Channel Access Optimization with Adaptive Congestion Pricing for Cognitive Vehicular Networks: An Evolutionary Game Approach

Tian, Daxin; Zhou, Jianshan; Wang, Yunpeng; Sheng, Zhengguo; Duan, Xuting; Leung, Victor C. M.

doi:10.1109/tmc.2019.2901471

Cited by 38 publications

(12 citation statements)

References 38 publications

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“…• Untrustworthy vehicles remove [129] • Cluster formation and optimization [130] • Optimal access or communication mode selection [131]- [133] • Spectrum allocation [134] √ √…”

Section: Essmentioning

confidence: 99%

Applications of Game Theory in Vehicular Networks: A Survey

Sun

Liu²,

Wang

et al. 2021

IEEE Commun. Surv. Tutorials

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In the Internet of Things (IoT) era, vehicles and other intelligent components in an intelligent transportation system (ITS) are connected, forming Vehicular Networks (VNs) that provide efficient and secure traffic and ubiquitous access to various applications. However, as the number of nodes in ITS increases, it is challenging to satisfy a varied and large number of service requests with different Quality of Service (QoS) and security requirements in highly dynamic VNs. Intelligent nodes in VNs can compete or cooperate for limited network resources to achieve either an individual or a group's objectives. Game Theory (GT), a theoretical framework designed for strategic interactions among rational decision-makers sharing scarce resources, can be used to model and analyze individual or group behaviors of communicating entities in VNs. This paper primarily surveys the recent developments of GT in solving various challenges of VNs. This survey starts with an introduction to the background of VNs. A review of GT models studied in the VNs is then introduced, including its basic concepts, classifications, and applicable vehicular issues. After discussing the requirements of VNs and the motivation of using GT, a comprehensive literature review on GT applications in dealing with the challenges of current VNs is provided. Furthermore, recent contributions of GT to VNs integrating with diverse emerging 5G technologies are surveyed. Finally, the lessons learned are given, and several key research challenges and possible solutions for applying GT in VNs are outlined.

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“…• Untrustworthy vehicles remove [129] • Cluster formation and optimization [130] • Optimal access or communication mode selection [131]- [133] • Spectrum allocation [134] √ √…”

Section: Essmentioning

confidence: 99%

Applications of Game Theory in Vehicular Networks: A Survey

Sun

Liu²,

Wang

et al. 2021

IEEE Commun. Surv. Tutorials

Self Cite

View full text Add to dashboard Cite

show abstract

“…Further, the routing performance improvement in such a network can be optimized using a bio-inspired scheme (Tian et al [26]). This scheme is also known for its adaptive nature facilitating transmission over a dynamic environment of vehicular nodes.…”

Section: Adhoc-based Approachmentioning

confidence: 99%

Novel Hybrid Architecture of Infotainment for Streaming Signals in Vehicular Network

Reshma¹,

Prakash

Rafi

2021

Preprint

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Infotainment system is meant for offering integrated services of information and entertainment to the driver to offer a better driving experience. However, the infotainment system's present state is more towards entertainment and less towards accessing real-time information propagation for avoiding the occurrences of road fatalities. In this regard, the streaming of multimedia signals would increase communication to enhance driving experiences. The infotainment system is one integral part of vehicular communication for road safety; however, it has received less attention. Existing approaches towards data transmission among vehicles are studied concerning three standard architectures. A hybrid approach is far better than the infrastructure-based and ad-hoc-based approaches. Still, there are open-end loopholes towards hybrid architectures where reliability in the data dissemination process in the presence of dynamic topology of vehicular nodes is not considered. Therefore, the proposed study introduces a novel analytical model where the vehicles' streaming services can be offered by improvising the existing hybrid architecture. With a unique inclusion of link-quality-based attributes towards making a precise decision of the vehicles' mobility, the proposed system formulates error-free links among the communicating vehicles. The simulated study outcome shows that the proposed system offers better streaming performance than existing hybrid schemes.

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“…A cost-effective and efficient technology, i.e., Wireless Access in Vehicular Environments (WAVE) for VANETs was proposed in [17]. The WAVE technology is based on DSRC channels, and these channels are not sufficient, particularly when the number of vehicles increases, leading to network congestion [18], [19]. Therefore, alternate solutions for increasing the channel capacity in IoV need to be explored, and CR-based networks are among one such solutions.…”

Section: Related Workmentioning

confidence: 99%

“…Algorithm 1 Licensed Channel Allocation to Vehicles 1: procedure 2: RSU senses spectrum using energy detection and each node prdicts a list of free channels C based on Eq. (21) where a (S,C) is the assignment of channel m to user n. end if 19: end procedure If the total utilization of the network is represented by U(T ), then we can define channel allocation by the following optimization function:…”

Section: Channel Assignmentmentioning

confidence: 99%

A Secured and Efficient Communication Scheme for Decentralized Cognitive Radio-Based Internet of Vehicles

et al. 2019

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The advancements in hardware technologies have driven the evolution of vehicular ad hoc networks into the Internet of Vehicles (IoV). The IoV is a decentralized network of IoT-enabled vehicles capable of smooth traffic flow to perform fleet management and accident avoidance. The IoV has many commercial applications due to improved security and safety on the roads. However, the rapidly increasing number of wireless applications have challenged the existing spectrum bands allocated to IoV. The IoV has only six communication channels that are congested during the peak hours. The limited number of channels and the presence of congestion on these channels are the challenging issues that affect the safety of vehicles on the road. To mitigate the congestion, Cognitive Radio (CR) can be an optimal solution for the existing IoV Paradigm. In this paper, we propose a secured and efficient communication scheme for a decentralized CR-based IoV (CIoV) network. In this scheme, the Roadside Unit (RSU) senses the spectrum using an energy detection method. Each vehicle independently predicts the Primary User (PU) activity pattern using a hidden Markov model (HMM). Once a vehicle detects a licensed channel free from the PUs, it informs the RSU to store the channel in a database alongside the dedicated direct short-range communication (DSRC) channels for data transmission. The RSU and vehicles are registered with a trusted authority and they mutually authenticate each other. Upon mutual authentication, the RSU assigns communication channels to the vehicles on the road, based on their density. When the density of the vehicles is high, the detected licensed channels are used, otherwise, the DSRC channels are used. We evaluate the performance of CIoV in terms of packet delivery and packet loss ratio, end-to-end delay, and throughput, using NS-2. The simulation results show that the CR-based approach of CIoV outperforms the existing schemes and significantly enhances the performance of the underlying network.INDEX TERMS Authentication, trusted authority, internet of vehicles, channel detection and allocation, primary user activity, hidden markov model.

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Channel Access Optimization with Adaptive Congestion Pricing for Cognitive Vehicular Networks: An Evolutionary Game Approach

Cited by 38 publications

References 38 publications

Applications of Game Theory in Vehicular Networks: A Survey

Applications of Game Theory in Vehicular Networks: A Survey

Novel Hybrid Architecture of Infotainment for Streaming Signals in Vehicular Network

A Secured and Efficient Communication Scheme for Decentralized Cognitive Radio-Based Internet of Vehicles

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