Survey of Interoperability Challenges in the Internet of Vehicles

Agbaje, Paul; Anjum, Afia; Mitra, Arkajyoti; Oseghale, Emmanuel; Bloom, Gedare; Olufowobi, Habeeb

doi:10.1109/tits.2022.3194413

Cited by 24 publications

(10 citation statements)

References 140 publications

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“…2024.3384272 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ to facilitate efficient data sharing, interoperability, functionality, scalability, and data security [38]. The APIs are adaptive to dynamic network conditions and can adjust data flow and resource allocation in real-time.…”

Section: A Integration Of Ai and Dtnmentioning

confidence: 99%

A Comprehensive Survey on Revolutionizing Connectivity Through Artificial Intelligence-Enabled Digital Twin Network in 6G

Sheraz,

Chuah,

Lee

et al. 2024

IEEE Access

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The deployment of 5G has exposed capacity constraints in realizing the key vision of the Internet of Everything (IoE). Therefore, the researchers are exploring potentials of Digital Twin Network (DTN) in wireless networks. DTN is a novel technology to create virtual replicas of physical environment for testing, optimizing, and managing wireless networks. The integration of Artificial Intelligence (AI) and DTN appears to be a promising approach to address communication systems by providing an efficient environment for testing and improving AI models before deployment in real networks for effective network management, optimal resource allocation, and precise behavior prediction. Therefore, AI-enabled DTN in 6G represents a compelling avenue to address multifaceted challenges faced by wireless networks. In this comprehensive work, we offer a holistic survey that delves into the state-of-the-art approaches for AIenabled DTNs in 6G. Firstly, we discuss the evolution of wireless networks and concept of AI-enabled DTN in 6G. Secondly, we discuss the role of AI-enabled DTN in 6G and driving advancements in fundamental components of 6G including resource allocation, caching, data offloading, and data security. Thirdly, we conduct a detailed discussion on key enabling technologies for realizing the capabilities of AI-enabled DTN in 6G. Fourthly, several applications of AI-enabled DTN in 6G are discussed for the practical relevance and significance in various industries such as smart cities, healthcare, and transportation etc. Finally, we provide lessons learned and highlight existing challenges and research directions to embark on further research efforts in the realm of AI-enabled DTN in 6G.INDEX TERMS Digital twin networks (DTNs), 6G, artificial intelligence (AI), caching, resource allocation, data offloading, security, enabling technologies, unmanned aerial vehicle (UAV), mmWave, THz.

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Section: A Integration Of Ai and Dtnmentioning

confidence: 99%

A Comprehensive Survey on Revolutionizing Connectivity Through Artificial Intelligence-Enabled Digital Twin Network in 6G

Sheraz,

Chuah,

Lee

et al. 2024

IEEE Access

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“…challenges [5]. The use of standardized frameworks is crucial for achieving true smart cities, and open standards are necessary for establishing an integrated ecosystem [6], [7].…”

Section: Introductionmentioning

confidence: 99%

“…Interoperability plays a vital role in the efficient functioning of ITMS by facilitating seamless information exchange and transmission between different traffic systems [5]. It enhances road safety, efficiency, collaboration between stakeholders, and the overall user experience.…”

Section: Introductionmentioning

confidence: 99%

Interoperability for intelligent traffic management systems in smart cities

Alanazi,

Alenezi

2024

IJECE

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Intelligent traffic management systems (ITMS) are essential for safe and livable smart cities. However, achieving seamless interoperability between diverse devices and services is challenging due to the lack of universal open standards. This study examines different types of interoperability (syntactic, semantic, network, middleware, and security) and their relationships with ITMS in the smart city context. By discussing requirements, challenges, and potential standards, this research provides a comprehensive understanding of interoperability issues in ITMS. It highlights the importance of standardization and collaboration among stakeholders, including policymakers, urban planners, and technology providers, to achieve interoperability. Addressing these challenges can optimize ITMS performance and contribute to smarter, sustainable cities. The study categorically examines challenges and potential standards, offering a framework for future research and practice. By advancing our understanding of ITMS interoperability, this research facilitates improved traffic management and smarter city development, enhancing urban residents’ quality of life. It makes a significant contribution to the field by emphasizing the critical role of interoperability in effective traffic management systems and the advancement of smart cities. By addressing interoperability challenges, we can create safer, more efficient, and sustainable transportation networks, fostering the development of livable cities.

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“…Autonomous vehicles (AVs) are nearing commercialization and are expected to become dominant among various emerging vehicles in the future [11], [12]. Wireless communication technologies, specifically vehicular communications such as Vehicle-to-Everything (V2X) [13], along with existing vehicle-sensing capabilities [14], provide support for enhanced safety applications, thereby enabling AVs for safer autonomous driving [15]. The important supporting technologies of artificial intelligence (AI) [16] and fifthgeneration (5G) networks [17], [18] in IoV technology are considered potential solutions for boosting vehicular critical safety applications [19].…”

Section: Introductionmentioning

confidence: 99%

Federated Learning Enabled SDN for Routing Emergency Safety Messages (ESMs) in IoV Under 5G Environment

Hussein,

Askar

2023

IEEE Access

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The emerging fifth-generation (5G) technology towards Internet of Vehicles (IoV) provides numerous advantages, such as lower levels of latency, stable link connections, and support for high mobility. However, avoiding vehicle collisions in IoV is a challenging task due to routing Emergency Safety Messages (ESMs) without strict delay and reliability requirements. To address this issue, we propose a novel intelligent Software-Defined Networking-based Collision Avoidance (SDNCA) framework assisted 5G. Primarily, SDNCA performs the first algorithm that accurately estimates the Risk Severity (RS) value for each vehicle via training the proposed Risk Severity-Artificial Neural Network (RS-ANN) model through the implementation of federated learning among vehicles. The SDNCA framework applies the second algorithm to achieve three main objectives. First, it calculates the Quality of Service (QoS) of the ESM based on RS, Vehicle Speed (VS), and Risk Distance (RD). Second, it dynamically allocates 5G network and computing resources (gNB nr i and gNB cr i ) for three Virtual Networks (VNs) based on QoS, RD, and VS. Third, it selects the best route (best gNB) for routing the ESMs from the Source Vehicle (SV) to the Destination Vehicle (DV). To ensure effective forwarding for each ESM, SDNCA deploys the third algorithm at the selected gNB to schedule the ESMs considering their priorities and configures the gNB nr i and gNB cr i based on the OpenFlow control message received from the SDN. The real-time simulation results demonstrate that the SDNCA framework achieves the ideal values of 17% Network Overhead (NO) and Computational Complexity (CC), a remarkable 0% Collision Rate (CR), 18 ms End-to-End (E2E) Delay, and 89%-90% Packet (ESM) Transmission Reliability (TR) compared with the existing related research.

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Survey of Interoperability Challenges in the Internet of Vehicles

Cited by 24 publications

References 140 publications

A Comprehensive Survey on Revolutionizing Connectivity Through Artificial Intelligence-Enabled Digital Twin Network in 6G

A Comprehensive Survey on Revolutionizing Connectivity Through Artificial Intelligence-Enabled Digital Twin Network in 6G

Interoperability for intelligent traffic management systems in smart cities

Federated Learning Enabled SDN for Routing Emergency Safety Messages (ESMs) in IoV Under 5G Environment

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