Software-Defined Vehicular Networking

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 7538

Special Issue Editors


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Guest Editor
School of Computing, Faculty of Science & Engineering, Macquarie University, Sydney, NSW 2109, Australia
Interests: internet of things; internet of vehicles; trust management; cloud, fog, and edge computing; software-defined networking; next-generation wireless networks
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Special Issue Information

Dear Colleagues,

Over the past few years, considerable state-of-the-art advancements in the telecommunications and automotive sectors have empowered drivers with highly innovative communication and sensing capabilities, in turn paving the way for the next generation of Intelligent Transportation System (ITS) which is indispensable for an efficient deployment of futuristic connected and autonomous vehicles. Nevertheless, the safety of both vehicular passengers and vulnerable pedestrians in the context of ITS is of paramount importance. In this aspect, sharing of timely safety-critical information and a seamless connectivity with the traffic management entities is extremely imperative not only for the purpose of collision mitigation but also for necessary guidance pertinent to the current and anticipated trajectories and their corresponding speeds for ensuring an efficacious traffic flow. Therefore, a secure and low-latent communication architecture is essential to satisfy the stringent performance requirements of safety-critical vehicular applications.

Although conventional vehicular ad hoc networks can offer a diverse range of safety and non-safety (infotainment) services, nevertheless, they suffer from inherent shortcomings, including but not limited to lower bandwidths, higher end-to-end delays, and an unbalanced traffic flow. Additionally, modern-day connected vehicles are being equipped with hundreds of sensors onboard, which has transformed vehicles into an ambient sensing platform, i.e., data collection device, thereby paving the way for the connected cars of the future. It is further anticipated that an average connected vehicle would be able to generate more than 5 TB of data for each hour of its driving. Hence, (a) tackling such a flood of data so that the meaningful information could be processed and accordingly utilized for vehicular safety applications in an efficient manner, (b) selecting appropriate radio access technologies so that the said meaningful information could be transmitted with high data rates and low end-to-end delay, and (c) determining where to carry out all of this processing (i.e., compute and storage), since if sent to the backhaul would not only increase the network management overhead but would also compromise the service level objectives of the safety-critical vehicular applications, is extremely imperative.

To address the above stated challenges, the notion of software-defined networking (SDN) is being extensively deployed for wireless networks, and as of late, the same has been investigated for vehicular networks by a number of researchers within academia and industry. This Special Issue, accordingly, welcomes original contributions to bring forth the state-of-the-art advancements in the subject landscape. Thus, both high-quality surveys and technical contributions are welcome for this Special Issue.

Topics include but are not limited to:

  • Architectures for software-defined vehicular networks (SDVNs);
  • Software-defined heterogeneous vehicular networks (SDHVNETs);
  • Security aspects of software-defined vehicular networks;
  • Dynamic controller placement strategies in software-defined vehicular networks;
  • Machine learning/deep learning strategies for software-defined vehicular networks;
  • Energy-efficient software-defined vehicular networks;
  • Low latency in software-defined vehicular networks;
  • Integration of SDN and vehicular cloud computing;
  • Caching strategies in (5G-enabled) software-defined vehicular networks;
  • Integration of SDN and ICN for vehicular networks;
  • Crowd Collaborations for software-defined vehicular networks.

Prof. Dr. Michael Sheng
Dr. Adnan Mahmood
Guest Editors

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Keywords

  • Software-defined networks
  • Vehicular ad hoc networks
  • Internet of vehicles
  • Network security
  • Resource and mobility management
  • Tactile Internet

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Published Papers (2 papers)

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Research

21 pages, 2684 KiB  
Article
Towards Strengthening the Resilience of IoV Networks—A Trust Management Perspective
by Yingxun Wang, Hushairi Zen, Mohamad Faizrizwan Mohd Sabri, Xiang Wang and Lee Chin Kho
Future Internet 2022, 14(7), 202; https://doi.org/10.3390/fi14070202 - 30 Jun 2022
Cited by 7 | Viewed by 3006
Abstract
Over the past decade or so, considerable and rapid advancements in the state of the art within the promising paradigms of the Internet of Things (IoT) and Artificial Intelligence (AI) have accelerated the development of conventional Vehicular Ad Hoc Networks (VANETS) into the [...] Read more.
Over the past decade or so, considerable and rapid advancements in the state of the art within the promising paradigms of the Internet of Things (IoT) and Artificial Intelligence (AI) have accelerated the development of conventional Vehicular Ad Hoc Networks (VANETS) into the Internet of Vehicles (IoV), thereby bringing both connected and autonomous driving much closer to realization. IoV is a new concept in the Intelligent Traffic System (ITS) and an extended application of IoV in intelligent transportation. It enhances the existing capabilities of mobile ad hoc networks by integrating them with IoT so as to build an integrated and unified vehicle-to-vehicle network. It is worth mentioning that academic and industrial researchers are paying increasing attention to the concept of trust. Reliable trust models and accurate trust assessments are anticipated to improve the security of the IoV. This paper, therefore, focuses on the existing trustworthiness management models along with their corresponding trust parameters, as well as the corresponding trust evaluation parameters and simulation, which provide the basis for intelligent and efficient model suggestions and optimal parameter integration. In addition, this paper also puts forward some open research directions that need to be seriously solved before trust can play its due role in enhancing IoV network elasticity. Full article
(This article belongs to the Special Issue Software-Defined Vehicular Networking)
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24 pages, 823 KiB  
Article
Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles
by Rhodney Simões, Kelvin Dias and Ricardo Martins
Future Internet 2021, 13(11), 270; https://doi.org/10.3390/fi13110270 - 26 Oct 2021
Cited by 3 | Viewed by 2851
Abstract
The expected huge amount of connected cars and applications with varying Quality of Service (QoS) demands still depend on agile/flexible networking infrastructure to deal with dynamic service requests to the control plane, which may become a bottleneck for 5G and Beyond Software-Defined Network [...] Read more.
The expected huge amount of connected cars and applications with varying Quality of Service (QoS) demands still depend on agile/flexible networking infrastructure to deal with dynamic service requests to the control plane, which may become a bottleneck for 5G and Beyond Software-Defined Network (SDN) based Internet of Vehicles (IoV). At the heart of this issue is the need for an architecture and optimization mechanisms that benefit from cutting edge technologies while granting latency bounds in order to control and manage the dynamic nature of IoV. To this end, this article proposes an autonomic software-defined vehicular architecture grounded on the synergy of Multi-access Edge Computing (MEC) and Network Functions Virtualization (NFV) along with a heuristic approach and an exact model based on linear programming to efficiently optimize the dynamic resource allocation of SDN controllers, ensuring load balancing between controllers and employing reserve resources for tolerance in case of demand variation. The analyses carried out in this article consider: (a) to avoid waste of limited MEC resources, (b) to devise load balancing among controllers, (c) management complexity, and (d) to support scalability in dense IoV scenarios. The results show that the heuristic efficiently manages the environment even in highly dynamic and dense scenarios. Full article
(This article belongs to the Special Issue Software-Defined Vehicular Networking)
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