA-Based Clustering of Virtual Machines [J]. , 2014, 29(1): 38-52.
[15] Bo Yang, Xiao-Qiong Pang, Jun-Qiang Du, and Dan Xie. Effective Error-Tolerant Keyword Search for Secure Cloud Computing [J]. , 2014, 29(1): 81-89.
Full text



[1] C.Y.Chung; H.R.Hwa;. A Chinese Information Processing System[J]. , 1986, 1(2): 15 -24 .
[2] Zhang Cui; Zhao Qinping; Xu Jiafu;. Kernel Language KLND[J]. , 1986, 1(3): 65 -79 .
[3] Huang Xuedong; Cai Lianhong; Fang Ditang; Chi Bianjin; Zhou Li; Jiang Li;. A Computer System for Chinese Character Speech Input[J]. , 1986, 1(4): 75 -83 .
[4] Tang Tonggao; Zhao Zhaokeng;. Stack Method in Program Semantics[J]. , 1987, 2(1): 51 -63 .
[5] Xia Peisu; Fang Xinwo; Wang Yuxiang; Yan Kaiming; Zhang Tingjun; Liu Yulan; Zhao Chunying; Sun Jizhong;. Design of Array Processor Systems[J]. , 1987, 2(3): 163 -173 .
[6] Sun Yongqiang; Lu Ruzhan; Huang Xiaorong;. Termination Preserving Problem in the Transformation of Applicative Programs[J]. , 1987, 2(3): 191 -201 .
[7] Lin Qi; Xia Peisu;. The Design and Implementation of a Very Fast Experimental Pipelining Computer[J]. , 1988, 3(1): 1 -6 .
[8] Xie Li; Chen Peipei; Yang Peigen; Sun Zhongxiu;. The Design and Implementation of an OA System ZGL1[J]. , 1988, 3(1): 75 -80 .
[9] Luo Yinfang;. Algorithm and Implementation of Parallel Multiplication in a Mixed Number System[J]. , 1988, 3(3): 203 -213 .
[10] Chen Guoliang;. A Partitioning Selection Algorithm on Multiprocessors[J]. , 1988, 3(4): 241 -250 .

ISSN 1000-9000(Print)

CN 11-2296/TP

Editorial Board
Author Guidelines
Journal of Computer Science and Technology
Institute of Computing Technology, Chinese Academy of Sciences
P.O. Box 2704, Beijing 100190 P.R. China
  Copyright ©2015 JCST, All Rights Reserved