The advancement of the Internet of Vehicles (IoV) necessitates secure, scalable, and energy-eficient networking solutions to support seamless, real-time data exchange among connected vehicles. This paper introduces a tailored hybrid consensus mechanism, Delegated and Authorized Proof of Stake (DPA-PoS), which addresses these needs by combining Delegated Proof of Stake (DPoS) with Proof of Authority (PoA). Enhanced with advanced cryptographic techniques such as Zero-Knowledge Proofs (ZKP) and homomorphic encryption, DPA-PoS ofers significant improvements in security, privacy, and eficiency. By minimizing latency and lowering energy demands, this approach proves well-suited for critical IoV applications like autonomous vehicle coordination and secure inter-vehicle communication. Performance tests demonstrate that DPA-PoS surpasses traditional consensus protocols (PoW, PoS) in eficiency metrics, including reduced latency, faster transaction processing, and improved energy savings, highlighting its potential as a foundational solution for next-generation IoV systems.
The Internet of Vehicles (IoV) represents a transformative advancement in connected transportation,
establishing a sophisticated network system where vehicles can communicate seamlessly with each
other (V2V), with surrounding infrastructure like trafic signals and sensors (V2I), and with various
other entities such as pedestrians and smart devices (V2X) [
In recent years, IoV has shown significant potential to improve road safety by facilitating
realtime alerts about hazards and trafic conditions, thereby enabling drivers and autonomous vehicles
to make informed, split-second decisions [
To achieve its full potential, IoV must address several objectives related to data security,
communication eficiency, and interoperability [
This paper addresses these challenges by proposing a hybrid consensus mechanism, Delegated and Authorized Proof of Stake (DPA-PoS). The mechanism combines the scalability and low latency of Delegated Proof of Stake (DPoS) with the energy eficiency and security of Proof of Authority (PoA). Enhanced with advanced cryptographic techniques such as Zero-Knowledge Proofs (ZKP) and homomorphic encryption, DPA-PoS ensures robust data security and operational eficiency, making it suitable for real-time IoV applications. By leveraging these features, DPA-PoS ofers improvements in critical metrics such as transaction latency, throughput, energy consumption, and data integrity, addressing key gaps in existing IoV solutions.
The rest of the paper is structured as follows: Section 2 reviews related work and highlights limitations of existing blockchain-based solutions for IoV. Section 3 analyzes key challenges in IoV systems related to safety and eficiency. Section 4 provides an overview of traditional consensus mechanisms and their limitations. Section 5 introduces the DPA-PoS mechanism and its theoretical framework. Section 6 presents case studies and simulation results, comparing DPA-PoS with other mechanisms. Section 7 discusses implementation challenges and future perspectives. Section 8 addresses limitations of the proposed mechanism and suggests directions for future research. Finally, Section 9 concludes by summarizing the contributions and emphasizing the potential of DPA-PoS to transform IoV systems.
This class depends on the following packages for its proper functioning:
The Internet of Vehicles (IoV) has garnered significant attention as an advanced communication network between vehicles, road infrastructure, and surrounding entities. In [9], As B. Ji et al. (2020) define, IoV is fundamentally a dynamic network designed to enhance road safety, improve trafic eficiency, and optimize user experience by enabling real-time data exchanges. Early studies, such as those by Siuhi and Mwakalonge (2016), focused on the initial applications of IoV, highlighting its transformative potential in intelligent transport systems (ITS) and autonomous vehicle networks, where real-time data transfer is critical for safe and eficient operations [10].
Research has since expanded to explore the diverse applications and benefits of IoV.
GuerreroIbáñez, Zeadally, and Contreras-Castillo (2018) discuss how IoV supports practical applications, such as
intelligent transport systems, shared mobility services, and commercial logistics. They emphasize that
IoV improves road safety and trafic management while also contributing to environmental sustainability
by reducing greenhouse gas emissions[11]. Similarly, Hamid, Zamzuri, and Limbu (2019) underscore
the essential role of IoV in autonomous vehicles, where real-time communication enables
decisionmaking and safe navigation, highlighting IoV’s critical function in supporting the future of automated
transportation[
However, as IoV has advanced, researchers have identified several challenges that must be addressed to fully realize its potential. Lu et al. (2014) outline key issues, including data security, user privacy, communication eficiency, and the interoperability of diferent systems and devices[ 12]. These challenges underscore the need for robust and secure communication protocols to ensure that IoV networks can function efectively. Qiu et al. (2018) further elaborate on these vulnerabilities, especially focusing on weaknesses in existing communication protocols that could expose IoV networks to security threats[13]. The insights from these studies demonstrate the necessity of developing enhanced security measures to protect IoV systems against cyber threats.
In recent years, blockchain technology has emerged as a promising solution for addressing security and eficiency challenges in IoV. Several researchers have explored its integration with IoV to enhance security, data integrity, and operational eficiency. For example, Arushi Aroraa and Sumit Kumar Yadav (2018) propose a blockchain-based security mechanism for IoV, emphasizing how blockchain’s decentralized architecture can improve authentication and data transfer security across the IoV network[14]. Their work also introduces smart contracts to automate connected car services, boosting system eficiency. In a similar vein, the authors of “Security Mechanism for Vehicle Identification and Transaction Authentication in the Internet of Vehicles (IoV) Scenario” discuss a blockchain model that employs publickey cryptography and secure transaction protocols to protect sensitive data and maintain confidentiality within the IoV network, highlighting critical aspects of secure identity management [15].
Further developments in blockchain-enabled IoV networks focus on optimizing communication and reducing computational demands. The authors of “Blockchain-Based Internet of Vehicles (IoV) Information Transmission Mechanisms” propose using blockchain functionalities, such as distributed registries and smart contracts, to authenticate data transmissions securely [16]. Their approach prioritizes essential messages and minimizes required authentications, thereby enhancing eficiency and reducing computational costs. [17] add to this line of research by presenting an optimized method for vehicle authentication using Proof of Authority (PoA). Their method enhances privacy and reduces the time required for vehicle authentication, which is especially beneficial in high-trafic IoV scenarios [ 17].
A more recent study, “Enhancing Security using Trusted Blockchain Method for Internet of Vehicles,” expands on these concepts by suggesting a distributed access control system within blockchain-enabled IoV. This method allows vehicles to participate in secure, scalable applications that support decentralized decision-making, demonstrating blockchain’s potential to enhance transparency and data security across IoV networks. Such applications illustrate how blockchain can foster a secure and trusted IoV environment [18].
Despite the progress made in integrating blockchain with IoV, a gap remains in the development of a specific hybrid consensus mechanism tailored to IoV’s unique requirements [ 19]. Our proposed Delegated and Authorized Proof of Stake (DPA-PoS) seeks to address this gap by combining the benefits of Delegated Proof of Stake (DPoS) and Proof of Authority (PoA) mechanisms. By incorporating advanced technologies like Zero-Knowledge Proofs (ZKP) and homomorphic encryption, DPA-PoS enhances IoV security, scalability, and eficiency, providing a robust solution for secure data exchange and reliable communications in connected vehicle networks.
This related work highlights the growing interest in leveraging blockchain to overcome IoV’s security and eficiency challenges, and DPA-PoS stands as a distinct contribution in advancing these eforts, ofering a comprehensive, hybrid approach that aligns with the IoV network’s complex needs. These studies highlight the need for a tailored consensus mechanism that can enhance scalability, security, and eficiency in IoV systems. The proposed DPA-PoS aims to bridge this gap.
The Internet of Vehicles (IoV) faces critical challenges in both security and eficiency that must be addressed to achieve safe and efective network operations.
IoV networks are vulnerable to cyber threats like DDoS attacks, data interception, and intrusions due to weak communication protocols and interoperability issues. Ensuring data confidentiality is crucial to maintain user privacy, requiring data anonymization, encryption, and adherence to regulations such as GDPR[20]. Addressing security vulnerabilities is crucial to ensure trust and reliability in IoV systems, which also impacts overall eficiency, as discussed next. 3.2. Eficiency Challenges • Data Management: The vast amount of data generated in IoV demands eficient storage, synchronization, and real-time processing to enable accurate and timely decision-making.[21] • Latency: Low latency is essential for safety-critical applications, making high-speed networks like 5G critical for rapid data transmission.[22] • Scalability: IoV systems must handle increasing numbers of connected devices and data volumes without losing performance, requiring robust resource management and adaptability.[23] • By addressing these challenges, IoV can meet the demands of secure, eficient, and scalable modern transportation systems.
These challenges necessitate innovative solutions, such as a robust consensus mechanism, which we explore in the following section.
Current blockchain mechanisms each ofer distinct advantages and drawbacks for IoV: • Proof of Work (PoW): Secure but energy-intensive and slow, making it unsuitable for real-time
IoV needs.[24] • Proof of Stake (PoS): More energy-eficient but prone to centralization and security challenges.[ 25] • Delegated Proof of Stake (DPoS): Improves scalability and latency but risks centralization among elected delegates.[26] • Proof of Authority (PoA): Fast and energy-eficient, yet may compromise security and decentralization due to reliance on a few trusted nodes.[27]
These limitations highlight the need for a tailored, hybrid consensus mechanism to meet IoV’s specific requirements for low latency, security, and scalability.
While these mechanisms ofer distinct advantages, none fully address the unique requirements of IoV systems, such as real-time performance and scalability. This gap motivates the development of the proposed DPA-PoS mechanism.
The proposed Delegated and Authorized Proof of Stake (DPA-PoS) mechanism addresses the unique challenges of the Internet of Vehicles (IoV), focusing on enhancing scalability, security, and energy eficiency. By integrating the scalability and low latency of Delegated Proof of Stake (DPoS) with the energy-eficient and secure characteristics of Proof of Authority (PoA), DPA-PoS provides a tailored consensus mechanism for real-time, secure IoV applications.
The DPA-PoS mechanism operates through the following steps: 1. Delegate and Validator Selection: 2. Block Proposal and Validation: 3. Consensus Formation: • IoV participants, such as connected vehicles and roadside units (RSUs), vote for delegates based on their reputation and stake [28]. • Validators are randomly selected from the pool of delegates to ensure fairness and mitigate risks of centralization [29]. • Delegates propose blocks containing transaction or communication data within the IoV network [30]. • Validators authenticate blocks using Zero-Knowledge Proofs (ZKP) to maintain data privacy without revealing sensitive details. • Validators evaluate the block and reach a consensus based on a predefined threshold, ensuring the inclusion of validated transactions in the blockchain.
• If the block is invalid, it is rejected and re-proposed by another delegate. 4. Dynamic Security and Role Rotation: 5. Energy-Eficient Operations: • To prevent centralization and improve resilience, the roles of delegates and validators are rotated periodically. • Continuous network monitoring and cryptographic protocols (e.g., homomorphic encryption) protect against threats such as Sybil attacks and Distributed Denial of Service (DDoS) attacks. • By limiting computational tasks to a small number of trusted nodes, DPA-PoS achieves significantly reduced energy consumption while maintaining high transaction throughput and low latency. • Continuous network monitoring and cryptographic protocols (e.g., homomorphic encryption) protect against threats such as Sybil attacks and Distributed Denial of Service (DDoS) attacks.
DPA-PoS is particularly suited for critical IoV applications, including:
• RSUs act as delegates to validate and synchronize trafic data, enabling dynamic control of trafic flow and congestion reduction. • Low-latency operations ensure real-time updates to trafic lights and navigation systems. • ToAutonomous vehicles communicate securely using encrypted messages validated through
DPA-PoS. • The mechanism supports reliable decision-making for tasks such as collision avoidance, lane changes, and platooning.
• DPA-PoS enables secure, low-latency financial transactions between electric vehicles and charging stations. • Cryptographic techniques such as ZKP and homomorphic encryption ensure transaction confidentiality and integrity.
Below is a high-level flowchart illustrating the operational steps of DPA-PoS for IoV systems:
The DPA-PoS mechanism demonstrates significant advantages over traditional consensus methods: 1. Scalability: Supports up to 2000 transactions per second (TPS), outperforming Proof of Work (PoW) and Proof of Stake (PoS) systems [30]. 2. Energy Eficiency: Consumes only 0.5 J per transaction, significantly less than PoW and comparable to PoA [30]. 3. Security: Combines ZKP and homomorphic encryption to ensure data integrity, confidentiality, and robustness against cyberattacks [30]. 4. eal-Time Communication: Achieves sub-second transaction latency, enabling real-time operations essential for IoV applications such as trafic management and autonomous vehicle coordination [30].
By addressing these critical needs, DPA-PoS ofers a robust solution for secure, scalable, and eficient IoV systems, bridging gaps in current blockchain-based consensus mechanisms and paving the way for enhanced connected mobility.
To address the computational demands of advanced cryptographic methods in the DPA-PoS mechanism, we assess the impact of Zero-Knowledge Proofs (ZKP) and homomorphic encryption. While ZKP enhances data privacy by enabling verification without exposing details, it introduces latency as transaction volume increases. Homomorphic encryption allows encrypted data processing but requires considerable computational resources, which can impact throughput in high-trafic IoV environments. These trade-ofs are considered in our performance simulations.
Our simulations evaluate DPA-PoS for performance, safety, and energy eficiency across test scenarios in dense urban areas and for electric vehicle payments. Using trafic and network simulators (SUMO and NS-3) alongside blockchain performance tools (Hyperledger Caliper), we measure latency, throughput, energy consumption, and security.
The validation results, presented in the next section, highlight the performance of DPA-PoS in terms of latency, throughput, and energy eficiency.
Simulation of Urban Mobility (SUMO) and Network Simulator 3 (NS-3) to replicate realistic IoV conditions. SUMO was employed to model trafic dynamics in a virtual urban environment, simulating vehicle mobility, trafic density, and road conditions. The simulation involved creating a city layout with intersections, trafic lights, and diverse road types, where vehicles followed predefined routes over a simulation period of 3600 seconds. With a total of 1000 vehicles moving at an average speed of 40 km/h, SUMO generated mobility traces representing real-time vehicle positions, which were later integrated into the network simulation.
NS-3 was then utilized to simulate communication among vehicles and infrastructure, incorporating the mobility traces from SUMO to ensure accurate vehicle movements. The IEEE 802.11p standard, designed for vehicular ad hoc networks (VANETs), was used to model data exchanges. The network setup included a communication range of 300 meters, a channel bandwidth of 10 MHz, a packet size of 512 bytes, and a transmission interval of 100 milliseconds. Metrics such as latency, throughput, packet delivery ratio, and energy consumption were measured to evaluate the performance of the communication network under real-world IoV scenarios.
The simulation parameters used in this study are summarized in the following table:
The DPA-PoS mechanism was integrated into the simulation to handle transaction validation and block generation. Testing scenarios included high-density urban trafic, electric vehicle charging station payments, and emergency vehicle prioritization. Key performance indicators such as average transaction latency, throughput in transactions per second (TPS), energy consumed per transaction, system scalability under increasing loads, and security resilience against cyberattacks were analyzed to assess the efectiveness of the mechanism.
By combining SUMO and NS-3, the validation process provided a comprehensive framework to test DPA-PoS in realistic IoV settings, demonstrating its relevance and efectiveness in addressing the challenges of real-time communication, energy eficiency, and network scalability. This integration ensured an accurate evaluation of the proposed mechanism’s performance and applicability in modern IoV systems.
The evaluation of the proposed DPA-PoS mechanism demonstrated significant improvements across key metrics, including latency, throughput, energy eficiency, and security, making it a robust solution for real-time and scalable IoV applications. Table 2 summarizes the performance metrics and provides a comparative analysis with traditional consensus mechanisms such as Proof of Work (PoW), Proof of Stake (PoS), and Proof of Authority (PoA).
Performance Metrics. The DPA-PoS mechanism achieved a latency of less than 1 second, significantly outperforming PoW, which requires 50 seconds, and PoS, which averages 3.5 seconds. This ultra-low latency is essential for IoV systems that rely on real-time data exchanges, such as autonomous navigation and emergency response applications. Additionally, DPA-PoS demonstrated a throughput of 2000 transactions per second (TPS), far exceeding PoW (15–20 TPS), PoS (1250 TPS), and PoA (1500 TPS). This high throughput ensures the system can accommodate the increasing number of connected vehicles in modern IoV networks. In terms of energy eficiency, DPA-PoS consumed only 0.5 Joules per transaction, a dramatic improvement over PoW’s 3 Joules and comparable to PoA. This energy eficiency makes the mechanism sustainable, especially for battery-constrained devices like electric vehicles and roadside units. Furthermore, DPA-PoS exhibited strong security capabilities, achieving an attack failure rate of less than 0.01% and 99.9% confidentiality through advanced cryptographic techniques such as Zero-Knowledge Proofs (ZKP) and homomorphic encryption. These attributes ensure the integrity and privacy of sensitive data, safeguarding IoV systems against cyber threats such as Distributed Denial of Service (DDoS) and Sybil attacks.
Scalability was another key strength of DPA-PoS, which demonstrated the ability to handle an annual network growth rate of 25%, outperforming PoW (5%), PoS (15%), and PoA (20%). This scalability highlights the mechanism’s capacity to support the rapid expansion of IoV networks without performance degradation.
Practical Implications and Scenarios. These results highlight several practical implications for IoV systems. The low latency enables real-time decision-making in critical applications, such as autonomous vehicle coordination and dynamic trafic management. High throughput ensures the eficient handling of trafic surges in urban environments, preventing congestion and enabling smooth trafic flow. The energy eficiency of DPA-PoS supports sustainable operations, reducing the energy burden on IoV devices and contributing to the environmental goals of smart cities.
To illustrate the potential applications, consider a smart city trafic management system. During rush hours, DPA-PoS can dynamically adjust trafic signals and reroute vehicles to optimize trafic flow. In emergency response scenarios, such as an ambulance navigating heavy trafic, DPA-PoS enables seamless communication with trafic lights and nearby vehicles to create a clear path. In decentralized electric vehicle charging networks, DPA-PoS facilitates secure, low-latency payments while optimizing energy distribution to meet user demand eficiently.
The results underline the transformative potential of DPA-PoS for IoV systems, ofering a unique combination of low latency, high throughput, energy eficiency, and robust security. These characteristics make it well-suited for addressing the challenges of real-world IoV applications, paving the way for enhanced scalability, eficiency, and sustainability in connected transportation networks. Further exploration through real-world implementations could validate these findings and uncover additional use cases.
1. Latency Comparison Graph
The graph illustrates the average latency for transaction validation across diferent consensus mechanisms. The x-axis is labeled as "Consensus Mechanism" (e.g., DPA-PoS, PoW, PoS, PoA), while the y-axis is labeled as "Latency (seconds)." Consistent colors or patterns are used to represent each mechanism.
ifg 2. This graph compares the average transaction latency of various consensus mechanisms. DPAPoS achieves a latency of less than 1 second, significantly outperforming PoW (50 seconds) and PoS (3.5 seconds) while matching PoA. This low latency is crucial for real-time IoV applications such as collision avoidance and trafic management. 2. Throughput Comparison Graph This graph displays the throughput achieved by each consensus mechanism. The x-axis represents "Consensus Mechanism," and the y-axis represents "Throughput (TPS)." A legend is included to clarify the representation of each mechanism.
ifg 3. This graph highlights the throughput in transactions per second for diferent consensus mechanisms. DPA-PoS achieves the highest throughput at 2000 TPS, significantly exceeding PoW (15–20 TPS), PoS (1250 TPS), and PoA (1500 TPS). This high throughput ensures scalability in handling the increasing number of IoV transactions. 3. Energy Eficiency Comparison Graph The energy consumption graph uses a bar chart to highlight the eficiency diferences between consensus mechanisms. The x-axis is labeled "Consensus Mechanism," and the y-axis is labeled "Energy Consumption (Joules per transaction).
ifg 4. This graph shows the energy consumption per transaction for each consensus mechanism. DPA-PoS and PoA are the most energy-eficient, consuming only 0.5 Joules per transaction, while PoW is significantly less eficient, consuming 3 Joules. This energy eficiency supports sustainable IoV operations, especially for battery-constrained devices.
Resistance to Attacks: Simulations showed robustness against DDoS attacks and intrusions, thanks to the combination of PoS and PoA. Data Integrity: Transactions remained intact and unaltered, guaranteeing the integrity of communications. Privacy Protection: The use of ZKP and homomorphic encryption ensured the confidentiality of user data. Security Graph: The graph compares the attack resistance of diferent consensus mechanisms. The DPA-PoS mechanism demonstrates very high security, particularly due to the use of Zero-Knowledge Proofs (ZKP) and homomorphic encryption.
The DPA-PoS mechanism was evaluated for key metrics with quantitative estimates to enhance comparison:
Energy Consumption: DPA-PoS uses approximately 0.5 Joules per transaction, about 40% less energy than PoW and comparable to PoA.
Security: DPA-PoS demonstrated resilience, with an attack failure rate below 0.01% and enhanced data integrity, outperforming typical PoS systems by up to 30%.
Confidentiality: With Zero-Knowledge Proofs (ZKP) and homomorphic encryption, DPA-PoS achieves 99.9% confidentiality, a 20% improvement over PoS.
Scalability: DPA-PoS supports high transaction throughput (around 2,000 TPS) and can accommodate an annual network growth rate of 25%, significantly higher than PoW and PoS.
This quantitative approach provides a clearer, data-backed comparison of DPA-PoS with PoW, PoS, and PoA systems, emphasizing its benefits in energy eficiency, security, confidentiality, and scalability.
The following table provides a comparison of the proposed DPA-PoS mechanism with traditional consensus mechanisms in terms of key performance metric:
The results of case studies and simulations show that the DPA-PoS hybrid mechanism ofers a viable and improved solution for the specific needs of the Internet of Vehicles (IoV). It ofers superior performance, enhanced security, and optimal energy eficiency compared with traditional consensus mechanisms such as PoW, PoS, and PoA. By combining the strengths of Delegated Proof of Stake and Proof of Authority, and integrating advanced technologies such as Zero-Knowledge Proofs (ZKP) and homomorphic encryption, DPA-PoS can revolutionize the way connected vehicles interact and communicate, paving the way for safer, more eficient, and more sustainable mobility.
The DPA-PoS mechanism ofers significant potential to enhance scalability and security in smart city and IoV applications. In trafic management, it can dynamically coordinate real-time communication between vehicles and infrastructure, reducing congestion and improving safety in projects like Singapore’s intelligent trafic systems. For decentralized EV charging networks, as seen in cities like Amsterdam, DPA-PoS facilitates secure, real-time payments and supports scalability to meet growing demand.
Autonomous vehicle coordination, such as Detroit’s Mobility Innovation Corridor, benefits from DPAPoS’s low-latency and high-security communication, ensuring safe navigation and eficient platooning. During disasters, the mechanism enables rapid validation of evacuation routes, as seen in disaster-prone cities like Tokyo, ensuring reliable and secure coordination of emergency vehicles. In rural areas connected to smart city networks, DPA-PoS’s energy-eficient design supports long-term operation for IoV devices reliant on limited power sources.
These scenarios illustrate how DPA-PoS addresses IoV challenges, providing scalable, secure, and eficient solutions for modern transportation systems. Future pilot projects will further demonstrate its practicality and refine its capabilities for widespread adoption.
The implementation of DPA-PoS in IoV systems faces technical challenges, including interoperability, scalability, security, privacy, and achieving low latency for real-time applications. Operationally, high implementation costs, adoption hurdles, and regulatory compliance pose significant barriers. Addressing these requires collaboration among stakeholders, including manufacturers, governments, and service providers.
Future advancements in AI, 6G, and smart cities present opportunities to enhance DPA-PoS. AI can optimize resource allocation and transaction validation, while 6G’s ultra-low latency and high data rates will improve real-time performance. Pilot projects and collaborations will be essential to refine the mechanism and test its applicability in trafic management, EV charging, and autonomous vehicles. With continuous innovation and stakeholder cooperation, DPA-PoS can become a cornerstone for secure and scalable IoV systems in smart cities.
While DPA-PoS addresses several critical challenges, certain limitations persist, which are explored in the following section.
The proposed DPA-PoS mechanism, while showcasing significant improvements in scalability, security, and energy eficiency, faces several limitations that must be addressed to ensure its practical applicability in real-world IoV systems. One of the primary challenges lies in the integration costs associated with deploying the mechanism in existing vehicular communication infrastructures. These costs, which include the implementation of blockchain frameworks and hardware upgrades, may discourage adoption, particularly among smaller stakeholders with limited resources.
Another concern is the mechanism’s susceptibility to Sybil attacks, where malicious actors can create multiple fake identities to manipulate the consensus process. Although DPA-PoS combines the strengths of Delegated Proof of Stake (DPoS) and Proof of Authority (PoA), the reliance on node selection processes exposes it to this vulnerability. Addressing this issue is critical to maintaining the integrity and fairness of the network. Additionally, the scalability of DPA-PoS, while superior to traditional consensus mechanisms, can be challenged under high transaction volumes or peak trafic conditions. These bottlenecks may hinder real-time communication and decision-making in safety-critical IoV applications.
The computational overhead introduced by advanced cryptographic techniques, such as ZeroKnowledge Proofs (ZKP) and homomorphic encryption, also presents a limitation. While these techniques enhance security and privacy, they demand significant processing power, which could strain resource-constrained IoV devices like autonomous vehicles and roadside units. Reducing this overhead is essential to ensure the widespread adoption of the mechanism across diverse IoV environments.
To overcome these challenges, several solutions and future directions are proposed. Cost optimization can be achieved through collaborative funding models involving governments, automotive manufacturers, and IoV service providers. Additionally, using modular and open-source blockchain frameworks may reduce development costs and simplify integration. To enhance security against Sybil attacks, robust identity management systems based on decentralized identifiers (DIDs) can be implemented. Integrating machine learning algorithms to detect and prevent malicious behavior can further improve network integrity.
Improving scalability is a priority, and techniques such as sharding and sidechains can be introduced to distribute transaction loads across multiple chains. For example, transactions in high-density trafic areas can be processed on sidechains, leaving the main chain free for critical operations. Dynamic resource allocation mechanisms can also be employed to prioritize time-sensitive transactions during high-load conditions, ensuring real-time performance in critical IoV scenarios.
Leveraging artificial intelligence (AI) ofers another promising avenue for optimization. AI can be integrated with DPA-PoS to enhance resource allocation, predict potential bottlenecks, and streamline transaction validation processes. This integration can ensure consistent performance under varying network conditions while minimizing computational demands. Additionally, research into lightweight cryptographic protocols can address the challenges posed by the computational overhead of ZKP and homomorphic encryption, making DPA-PoS more suitable for devices with limited processing power.
Finally, real-world pilot projects in smart cities can validate the mechanism’s practicality and performance. Collaborations with automotive manufacturers, urban planners, and IoV service providers can provide empirical data to refine the mechanism and demonstrate its scalability and adaptability. These initiatives will be critical in translating the theoretical benefits of DPA-PoS into tangible improvements in connected transportation systems.
By addressing these limitations and exploring the proposed solutions, DPA-PoS can evolve into a comprehensive and adaptable technology for IoV systems. Future research should focus on integrating emerging technologies such as AI and IoT to further enhance its robustness and eficiency. Continuous innovation and collaboration among stakeholders will ensure that DPA-PoS meets the demands of secure, scalable, and energy-eficient IoV systems, paving the way for its adoption as a cornerstone of connected mobility.
The DPA-PoS mechanism demonstrates strong potential as a scalable, secure, and energy-eficient solution for IoV systems, addressing challenges in real-time communication, data privacy, and network resilience. By combining DPoS and PoA with advanced cryptographic techniques like ZKP and homomorphic encryption, it outperforms traditional mechanisms in latency, throughput, and energy eficiency, making it ideal for connected transportation networks.
Future research should validate DPA-PoS through pilot projects in trafic management, autonomous vehicle coordination, and EV charging networks, providing insights into practical deployment challenges. AI integration can further optimize resource allocation and transaction validation, while scalability enhancements via sharding and sidechains will support growing IoV networks. Eforts to improve cryptographic eficiency will ensure the mechanism’s suitability for resource-constrained devices. With these advancements, DPA-PoS can become a foundational technology for smart, connected mobility systems.
[8] A. K. Jain, S. R. Sahoo, J. Kaubiyal, Online social networks security and privacy: comprehensive review and analysis, Complex & Intelligent Systems 7 (2021) 2157–2177. [9] B. Ji, X. Zhang, S. Mumtaz, C. Han, C. Li, H. Wen, D. Wang, Survey on the internet of vehicles: Network architectures and applications, IEEE Communications Standards Magazine 4 (2020) 34–41. [10] S. Siuhi, J. Mwakalonge, Opportunities and challenges of smart mobile applications in transportation, Journal of trafic and transportation engineering (english edition) 3 (2016) 582–592. [11] J. Guerrero-Ibáñez, S. Zeadally, J. Contreras-Castillo, Sensor technologies for intelligent transportation systems, Sensors 18 (2018) 1212. [12] N. Lu, N. Cheng, N. Zhang, X. Shen, J. W. Mark, Connected vehicles: Solutions and challenges,
IEEE internet of things journal 1 (2014) 289–299. [13] T. Qiu, N. Chen, K. Li, M. Atiquzzaman, W. Zhao, How can heterogeneous internet of things build our future: A survey, IEEE Communications Surveys & Tutorials 20 (2018) 2011–2027. [14] A. Arora, S. Yadav, Block chain based security mechanism for internet of vehicles (IoV), 2018. [15] R. Loganathan, S. SelvakumaraSamy, Blockchain based internet of vehicles (iov) information transmission mechanisms, in: 2022 International Conference on Edge Computing and Applications (ICECAA), IEEE, 2022, pp. 514–523. [16] S. Khedkar, R. Mahajan, Optimized and eficient authentication in vanet using blockchain, SSRN (2022). Available at SSRN 4203801. [17] S. Khedkar, R. Mahajan, Optimized and eficient authentication in vanet using blockchain, Available at SSRN 4203801 (2022). [18] S. Yadav, K. Singh, S. Bezzateev, Enhancing security using trusted blockchain method for internet of vehicle, in: 2024 International Conference on Automation and Computation (AUTOCOM), IEEE, 2024, pp. 512–518. [19] B. Hildebrand, M. Baza, T. Salman, S. Tabassum, B. Konatham, F. Amsaad, A. Razaque, A comprehensive review on blockchains for internet of vehicles: Challenges and directions, Computer Science Review 48 (2023) 100547. [20] M. Mogadem, Y. Li, D. Meheretie, A survey on internet of energy security: related fields, challenges, threats and emerging technologies, Cluster Computing (2022) 1–37. [21] A. Sarkar, K. Daripa, M. Khan, A. Noorwali, Cloud enabled blockchain-based secured communication in mutual intelligent transportation using neural synchronization, Vehicular Communications 38 (2022) 100533. [22] L. Ang, K. Seng, G. Ijemaru, A. Zungeru, Deployment of iov for smart cities: Applications, architecture, and challenges, IEEE Access 7 (2018) 6473–6492. [23] M. Nasir, J. Arshad, M. Khan, M. Fatima, K. Salah, R. Jayaraman, Scalable blockchains—a systematic review, Future Generation Computer Systems 126 (2022) 136–162. [24] P. Alvares, L. Silva, N. Magaia, Blockchain-based solutions for uav-assisted connected vehicle networks in smart cities: a review, open issues, and future perspectives, Telecom 2 (2021) 108–140. [25] M. Saad, Z. Qin, K. Ren, D. Nyang, D. Mohaisen, e-pos: Making proof-of-stake decentralized and fair, IEEE Transactions on Parallel and Distributed Systems 32 (2021) 1961–1973. [26] J. Mišić, V. Mišić, X. Chang, Towards decentralization in dpos systems: election, voting and leader selection using virtual stake, IEEE Transactions on Network and Service Management (2023). [27] S. Fahim, S. Rahman, S. Mahmood, Blockchain: A comparative study of consensus algorithms pow, pos, poa, pov, International Journal of Mathematical Sciences and Computing 3 (2023) 46–57. [28] C. Pop, T. Cioara, I. Anghel, M. Antal, I. Salomie, Blockchain based decentralized applications:
Technology review and development guidelines, arXiv preprint (2020). arXiv:2003.07131. [29] F. Sami, Integration of blockchain and edge computing to improve the scalability and latency,
International Journal of Advanced Sciences and Computing 1 (2022) 27–36. [30] J. Lauinger, J. Ernstberger, E. Regnath, M. Hamad, S. Steinhorst, A-poa: Anonymous proof of authorization for decentralized identity management, in: 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), IEEE, 2021, pp. 1–9.