Riya Kakkar, Aparna Kumari, Rajesh Gupta, Smita Agrawal, S. Tanwar
{"title":"电动汽车安全最优充电站选择的人工神经网络与博弈论","authors":"Riya Kakkar, Aparna Kumari, Rajesh Gupta, Smita Agrawal, S. Tanwar","doi":"10.1109/INFOCOMWKSHPS57453.2023.10225788","DOIUrl":null,"url":null,"abstract":"The penetration of electric vehicles (EV s) entails the deployment of more charging station (CS) infrastructure to realize the charging requirement issues of the EV s. But, limited installation of charging infrastructure and data security issues require a secure and efficient CS selection mechanism for EV s. Towards this goal, we proposed an Artificial Intelligence (AI) and game theory-based secure CS selection scheme for EVs using blockchain. Blockchain and AI-based proposed scheme provides security and privacy during the communication between participants, i.e., EV s and CSs, for optimal CS selection. Moreover, an incorporated blockchain network with Interplanetary File System (IPFS) strengthens the reliability and cost-efficiency of CS selection by using beyond 5G network and its ultra-intelligent features. Furthermore, the blockchain and AI-based proposed scheme utilizes coalition game theory approach to recommend the optimal CS for EV and balance the fair payoff between the participants in the network. Finally, experimental results show that the proposed scheme yields better results than the conventional approaches considering the performance evaluation metrics such as State of Charge (SoC), profit analysis, and latency comparison.","PeriodicalId":354290,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Neural Network and Game Theory for Secure Optimal Charging Station Selection for EVs\",\"authors\":\"Riya Kakkar, Aparna Kumari, Rajesh Gupta, Smita Agrawal, S. Tanwar\",\"doi\":\"10.1109/INFOCOMWKSHPS57453.2023.10225788\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The penetration of electric vehicles (EV s) entails the deployment of more charging station (CS) infrastructure to realize the charging requirement issues of the EV s. But, limited installation of charging infrastructure and data security issues require a secure and efficient CS selection mechanism for EV s. Towards this goal, we proposed an Artificial Intelligence (AI) and game theory-based secure CS selection scheme for EVs using blockchain. Blockchain and AI-based proposed scheme provides security and privacy during the communication between participants, i.e., EV s and CSs, for optimal CS selection. Moreover, an incorporated blockchain network with Interplanetary File System (IPFS) strengthens the reliability and cost-efficiency of CS selection by using beyond 5G network and its ultra-intelligent features. Furthermore, the blockchain and AI-based proposed scheme utilizes coalition game theory approach to recommend the optimal CS for EV and balance the fair payoff between the participants in the network. Finally, experimental results show that the proposed scheme yields better results than the conventional approaches considering the performance evaluation metrics such as State of Charge (SoC), profit analysis, and latency comparison.\",\"PeriodicalId\":354290,\"journal\":{\"name\":\"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225788\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial Neural Network and Game Theory for Secure Optimal Charging Station Selection for EVs
The penetration of electric vehicles (EV s) entails the deployment of more charging station (CS) infrastructure to realize the charging requirement issues of the EV s. But, limited installation of charging infrastructure and data security issues require a secure and efficient CS selection mechanism for EV s. Towards this goal, we proposed an Artificial Intelligence (AI) and game theory-based secure CS selection scheme for EVs using blockchain. Blockchain and AI-based proposed scheme provides security and privacy during the communication between participants, i.e., EV s and CSs, for optimal CS selection. Moreover, an incorporated blockchain network with Interplanetary File System (IPFS) strengthens the reliability and cost-efficiency of CS selection by using beyond 5G network and its ultra-intelligent features. Furthermore, the blockchain and AI-based proposed scheme utilizes coalition game theory approach to recommend the optimal CS for EV and balance the fair payoff between the participants in the network. Finally, experimental results show that the proposed scheme yields better results than the conventional approaches considering the performance evaluation metrics such as State of Charge (SoC), profit analysis, and latency comparison.