Integration of IoT and edge cloud computing for smart microgrid energy management in VANET using machine learning

被引:12
作者
Arul, U. [1 ]
Gnanajeyaraman, R. [1 ]
Selvakumar, A. [1 ]
Ramesh, S. [1 ]
Manikandan, T. [1 ]
Michael, G. [1 ]
机构
[1] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Artificial Intelligence & Machine Learning, Chennai, Tamil Nadu, India
关键词
IoT; Edge cloud computing; Microgrid; Energy management; VANET;
D O I
10.1016/j.compeleceng.2023.108905
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
A significant subset of ubiquitous computing known as vehicular ad hoc networks (VANETs) serves as a foundational piece of technology for VANET applications. Blockchain technology can be used in microgrids to conduct safe point-to-point transactions between anonymous parties while also addressing needs for security. This research is o proposes novel method in IoT(internet of things) based edge cloud computing architecture with microgrid energy management of VANET. here the VANET communication is carried out based on IoT edge cloud computing module and the smart microgrid architecture is used for energy management in VANET. then each vehicle energy has been analysed using structural reinforcement variational encoder neural networks. experimental analysis is carried out in terms of energy efficiency, network lifetime, training accuracy, QoS, communication overhead. the proposed technique attained energy efficiency of 96%, network lifetime of 85%, training accuracy of 98%, QoS of 95%, communication overhead of 55%.
引用
收藏
页数:14
相关论文
共 20 条
[1]  
Arshed J.U., 2022, Research article GA-IRACE: genetic algorithm-based improved resource aware cost-efficient scheduler for cloud fog computing environment
[2]   GA-IRACE: Genetic Algorithm-Based Improved Resource Aware Cost-Efficient Scheduler for Cloud Fog Computing Environment [J].
Arshed, Jawad Usman ;
Ahmed, Masroor ;
Muhammad, Tufail ;
Afzal, Mehtab ;
Arif, Muhammad ;
Bazezew, Banchigize .
WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
[3]   A blockchain-based Fog-oriented lightweight framework for smart public vehicular transportation systems [J].
Baker, Thar ;
Asim, Muhammad ;
Samwini, Hezekiah ;
Shamim, Nauman ;
Alani, Mohammed M. ;
Buyya, Rajkumar .
COMPUTER NETWORKS, 2022, 203
[4]   A Multisignature-Based Secure and OBU-Friendly Emergency Reporting Scheme in VANET [J].
Chen, Xiaohu ;
Yang, Anjia ;
Tong, Yao ;
Weng, Jian ;
Weng, Jiasi ;
Li, Tao .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (22) :23130-23141
[5]   ICDRP-F-SDVN: An innovative cluster-based dual-phase routing protocol using fog computing and software-defined vehicular network [J].
Darabkh, Khalid A. ;
Alkhader, Bayan Z. ;
Khalifeh, Ala F. ;
Jubair, Fahed ;
Abdel-Majeed, Mohammad .
VEHICULAR COMMUNICATIONS, 2022, 34
[6]   Resource Provisioning for Mitigating Edge DDoS Attacks in MEC-Enabled SDVN [J].
Deng, Yuchuan ;
Jiang, Hao ;
Cai, Peijing ;
Wu, Tong ;
Zhou, Pan ;
Li, Beibei ;
Lu, Hao ;
Wu, Jing ;
Chen, Xin ;
Wang, Kehao .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (23) :24264-24280
[7]   A scalable blockchain-based scheme for traffic-related data sharing in VANETs [J].
Diallo, El-hacen ;
Dib, Omar ;
Al Agha, Khaldoun .
BLOCKCHAIN-RESEARCH AND APPLICATIONS, 2022, 3 (03)
[8]   A Fog Computing Model for VANET to Reduce Latency and Delay Using 5G Network in Smart City Transportation [J].
Farooqi, Abdul Majid ;
Alam, M. Afshar ;
Hassan, Syed Imtiyaz ;
Idrees, Sheikh Mohammad .
APPLIED SCIENCES-BASEL, 2022, 12 (04)
[9]   End-to-end network slicing in vehicular clouds using the MobFogSim simulator [J].
Goncalves, Diogo M. ;
Puliafito, Carlo ;
Mingozzi, Enzo ;
Bittencourt, Luiz F. ;
Madeira, Edmundo R. M. .
AD HOC NETWORKS, 2023, 141
[10]  
Hamad AH, 2023, Int J Electric Comput Eng, V13, P2270