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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 7/2021

02.01.2021

Data congestion in VANETs: research directions and new trends through a bibliometric analysis

verfasst von: Tarandeep Kaur Bhatia, Ramkumar Ketti Ramachandran, Robin Doss, Lei Pan

Erschienen in: The Journal of Supercomputing | Ausgabe 7/2021

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Abstract

Vehicular Ad hoc Networks (VANETs) become increasingly popular in academia and manufacturing businesses. The VANETs domain attracts massive attention from various authors all over the world on a large scale. However, substantial research efforts are expected in the VANETs field to solve the data congestion problem. For this, it is vital to state the current status of research in this domain. As the research publications have substantially increased since 2009, a bibliometric analysis is necessary for researchers to understand actual results and findings in this area. This paper examines and analyzes the status of research trends between 2010 and 2019 for the domain “Data congestion in VANETs” by applying various parameters. As extracted from the Scopus database till December 31, 2019, a total of 11,109 publications are associated with the VANETs domain. Moreover, 434 publications among the collection are related to data congestion in the VANETs field. Finally, a software tool named the VOSviewer is used to create and envision the selected field’s bibliometric networks. This analysis paper will help the researchers to catch the research trends of data congestion in VANETs.
Vorheriger Artikel PEPS: predictive energy-efficient parallel scheduler for multi-core processors
Nächster Artikel A contention aware EQS priority assignment heuristic for cohorts in DRTDBS

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Literatur
1.
Abu-Tair M, Min G, Ni Q, Liu H (2010) An adaptive medium access control scheme for mobile ad hoc networks under self-similar traffic. J Supercomput 53(1):212–230
2.
Hartenstein H, Laberteaux L (2008) A tutorial survey on vehicular ad hoc networks. IEEE Commun Mag 46(6):164–171
3.
Ali GMN, Chan E, Li W (2014) On scheduling data access with cooperative load balancing in vehicular ad hoc networks (vanets). J Supercomput 67(2):438–468
4.
Stanica R, Chaput E, Beylot A-L (2011) Simulation of vehicular ad-hoc networks: challenges, review of tools and recommendations. Comput Netw 55(14):3179–3188
5.
Prakash G, Krishnamoorthy R, Kalaivaani P (2019) Resource key distribution and allocation based on sensor vehicle nodes for energy harvesting in vehicular ad hoc networks for transport application. J Supercomput 76:1–14
6.
Cunha F, Villas L, Boukerche A, Maia G, Viana A, Mini RA, Loureiro AA (2016) Data communication in vanets: protocols, applications and challenges. Ad Hoc Netw 44:90–103
7.
Eze EC, Zhang S-J, Liu E-J, Eze JC (2016) Advances in vehicular ad-hoc networks (vanets): challenges and road-map for future development. Int J Autom Comput 13(1):1–18
8.
Saini M, Alelaiwi A, Saddik AE (2015) How close are we to realizing a pragmatic vanet solution? a meta-survey. ACM Comput Surv (CSUR) 48(2):29
9.
Balouchzahi N-M, Fathy M, Akbari A (2016) An efficient infrastructure based service discovery in vehicular networks using p2p structures. J Supercomput 72(3):1013–1034
10.
Arkian HR, Atani RE, Diyanat A, Pourkhalili A (2015) A cluster-based vehicular cloud architecture with learning-based resource management. J Supercomput 71(4):1401–1426
11.
Amer HM, Al-Kashoash H, Hawes M, Chaqfeh M, Kemp A, Mihaylova L (2019) Centralized simulated annealing for alleviating vehicular congestion in smart cities. Technol Forecast Soc Change 142:235–248
12.
Li J, Fu D, Yuan Q, Zhang H, Chen K, Yang S, Yang F (2019) A traffic prediction enabled double rewarded value iteration network for route planning. IEEE Trans Veh Technol 68:4170–4181
13.
Guo C, Li D, Zhang G, Zhai M (2018) Real-time path planning in urban area via vanet-assisted traffic information sharing. IEEE Trans Veh Technol 67(7):5635–5649
14.
Qureshi KN, Abdullah AH, Kaiwartya O, Iqbal S, Butt RA, Bashir F (2018) A dynamic congestion control scheme for safety applications in vehicular ad hoc networks. Comput Electr Eng 72:774–788
15.
Oliveira R, Montez C, Boukerche A, Wangham MS (2017) Reliable data dissemination protocol for vanet traffic safety applications. Ad Hoc Netw 63:30–44
16.
Feukeu E, Zuva T (2017) Dbsma approach for congestion mitigation in vanets. Procedia Comput Sci 109:42–49
17.
Fallah YP, Nasiriani N, Krishnan H (2016) Stable and fair power control in vehicle safety networks. IEEE Trans Veh Technol 65(3):1662–1675
18.
Hamida EB, Noura H, Znaidi W (2015) Security of cooperative intelligent transport systems: standards, threats analysis and cryptographic countermeasures. Electronics 4(3):380–423
19.
Engoulou RG, Bellaïche M, Pierre S, Quintero A (2014) Vanet security surveys. Comput Commun 44:1–13
20.
Mejri MN, Ben-Othman J, Hamdi M (2014) Survey on vanet security challenges and possible cryptographic solutions. Veh Commun 1(2):53–66
21.
Taherkhani N, Pierre S (2016) Centralized and localized data congestion control strategy for vehicular ad hoc networks using a machine learning clustering algorithm. IEEE Trans Intell Trans Syst 17(11):3275–3285
22.
Xu Y, Wu Y, Wu G, Xu J, Liu B, Sun L (2010) Data collection for the detection of urban traffic congestion by vanets. In: 2010 IEEE Asia-Pacific Services Computing Conference, IEEE, pp. 405–410
23.
de Oliveira CHR, Costa APF, Thomaz VF, Silva IA (2019) Low-cost deployment proposal to urban mobility in smart cities. J Supercomput 75(11):7265–7289
24.
Ullah A, Yaqoob S, Imran M, Ning H (2018) Emergency message dissemination schemes based on congestion avoidance in vanet and vehicular fog computing. IEEE Access 7:1570–1585
25.
Knorr F, Baselt D, Schreckenberg M, Mauve M (2012) Reducing traffic jams via vanets. IEEE Trans Veh Technol 61(8):3490–3498
26.
Fernández-González Á, Rosillo R, Miguel-Dávila JÁ, Matellán V (2015) Historical review and future challenges in supercomputing and networks of scientific communication. J Supercomput 71(12):4476–4503
27.
Lewis BR, Templeton GF, Luo X (2007) A scientometric investigation into the validity of is journal quality measures. J Assoc Inform Syst 8(12):35
28.
Rajendran P, Jeyshankar R, Elango B (2011) Scientometric analysis of contributions to journal of scientific and industrial research. Int J Digital Libr Serv 1(2):79–89
29.
Van Raan AF (1997) Scientometrics: state-of-the-art. Scientometrics 38(1):205–218
30.
Mooghali A, Alijani R, Karami N, Khasseh A (2012) Scientometric analysis of the scientometric literature. Int J Inform Sci Manag (IJISM) 9(1):19–31
31.
Schwarze S, Voß S, Zhou G, Zhou G (2012) Scientometric analysis of container terminals and ports literature and interaction with publications on distribution networks. In: Proceedings of the International Conference on Computational Logistics, Springer, pp. 33–52
32.
Straub D (2006) The value of scientometric studies: an introduction to a debate on is as a reference discipline. J Assoc Inform Syst 7(5):241
33.
Serenko A, Bontis N (2004) Meta-review of knowledge management and intellectual capital literature: citation impact and research productivity rankings. Knowl Process Manag 11(3):185–198
34.
Voß S, Zhao X (2005) Some steps towards a scientometric analysis of publications in machine translation. In: Proceedings of the 23rd IASTED IASTED International Multi-Conference Artificial Intelligence and Applications, Innsbruck, Austria. pp. 651–655
35.
Leydesdorff L, Schank T (2008) Dynamic animations of journal maps: indicators of structural changes and interdisciplinary developments. J Am Soc Inform Sci Technol 59(11):1810–1818
36.
Hood W, Wilson C (2001) The literature of bibliometrics, scientometrics, and informetrics. Scientometrics 52(2):291–314
37.
Leydesdorff L (2002) Indicators of structural change in the dynamics of science: Entropy statistics of the sci journal citation reports. Scientometrics 53(1):131–159
38.
Cobo MJ, Chiclana F, Collop A, de Ona J, Herrera-Viedma E (2013) A bibliometric analysis of the intelligent transportation systems research based on science mapping. IEEE Trans Intell Trans Syst 15(2):901–908
39.
Sivaraman S, Trivedi MM (2010) A general active-learning framework for on-road vehicle recognition and tracking. IEEE Trans Intell Trans Syst 11(2):267–276
40.
Fu Y, Tang L, Chen Q, Gong P (2013) Vehicular ad hoc network routing protocol and its research progress [j]. J Comput Appl, vol. 7
41.
Shahid A, Afzal MT, Abdar M, Basiri ME, Zhou X, Yen NY, Chang J-W (2019) Insights into relevant knowledge extraction techniques: a comprehensive review. J Supercomput 76:1–39
42.
Kabir MH (2013) Research issues on vehicular ad hoc network. Intern J Eng Trends Tech (IJETT). 6:174–179
43.
Dalal K, Dahiya P (2017) State-of-the-art in vanets: The core of intelligent transportation system. IUP J Electr Electron Eng. 10(1):27–39
44.
Yang Y, Bagrodia R (2009) Evaluation of vanet-based advanced intelligent transportation systems. In: Proceedings of the Sixth ACM International Workshop on Vehicular Internetworking, pp. 3–12
45.
Liang W, Li Z, Zhang H, Wang S, Bie R (2015) Vehicular ad hoc networks: architectures, research issues, methodologies, challenges, and trends. Int J Distrib Sens Netw 11(8):745303
46.
Eze EC, Zhang S, Liu E (2014) Vehicular ad hoc networks (vanets): Current state, challenges, potentials and way forward. In: Proceedings of the 2014 20th International Conference on Automation and Computing, IEEE, pp. 176–181
47.
Jacobs D (2010) Demystification of bibliometrics, scientometrics, informetrics and webometrics. In: Proceedings of the 11th DIS Annual Conference, pp. 1–19
48.
Sarmiento I, Cardenas Y, Valencia G (2017) Análisis cienciométrico de la investigación de sistemas fotovoltaicos integrados a edificios desde el año, (2000) a 2017. Revista Espacios 38(47):29
49.
Abramo G, Angelo CAD, Caprasecca A (2009) Allocative efficiency in public research funding: Can bibliometrics help? Res Policy 38(1):206–215
50.
Ahmad I, Ahmed G, Shah SAA, Ahmed E (2020) A decade of big data literature: analysis of trends in light of bibliometrics. J Supercomput 76(5):3555–3571
51.
Liu X, Wang M, Fu H (2020) Visualized analysis of knowledge development in green building based on bibliographic data mining. J Supercomput 76(5):3266–3282
52.
Shafiq M, Yu X, Bashir AK, Chaudhry HN, Wang D (2018) A machine learning approach for feature selection traffic classification using security analysis. J Supercomput 74(10):4867–4892
53.
Zeadally S, Hunt R, Chen Y-S, Irwin A, Hassan A (2012) Vehicular ad hoc networks (vanets): status, results, and challenges. Telecommun Syst 50(4):217–241
54.
ur Rehman S, Khan MA, Zia TA, Zheng L (2013) Vehicular ad-hoc networks (vanets)-an overview and challenges. J Wirel Netw Commun 3(3):29–38
55.
Yousefi S, Mousavi MS, Fathy M (2006) Vehicular ad hoc networks (vanets): challenges and perspectives. In: Proceedings of the 2006 6th International Conference on ITS Telecommunications, IEEE, pp. 761–766
56.
Samara G, Al-Salihy WA, Sures R (2010) Security issues and challenges of vehicular ad hoc networks (vanet). In: Proceedings of the 4th International Conference on New Trends in Information Science and Service Science, IEEE, pp. 393–398
57.
Cavalcanti ER, de Souza JAR, Spohn MA, Gomes RCdM, Costa AFBFd (2018) Vanets’ research over the past decade: overview, credibility, and trends. ACM SIGCOMM Comput Commun Rev 48(2):31–39
58.
Liu S, Lee M-H (2013) Research on prospective innovation design of smart electric vehicle. Front Manuf Eng 1(2):1–9
59.
Mussa SAB, Manaf M, Ghafoor KZ, Doukha Z (2015) Simulation tools for vehicular ad hoc networks: A comparison study and future perspectives. In: Proceedings of the 2015 International Conference on Wireless Networks and Mobile Communications (WINCOM ’15), IEEE, pp. 1–8
60.
Fonseca E, Festag A (2006) A survey of existing approaches for secure ad hoc routing and their applicability to vanets. NEC Netw Lab 28:1–28
61.
62.
Kakkasageri M, Manvi S (2014) Information management in vehicular ad hoc networks: a review. J Netw Comput Appl 39:334–350
63.
Hajlaoui R, Guyennet H, Moulahi T (2016) A survey on heuristic-based routing methods in vehicular ad-hoc network: technical challenges and future trends. IEEE Sens J 16(17):6782–6792
64.
Straub DW, Ang S, Evaristo R (1994) Normative standards for is research. ACM SIGMIS Database DATABASE Adv Inform Syst 25(1):21–34
65.
Vrettas G, Sanderson M (2015) Conferences versus journals in computer science. J Assoc Inform Sci Technol 66(12):2674–2684
66.
Mehlhorn K, Vardi MY, Herbstritt M (2012) Publication culture in computing research. Dagstuhl Rep 2(11):20–44
67.
Patterson D, Snyder L, Ullman J (1999) Best practices memo: Evaluating computer scientists and engineers for promotion and tenure. Comput Res News 11(4):A–B
68.
Merton RK (1988) The Matthew effect in science, ii: Cumulative advantage and the symbolism of intellectual property. isis 79(4):606–623
69.
Merton RK (1968) The Matthew effect in science: The reward and communication systems of science are considered. Science 159(3810):56–63
70.
Bonitz M, Bruckner E, Scharnhorst A (1997) Characteristics and impact of the Matthew effect for countries. Scientometrics 40(3):407–422
71.
Faria JR, Goel RK (2010) Returns to networking in academia. NETNOMICS Econ Res Electron Netw 11(2):103–117
72.
Holsapple CW, Johnson LE, Manakyan H, Tanner J (1994) Business computing research journals: a normalized citation analysis. J Manag Inform Syst 11(1):131–140
73.
Howard GS, Cole DA, Maxwell SE (1987) Research productivity in psychology based on publication in the journals of the American psychological association. Am Psychol 42(11):975
74.
Van Eack N, Waltman L (2010) Software survey: Vosviewer a computer program for bibliometric mapping. Scientometrics 84(2):523–538
75.
Van Eck NJ, Waltman L (2013) Vosviewer manual. Univeristeit Leiden, Leiden, pp 1–53
76.
Williams B (2020) Dimensions & vosviewer bibliometrics in the reference interview. Code4Lib Journal, no. 47
77.
Pan X, Yan E, Cui M, Hua W (2018) Examining the usage, citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools. J Inform 12(2):481–493
78.
Choudhary RK, Awasthi S (2018) Bibliometric visualisation tools. Libr Prog (International) 38(2):319–324
79.
Cobo MJ, López-Herrera AG, Herrera-Viedma E, Herrera F (2011) Science mapping software tools: Review, analysis, and cooperative study among tools. J Am Soc Inform Sci Technol 62(7):1382–1402
80.
Boyack KW, Klavans R (2010) Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? J Am Soc Inform Sci Technol 61(12):2389–2404
81.
Yan E, Ding Y (2012) Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. J Am Soc Inform Sci Technol 63(7):1313–1326
82.
Kumar V, Mishra S, Chand N et al (2013) Applications of vanets: present & future. Commun Netw 5(01):12
83.
Hasrouny H, Samhat AE, Bassil C, Laouiti A (2017) Vanet security challenges and solutions: a survey. Veh Commun 7:7–20
84.
Liang L, Ye H, Li GY (2018) Toward intelligent vehicular networks: a machine learning framework. IEEE Internet Things J 6(1):124–135
85.
Kwon J-H, Chang HS, Shon T, Jung J-J, Kim E-J (2016) Neighbor stability-based vanet clustering for urban vehicular environments. J Supercomput 72(1):161–176
86.
87.
Coulter R, Pan L (2018) Intelligent agents defending for an iot world: A review. Comput Secur 73:439–458
88.
Kolandaisamy R, Noor RM, Z’aba MR, Ahmedy I, Kolandaisamy I (2020) Adapted stream region for packet marking based on ddos attack detection in vehicular ad hoc networks. J Supercomput 76(8):5948–5970
89.
Falah A, Pan L, Huda S, Pokhrel SR, Anwar A (2020) Improving malicious pdf classifier with feature engineering: A data-driven approach. Future Gener Comput Syst 115:314–326
90.
Zheng X, Pan L, Chen H, Di Pietro R, Batten L (2017) A testbed for security analysis of modern vehicle systems. In: Proceedings of the 2017 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (Trustcom ’17), IEEE, pp. 1090–1095
91.
Zheng X, Pan L, Chen H, Wang P (2016) Investigating security vulnerabilities in modern vehicle systems. In: Proceedings of the International Conference on Applications and Techniques in Information Security, Springer, pp. 29–40
92.
93.
Liu L, Chen C, Qiu T, Zhang M, Li S, Zhou B (2018) A data dissemination scheme based on clustering and probabilistic broadcasting in vanets. Veh Commun 13:78–88
94.
Schoch E, Kargl F, Weber M, Leinmuller T (2008) Communication patterns in vanets. IEEE Commun Mag 46(11):119–125
95.
Luo Y, Zhang W, Hu Y (2010) A new cluster based routing protocol for vanet. In: Proceedings of the 2010 Second International Conference on Networks Security, Wireless Communications and Trusted Computing, vol. 1, IEEE, pp. 176–180
96.
Nkenyereye L, Park Y, Rhee K-H (2018) Secure vehicle traffic data dissemination and analysis protocol in vehicular cloud computing. J Supercomput 74(3):1024–1044
97.
Fogue M, Garrido P, Martinez FJ, Cano J-C, Calafate CT, Manzoni P (2012) Evaluating the impact of a novel message dissemination scheme for vehicular networks using real maps. Trans Res Part C Emerg Technol 25:61–80
98.
Jerbi M, Senouci S-M, Meraihi R, Ghamri-Doudane Y (2007) An improved vehicular ad hoc routing protocol for city environments. In: Proceedings of the 2007 IEEE International Conference on Communications, IEEE, pp. 3972–3979
99.
Bagherlou H, Ghaffari A (2018) A routing protocol for vehicular ad hoc networks using simulated annealing algorithm and neural networks. J Supercomput 74(6):2528–2552
100.
Xiong W, Li Q-Q (2015) Performance evaluation of data disseminations for vehicular ad hoc networks in highway scenarios. Int Arch Photogramm Remote Sens Spat Inform Sci 37:1015–1020
101.
Caizzone G, Giacomazzi P, Musumeci L, Verticale G (2005) A power control algorithm with high channel availability for vehicular ad hoc networks. In: Proceedings of the IEEE International Conference on Communications (ICC 2005), vol. 5, IEEE, pp. 3171–3176
102.
Jakubiak J, Koucheryavy Y (2008) State of the art and research challenges for vanets. In: Proceedings of the 2008 5th IEEE Consumer Communications and Networking Conference, IEEE, pp. 912–916
103.
104.
Tsai M-F, Wang P-C, Shieh C-K, Hwang W-S, Chilamkurti N, Rho S, Lee YS (2015) Improving positioning accuracy for vanet in real city environments. J Supercomput 71(6):1975–1995
105.
Zhang L, Valaee S (2014) Safety context-aware congestion control for vehicular broadcast networks. In: Proceedings of the 2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC ’14), IEEE, pp. 399–403
106.
Lim J, Jeong YS, Park D-S, Lee H (2018) An efficient distributed mutual exclusion algorithm for intersection traffic control. J Supercomput 74(3):1090–1107
107.
Jain B, Brar G, Malhotra J, Rani S, Ahmed SH (2018) A cross layer protocol for traffic management in social internet of vehicles. Future Gener Comput Syst 82:707–714
108.
You Z, Cheng G, Wang Y, Chen P, Chen S (2019) Cross-layer and sdn based routing scheme for p2p communication in vehicular ad-hoc networks. Appl Sci 9(22):4734
109.
Antonopoulos A, Skianis C, Verikoukis C (2013) Network coding-based cooperative arq scheme for vanets. J Netw Comput Appl 36(3):1001–1007
110.
Zaidi S, Bitam S, Mellouk A (2016) Enhanced adaptive sub-packet forward error correction mechanism for video streaming in vanet. In: Proceedings of the 2016 IEEE Global Communications Conference (GLOBECOM ’16), IEEE, pp 1–6
111.
Jang H-C, Chuang S-C (2012) Cookie-cooperative automatic repeat request for transmission assistance in vanet. Telecommun Syst 50(4):311–324
Metadaten
Titel
Data congestion in VANETs: research directions and new trends through a bibliometric analysis
verfasst von
Tarandeep Kaur Bhatia
Ramkumar Ketti Ramachandran
Robin Doss
Lei Pan
Publikationsdatum
02.01.2021
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 7/2021
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-020-03520-7

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