With recent advances made in Internet of Vehicles(IoV)and Cloud Computing(CC),the Intelligent Transportation Systems(ITS)find it advantageous in terms of improvement in quality and interactivity of urban transportatio...With recent advances made in Internet of Vehicles(IoV)and Cloud Computing(CC),the Intelligent Transportation Systems(ITS)find it advantageous in terms of improvement in quality and interactivity of urban transportation service,mitigation of costs incurred,reduction in resource utilization,and improvement in traffic management capabilities.Many trafficrelated problems in future smart cities can be sorted out with the incorporation of IoV in transportation.IoV communication enables the collection and distribution of real-time essential data regarding road network condition.In this scenario,energy-efficient and reliable intercommunication routes are essential among vehicular nodes in sustainable urban computing.With this motivation,the current research article presents a new Artificial Intelligence-based Energy Efficient Clustering with Routing(AI-EECR)Protocol for IoV in urban computing.The proposed AI-EECR protocol operates under three stages namely,network initialization,Cluster Head(CH)selection,and routing protocol.The presented AI-EECR protocol determines the CHs from vehicles with the help of Quantum Chemical Reaction Optimization(QCRO)algorithm.QCROalgorithmderives a fitness function with the help of vehicle speed,trust level,and energy level of the vehicle.In order to make appropriate routing decisions,a set of relay nodeswas selected usingGroup Teaching Optimization Algorithm(GTOA).The performance of the presented AI-EECR model,in terms of energy efficiency,was validated against different aspects and a brief comparative analysis was conducted.The experimental outcomes established that AI-EECR model outperformed the existing methods under different measures.展开更多
在一次能源的生产和消费中,清洁可再生能源因多重优势逐步得到青睐.然而,随着经济全球化的进程,对能源的需求也越来越大,新的能源供给矛盾也逐步凸显:能源时间和空间分布不均与能源需求点不匹配的矛盾.全球能源互联网的构建为解决该矛...在一次能源的生产和消费中,清洁可再生能源因多重优势逐步得到青睐.然而,随着经济全球化的进程,对能源的需求也越来越大,新的能源供给矛盾也逐步凸显:能源时间和空间分布不均与能源需求点不匹配的矛盾.全球能源互联网的构建为解决该矛盾提供了解决途径,城市能源互联网作为全球能源互联网的重要补充,对其进行研究具有非常重要的意义.从构建城市能源互联网(urban energy internet,UEI)的基本形态和系统模式出发,以全球能源互联网(energy internet,EI)相关性特征为落脚点,研究了UEI的分类、概念及典型网络结构特征、网架结构等,对UEI的建设具有一定的指导意义.展开更多
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(RGP 2/25/42),Received by Fahd N.Al-Wesabi.www.kku.edu.sa.This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program.
文摘With recent advances made in Internet of Vehicles(IoV)and Cloud Computing(CC),the Intelligent Transportation Systems(ITS)find it advantageous in terms of improvement in quality and interactivity of urban transportation service,mitigation of costs incurred,reduction in resource utilization,and improvement in traffic management capabilities.Many trafficrelated problems in future smart cities can be sorted out with the incorporation of IoV in transportation.IoV communication enables the collection and distribution of real-time essential data regarding road network condition.In this scenario,energy-efficient and reliable intercommunication routes are essential among vehicular nodes in sustainable urban computing.With this motivation,the current research article presents a new Artificial Intelligence-based Energy Efficient Clustering with Routing(AI-EECR)Protocol for IoV in urban computing.The proposed AI-EECR protocol operates under three stages namely,network initialization,Cluster Head(CH)selection,and routing protocol.The presented AI-EECR protocol determines the CHs from vehicles with the help of Quantum Chemical Reaction Optimization(QCRO)algorithm.QCROalgorithmderives a fitness function with the help of vehicle speed,trust level,and energy level of the vehicle.In order to make appropriate routing decisions,a set of relay nodeswas selected usingGroup Teaching Optimization Algorithm(GTOA).The performance of the presented AI-EECR model,in terms of energy efficiency,was validated against different aspects and a brief comparative analysis was conducted.The experimental outcomes established that AI-EECR model outperformed the existing methods under different measures.
文摘在一次能源的生产和消费中,清洁可再生能源因多重优势逐步得到青睐.然而,随着经济全球化的进程,对能源的需求也越来越大,新的能源供给矛盾也逐步凸显:能源时间和空间分布不均与能源需求点不匹配的矛盾.全球能源互联网的构建为解决该矛盾提供了解决途径,城市能源互联网作为全球能源互联网的重要补充,对其进行研究具有非常重要的意义.从构建城市能源互联网(urban energy internet,UEI)的基本形态和系统模式出发,以全球能源互联网(energy internet,EI)相关性特征为落脚点,研究了UEI的分类、概念及典型网络结构特征、网架结构等,对UEI的建设具有一定的指导意义.
