Information-Centric Content Management Framework for Software Defined Internet of Vehicles Towards Application Specific Services
Abstract
Software defined network (SDN) architectures are assimilated with vehicular communication networks in order to improve the real-time application support for the driving users. Internet of vehicles (IoV) paradigm provides information-centric application support for the road-side users. Information sharing through the road-side units (RSUs) influences the application services due to the frequent change in physical attributes of the vehicles. Considering the application oriented services and information handling in IoV, this article introduces information-centric content management framework (ICMF) for effective information utilization in the vehicular networks. This framework performs data acquisition, smoothing and management process for effective information analysis and better offloading. The proposed framework incorporates the functions of linear vector quantization for classifying acquired information and segregating it for maximum utilization. This quantization is recurrent in both continuous and alternating learning process to improve the reliability of information handling and management. The performance of the proposed framework is verified using simulations and the results prove its efficiency. The proposed framework is found to maximize resource utilization and offloading ratio with less analysis time and overhead. The simulation is verified for the varying density of vehicles, offloading ratio, and communication time, information utilization.
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Manogaran et al. introduced the information-centric content management framework (ICMF), designed to streamline data acquisition, analysis, and management, thereby optimizing information use with minimal time and overhead.
“In parallel, Manogaran et al. [95] introduced the information-centric content management framework (ICMF), designed to streamline data acquisition, analysis, and management, thereby optimizing information use with minimal time and overhead.”
From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [95]
Cites
Mobile Edge Intelligence and Computing for the Internet of Vehicles
Zhang, J., & Letaief, K. B. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2947490 · Cited by 537 · see citing works
Blockchain-Based Internet of Vehicles: Distributed Network Architecture and Performance Analysis
Jiang, T., Fang, H., & Wang, H. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2874398 · Cited by 376 · see citing works
SDN/NFV-Empowered Future IoV With Enhanced Communication, Computing, and Caching
Zhuang, W., Ye, Q. J., Lyu, F., Cheng, N., & Ren, J. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2951169 · Cited by 304 · see citing works
Yang, H., Xie, X., & Kadoch, M. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2890686 · Cited by 182 · see citing works
SDN-based real-time urban traffic analysis in VANET environment
Bhatia, J., Dave, R., Bhayani, H., Tanwar, S., & Nayyar, A. (2019) · Computer Communications · doi:10.1016/j.comcom.2019.10.011 · Cited by 169 · see citing works
SD-IoV: SDN enabled routing for internet of vehicles in road-aware approach
Abbas, M. T., Afaq, M., & Song, W. (2019) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-019-01319-w · Cited by 110 · see citing works
Toward Reliable and Scalable Internet of Vehicles: Performance Analysis and Resource Management
Ni, Y., Cai, L., He, J., Vinel, A. V., Li, Y., Mosavat-Jahromi, H., & Pan, J. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2950349 · Cited by 100 · see citing works
Blockchain-based distributed software-defined vehicular networks: a dueling deep q-learning approach
Zhang, D., Yu, F. R., & Yang, R. (2019) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2019.2944399 · Cited by 96 · see citing works
Wang, X., Ning, Z., Hu, X., Wang, L., Hu, B., Cheng, J. S., & Leung, V. C. M. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2886010 · Cited by 93 · see citing works
Multi-objective computation offloading for Internet of Vehicles in cloud-edge computing
Xu, X., Gu, R., Dai, F., Qi, L., & Wan, S. (2019) · Wireless Networks · doi:10.1007/s11276-019-02127-y · Cited by 93 · see citing works
Kong, F., Li, J., Jiang, B., & Song, H. H. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.10.052 · Cited by 84 · see citing works
Heterogeneous Information Network-Based Content Caching in the Internet of Vehicles
Zhang⋆, Y., Wang, R., Hossain, M. S., Alhamid, M. F., & Guizani, M. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2936792 · Cited by 84 · see citing works
Maximizing the Utilization of Fog Computing in Internet of Vehicle Using SDN
Kadhim, A. J., & Seno, S. A. H. (2018) · IEEE Communications Letters · doi:10.1109/lcomm.2018.2878710 · Cited by 66 · see citing works
Content accessibility preference approach for improving service optimality in internet of vehicles
Tolba, A. K. R. (2019) · Computer Networks · doi:10.1016/j.comnet.2019.01.038 · Cited by 51 · see citing works
Congestion avoidance through fog computing in internet of vehicles
Yaqoob, S., Ullah, A., Akbar, M., Imran, M. A., & Shoaib, M. (2019) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-019-01253-x · Cited by 49 · see citing works
Noorani, N., & Seno, S. A. H. (2020) · Peer-to-Peer Networking and Applications · doi:10.1007/s12083-019-00859-4 · Cited by 40 · see citing works
Qafzezi, E., Bylykbashi, K., Ikeda, M., Matsuo, K., & Barolli, L. (2020) · Internet of Things · doi:10.1016/j.iot.2020.100169 · Cited by 40 · see citing works
Internet of Things, big data and the economics of networked vehicles
Knieps, G. (2018) · Telecommunications Policy · doi:10.1016/j.telpol.2018.09.002 · Cited by 34 · see citing works
Edge-MapReduce-Based Intelligent Information-Centric IoV: Cognitive Route Planning
Zhao, C., Dong, M., Ota, K., Li, J., & Wu, J. (2019) · IEEE Access · doi:10.1109/access.2019.2911343 · Cited by 30 · see citing works
Cognitive Internet of Vehicles: Motivation, Layered Architecture and Security Issues
Hasan, K. F., Kaur, T., Hasan, M. M., & Feng, Y. (2019) · International Conference on Sustainable Technologies for Industry 5.0 (STI) · doi:10.1109/sti47673.2019.9068070 · Cited by 28 · see citing works
Huang, C., Lin, T.-H., & Tseng, K.-C. (2019) · IEEE Access · doi:10.1109/access.2019.2936456 · Cited by 20 · see citing works
GAS: A group acknowledgment strategy for popular content distribution in Internet of vehicle
Chen, C., Xiao, T., Zhao, H., Liu, L., & Pei, Q. (2019) · Vehicular Communications · doi:10.1016/j.vehcom.2019.04.001 · Cited by 9 · see citing works
Intelligent augmented keyword search on spatial entities in real-life internet of vehicles
Li, Y., Wang, M., Zhu, R., Anjum, A., Du, X., Feng, Y., Luo, C., & Tian, S. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.12.051 · Cited by 8 · see citing works
Toward an Efficient Deployment of Open Source Software in the Internet of Vehicles Field
Khelifi, A., Talib, M. W. A., Nouichi, D., & El-Tawil, M. (2019) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-019-03870-2 · Cited by 7 · see citing works
Cognitive Internet of Vehicles: Motivation, Layered Architecture and Security IssuesPreprint
Hasan, K. F. (2019) · doi:10.31224/osf.io/agc43 · Cited by 7 · see citing works
Tizvar, R., & Abbaspour, M. (2020) · Wireless Personal Communications · doi:10.1007/s11277-020-07182-9 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
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Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy
Zhang, X., Li, J., Zhou, J., Zhang, S., Wang, J., Yuan, Y., Liu, J., & Li, J. (2025) · Automotive Innovation · doi:10.1007/s42154-024-00310-2 · Cited by 103 · see citing works
Vehicle Artificial Intelligence System Based on Intelligent Image Analysis and 5G Network
Liu, B., Han, C., Liu, X., & Li, W. (2021) · International Journal of Wireless Information Networks · doi:10.1007/s10776-021-00535-6 · Cited by 36 · see citing works
Blockchain-Based Car Networking Data Privacy Security Assessment Model
Wang, P., & Hemalatha, K. L. (2023) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-99-0880-6_86 · Cited by 26 · see citing works
Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey
Ravi, B., Varghese, B., Murturi, I., Donta, P. K., Dustdar, S., Dehury, C. K., & Srirama, S. N. (2023) · Computers · doi:10.3390/computers12080162 · Cited by 21 · see citing works
Ravi, B., Kumar, M. S., Hu, Y., Hassan, S., & Kumar, B. (2023) · International Journal of Network Management · doi:10.1002/nem.2224 · Cited by 18 · see citing works
Xin, Q., Alazab, M., Crespo, R. A. G., & Montenegro, C. (2022) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2022.102055 · Cited by 17 · see citing works
Ravi, B., Thangaraj, J., & Shandilya, S. K. (2021) · Physical Communication · doi:10.1016/j.phycom.2021.101498 · Cited by 15 · see citing works
Xu, Z. (2022) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.7262 · Cited by 9 · see citing works
SO-ITS: a secure offloading scheme for intelligent transportation systems in federated fog-cloud
Salami, Y. (2025) · Iran Journal of Computer Science · doi:10.1007/s42044-025-00318-9 · Cited by 7 · see citing works
Sustainable Energy Management in Intelligent Transportation
Gao, Y., Ren, T., Zhao, X., & Li, W. (2022) · Journal of Interconnection Networks · doi:10.1142/s0219265921460099 · Cited by 7 · see citing works
Ai, Z., Zhang, M., Zhang, W., Kang, J., Tong, L., & Duan, Y. (2023) · IET Communications · doi:10.1049/cmu2.12694 · Cited by 7 · see citing works
MEC‐Based Cooperative Multimedia Caching Mechanism for the Internet of Vehicles
Han, L., Li, S., Ao, C., Liu, Y., Liu, G., Zhang, Y., & Zhao, J. X. (2022) · Wireless Communications and Mobile Computing · doi:10.1155/2022/8777890 · Cited by 2 · see citing works
Blockchain-Enabled Edge Computing Techniques for Advanced Video Surveillance in Autonomous Vehicles
Quasim, M. T., & Nisa, K. U. (2025) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2025.061541 · Cited by 1 · see citing works
Integration of edge-enabled IoT in vehicular networks in smart cities
Kumari, J., Ankarboina, H., Sahoo, S. K., Mishra, S. K., Raju, M. R., & Mishra, S. K. (2026) · Elsevier eBooks · doi:10.1016/b978-0-44-327726-9.00015-0 · Cited by 1 · see citing works
Analysis on Vibroacoustic Fatigue Life of Empennage in a Hypersonic Vehicle
Hongxian, W., Ming, Z., & Nie, H. (2022) · Mathematical Problems in Engineering · doi:10.1155/2022/7027528 · Cited by 1 · see citing works
RETRACTED ARTICLE: Decentralized security framework for future IoT end-to-end connectivity
Xin, Q., Crespo, R. A. G., Montenegro, C., Díaz, V. G., & Alazab, M. (2022) · Annals of Operations Research · doi:10.1007/s10479-021-04380-x
Retracted
- Authors
- Manogaran, G., Saravanan, V., & Hsu, C.-H.
- Affiliations
- Asia University (TW)
- Toronto Metropolitan University (CA)
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2021-07
- Volume
- 22
- Issue
- 7
- Pages
- 4541-4549
- ISSN
- 1524-9050 (ISSN-L)
- 1558-0016
- OpenAlex
- W3180789870
- Cited by
- 16
- References
- 26
- Citations by year
- 2026: 1 · 2025: 3 · 2023: 4 · 2022: 6 · 2021: 2
- FWCI
- 0.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Intelligent Transportation Systems (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Keywords
- vehicular networks, roadside units, information sharing, linear vector quantization, data smoothing, data offloading, resource utilization, traffic density
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