# A Novel Energy-Efficient Reservation System for Edge Computing in 6G Vehicular Ad Hoc Network
## 2 Related Works
The authors test their approach via simulations and experiments, concluding that it improves security and performance in vehicular communication systems within 6G networks compared to existing methods. The study presents a new access control and security approach for vehicular communication systems, addressing the specific challenges of 6G networks and offering a secure and efficient communication setting for intelligent vehicular transport in the future. An effective and reliable autonomous vehicle routing system for 6G networks with computational intelligence has been proposed in this article [11]. The protocol establishes a routing method that enhances energy optimization amongst IoT-based vehicles and ensures the ideal solution under challenging conditions [11]. The authentication scheme proposed in [12] is based on the combination of elliptic curve cryptography (ECC) and symmetric key encryption. The scheme uses both public key cryptography and symmetric key cryptography to authenticate messages transmitted between vehicles in a VANET. The scheme also employs a secure key management mechanism to generate and distribute keys among vehicles. It involves two models, a secure key management model and a message authentication model. The secure key management model [13] is responsible for generating and distributing the keys required for the message authentication model. On the other hand, the message authentication model is responsible for verifying the authenticity of the messages transmitted between vehicles. The proposed authentication scheme in [14] was tested using a simulator and the simulation results showed that the proposed scheme performed better than other authentication schemes concerning security, computational overhead, and communication overhead. The proposed scheme achieved a high level of security with a low computational overhead and low communication overhead, making it a suitable option for 6G-enabled VANETs. The research study in [15] includes several algorithms, including a key generation algorithm that is used to create the public and private keys necessary for the authentication process. The key distribution algorithm is used to securely distribute the keys among the vehicles in the VANET. The message authentication algorithm [16] is applied to authenticate the messages transmitted between the vehicles in the VANET. The key update algorithm is introduced to periodically update the keys to ensure the security of the VANET. The scheme is based on well-established cryptography techniques and employs a secure key management mechanism to guarantee the confidentiality and integrity of the messages exchanged between vehicles. The experimental results demonstrate that the proposed scheme outperforms other authentication schemes regarding security, computational overhead, and communication overhead. The research in [17] proposes an intelligent trust-based e-learning-based intrusion detection system (IDS) for vehicular ad hoc networks (VANETs) in 6G. The proposed IDS system is based on a hybrid model of machine learning and deep learning algorithms. The proposed IDS system comprises three models: a trust model, a feature extraction model, and a classification model. The trust model evaluates the trustworthiness of the vehicles in the network based on their behavior. The feature extraction model extracts features from the network data, and the classification model classifies the extracted features as normal or anomalous. The proposed system outperforms existing IDS systems [18] in terms of detection accuracy and the false alarm rate. Specifically, he proposed system achieves a high level of accuracy with a low false alarm rate, making it a suitable option for 6G-enabled VANETs. The proposed intelligent trust-based e-learning-based IDS system in [19] is also a promising solution for intrusion detection in 6G-enabled VANETs. The system is based on a hybrid model of machine learning and deep learning algorithms and comprises several algorithms for trust evaluation, feature extraction, and classification.