Deep Learning Techniques to Improve Radio Resource Management in Vehicular Communication Network

Agarwal, Vartika; Sharma, Sachin

doi:10.1007/978-981-16-9012-9_14

Cited by 9 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Experimental result validate that it has 85% accuracy rate and are able to detect malicious modes within 200 seconds [29]. In 2022, Kim-Hung-Le present an intrusion detection software to protect vehicular communication from different kind of cyber attack such as wormhole, Backdoor etc [30].In 2022,vartika agarwal investigate about deep learning technique to improve RRM in VCN.They highlight various algorithm for resource allocation [31]. In 2022, Vartika Agarwal highlight multitype vehicle identification scheme from real time traffic database and offer subscription plan for its user [32].…”

Section: Literature Reviewmentioning

confidence: 86%

P2PCPM: Point to Point Critical Path Monitoring Based Denial of Service Attack Detection for Vehicular Communication Network Resource Management

Agarwal¹,

Sharma²

2022

IJCDS

View full text Add to dashboard Cite

Various types of security attacks are normal in vehicular communication networks. The current study uses a support vector machine to implement a Point to Point Critical Path Monitoring (P2PCPM) based Denial of Service (DOS) Attack detection technique for Vehicular Communication Network (VCN) resource management. Greatest quality of P2PCPM is that it eliminates attacked nodes from the network for the smooth process of vehicular communication. This scheme works well in terms of accuracy as well as attack detection rate. The whole simulation is made and tried by utilizing MATLAB Software. Simulation result shows 99% accuracy in case of security attack detection as well as reduced training and testing error upto 2%. Experimental results indicate that this scheme has a great efficiency and works well up to 1000 nodes, which is the limitation of current implementation. In future, simulation test may be done for unlimited nodes using similar or other techniques of attack detection.

show abstract

Section: Literature Reviewmentioning

confidence: 86%

P2PCPM: Point to Point Critical Path Monitoring Based Denial of Service Attack Detection for Vehicular Communication Network Resource Management

Agarwal¹,

Sharma²

2022

IJCDS

View full text Add to dashboard Cite

show abstract

“…In 2022, Vartika Agarwal highlight deep learning technique for radio resource management. They use various machine learning tools for resource allocation [13]. In 2022, Vartika Agarwal introduce scheme which is based on radio resource management.…”

Section: Literature Reviewmentioning

confidence: 99%

Resource Allocation Technique among Mobile Virtual VCN operators

Agarwal

Sharma

2023

Preprint

View full text Add to dashboard Cite

Resource allocation has been a guaranteed approach to provide users, spectrum from different network operators. In this research, we examine the use of Mobile virtual VCN operator (MVVO) to allow spectrum sharing. Specifically, we introduce a spectrum dividing framework between three VCN operators. We execute fairness by confirming that each VCN operators receive spectrum from another VCN operators for its user at reasonable charge. We formulate a Markov decision process to determine user scheduling between three VCN operators. Simulation result shows that virtual network operator takes 9 seconds for collecting information about user and network operator. Our numerical result validate that this scheme can achieve up to 90% improvement in terms of user satisfaction rate.

show abstract

Q Learning Algorithm for Network Resource Management in Vehicular Communication Network

Agarwal

Sharma

2022

Autonomous Vehicles Volume 2

View full text Add to dashboard Cite

Deep Learning Techniques to Improve Radio Resource Management in Vehicular Communication Network

Cited by 9 publications

References 15 publications

P2PCPM: Point to Point Critical Path Monitoring Based Denial of Service Attack Detection for Vehicular Communication Network Resource Management

P2PCPM: Point to Point Critical Path Monitoring Based Denial of Service Attack Detection for Vehicular Communication Network Resource Management

Resource Allocation Technique among Mobile Virtual VCN operators

Q Learning Algorithm for Network Resource Management in Vehicular Communication Network

Contact Info

Product

Resources

About