1 Optimizing the traffic flow in VANETs using deep quantum annealing
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J. Albert Mayan
Abstract
We have developed an optimization for the traffic flow in VANETs using deep quantum annealing. Deep quantum annealing is designed to maintain an optimal traffic flow without congestion in smart cities. Careful considerations are made to improve the flow in a manner that is better than the conventional methods. Simulation is carried out to test the efficacy of deep quantum annealing in VANETs. The results show that the proposed method achieves higher rate of accuracy in maintaining the traffic flow than expected.
Abstract
We have developed an optimization for the traffic flow in VANETs using deep quantum annealing. Deep quantum annealing is designed to maintain an optimal traffic flow without congestion in smart cities. Careful considerations are made to improve the flow in a manner that is better than the conventional methods. Simulation is carried out to test the efficacy of deep quantum annealing in VANETs. The results show that the proposed method achieves higher rate of accuracy in maintaining the traffic flow than expected.
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- Biographies XI
- List of contributors XIII
- 1 Optimizing the traffic flow in VANETs using deep quantum annealing 1
- 2 Quantum annealing-based routing in UAV network 13
- 3 Cyberbullying detection of social network tweets using quantum machine learning 25
- 4 AI-driven cybersecurity modeling using quantum computing for mitigation of attacks in IOT-SDN network 37
- 5 Machine learning-based quantum modeling to classify the traffic flow in smart cities 49
- 6 IoT attack detection using quantum deep learning in large-scale networks 67
- 7 Quantum transfer learning to detect passive attacks in SDN-IOT 79
- 8 Intrusion detection framework using quantum computing for mobile cloud computing 97
- 9 Fault-tolerant mechanism using intelligent quantum computing-based error reduction codes 109
- 10 Study of quantum computing for data analytics of predictive and prescriptive analytics models 121
- 11 A review of different techniques and challenges of quantum computing in various applications 147
- 12 Review and significance of cryptography and machine learning in quantum computing 159
- 13 An improved genetic quantum cryptography model for network communication 177
- 14 Code-based post-quantum cryptographic technique: digital signature 193
- 15 Post-quantum cryptography for the detection of injection attacks in small-scale networks 207
- 16 RSA security implementation in quantum computing for a higher resilience 219
- 17 Application of quantum computing for digital forensic investigation 231
- 18 Modern healthcare system: unveiling the possibility of quantum computing in medical and biomedical zones 249
- 19 Quantum computing-assisted machine learning to improve the prediction of cardiovascular disease in healthcare system 265
- 20 Mitigating the risk of quantum computing in cyber security era 283
- 21 IoMT-based data aggregation using quantum learning 301
- Index 319
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- Biographies XI
- List of contributors XIII
- 1 Optimizing the traffic flow in VANETs using deep quantum annealing 1
- 2 Quantum annealing-based routing in UAV network 13
- 3 Cyberbullying detection of social network tweets using quantum machine learning 25
- 4 AI-driven cybersecurity modeling using quantum computing for mitigation of attacks in IOT-SDN network 37
- 5 Machine learning-based quantum modeling to classify the traffic flow in smart cities 49
- 6 IoT attack detection using quantum deep learning in large-scale networks 67
- 7 Quantum transfer learning to detect passive attacks in SDN-IOT 79
- 8 Intrusion detection framework using quantum computing for mobile cloud computing 97
- 9 Fault-tolerant mechanism using intelligent quantum computing-based error reduction codes 109
- 10 Study of quantum computing for data analytics of predictive and prescriptive analytics models 121
- 11 A review of different techniques and challenges of quantum computing in various applications 147
- 12 Review and significance of cryptography and machine learning in quantum computing 159
- 13 An improved genetic quantum cryptography model for network communication 177
- 14 Code-based post-quantum cryptographic technique: digital signature 193
- 15 Post-quantum cryptography for the detection of injection attacks in small-scale networks 207
- 16 RSA security implementation in quantum computing for a higher resilience 219
- 17 Application of quantum computing for digital forensic investigation 231
- 18 Modern healthcare system: unveiling the possibility of quantum computing in medical and biomedical zones 249
- 19 Quantum computing-assisted machine learning to improve the prediction of cardiovascular disease in healthcare system 265
- 20 Mitigating the risk of quantum computing in cyber security era 283
- 21 IoMT-based data aggregation using quantum learning 301
- Index 319
