The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving(CWD)electric vehicles,from both traffic and energy points of view.To accurately quanti...The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving(CWD)electric vehicles,from both traffic and energy points of view.To accurately quantify the electric power required from an energy supplier for the proper management of the charging system,a traffic simulation model is implemented.This model is based on a mesoscopic approach,and it is applied to a freight distribution scenario.Lane changing and positioning are managed according to a cooperative system among vehicles and supported by advanced driver assistance systems(ADAS).From the energy point of view,the analyses indicate that the traffic may have the following effects on the energy of the system:in a low traffic level scenario,the maximum power that should be supplied for the entire road is simulated at approximately 9 MW;and in a high level traffic scenario with lower average speeds,the maximum power required by the vehicles in the charging lane increases by more than 50%.展开更多
The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industria...The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart agriculture.Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes.This paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks.The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies.The protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base station.The performance of the proposed protocol is evaluated through the network simulator NS3.40.For different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network lifetime.For 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.展开更多
The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy R...The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy Resource Management(SDHRM)algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic.In network-level resource allocation,the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility.In connection-level network selection,based on the above resource allocation and the pre-defined QoS requirement,three typical network selection policies are provided to assign traffic flow to the most appropriate network.Furthermore,based on multidimensional Markov model,we analyse the performance of SDHRM in HWNs with heavy tailed traffic.Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.展开更多
Pavement is an important part of transportation infrastructure.In order to maintain pavement before the damage and improve the service quality,it is necessary to develop an intelligent and durable pavement information...Pavement is an important part of transportation infrastructure.In order to maintain pavement before the damage and improve the service quality,it is necessary to develop an intelligent and durable pavement information monitoring system.However,the pavement dynamic response monitoring is highly costly,easily obsolete and statistically redundant.The emergence of the Internet of Things(IoT)technology promises to change that.In this paper,an architecture of a distributed road IoT monitoring system is proposed,which has an acquisition layer,a preprocessing layer,a processing layer,an interaction layer,an energy layer and a network layer.Then,a prototype wireless pavement vibration monitoring system based on the IoT is developed,which consists of a number of wireless sensing nodes,a gateway,a remote server and a browser.Finally,data preprocessing,wireless communication,time synchronization,data processing and visualization,which represent the key to an effective system,are tested and discussed.The prototype wireless pavement vibration monitoring system provides a viable scheme for upgrading the IoT system and its application in the road infrastructures.In the future,any smart road will have an IoT wireless monitoring system to monitor the traffic,environment,and pavement information,which help enable traffic guidance,signal control,danger warning,scientific maintenance decision-making.展开更多
移动业务流量在过去几年呈指数型增长,给移动运营商的核心网带来了巨大的冲击。3GPP提出了LIPA/SIPTO(Local IP Access/Selected IP Traffic Offload)的网络架构来卸载选定核心网络的移动业务流量。然而,如何选择流量并进行卸载没有给...移动业务流量在过去几年呈指数型增长,给移动运营商的核心网带来了巨大的冲击。3GPP提出了LIPA/SIPTO(Local IP Access/Selected IP Traffic Offload)的网络架构来卸载选定核心网络的移动业务流量。然而,如何选择流量并进行卸载没有给出具体的解决方案。针对这一问题,提出了一套基于业务识别的流量卸载机制,包括无线网络环境中的在线实时业务识别算法METCS及动态流量卸载路径选择算法。仿真结果表明METCS与现有的方法相比,识别准确率提高了5%-8%,复杂度降低了40%。基于METCS的流量卸载机制能使核心网流量减少60%,同时能根据网络负载变化实时动态的选择最优卸载路径以满足不同类型业务的QoS需求。展开更多
Internet of Car, resulting from the Internet of Things, is a key point for the forthcoming smart city. In this article, GPS technology, 3G wireless technology and cloud-processing technology are employed to construct ...Internet of Car, resulting from the Internet of Things, is a key point for the forthcoming smart city. In this article, GPS technology, 3G wireless technology and cloud-processing technology are employed to construct a cloud-processing network platform based on the Internet of Car. By this platform, positions and velocity of the running cars, information of traffic flow from fixed monitoring points and transportation videos are combined to be a virtual traffic flow data platform, which is a parallel system with real traffic flow and is able to supply basic data for analysis and decision of intelligent transportation system.展开更多
基金This study is partially supported by the eCo-FEV project(Grant agreement No.314411).
文摘The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving(CWD)electric vehicles,from both traffic and energy points of view.To accurately quantify the electric power required from an energy supplier for the proper management of the charging system,a traffic simulation model is implemented.This model is based on a mesoscopic approach,and it is applied to a freight distribution scenario.Lane changing and positioning are managed according to a cooperative system among vehicles and supported by advanced driver assistance systems(ADAS).From the energy point of view,the analyses indicate that the traffic may have the following effects on the energy of the system:in a low traffic level scenario,the maximum power that should be supplied for the entire road is simulated at approximately 9 MW;and in a high level traffic scenario with lower average speeds,the maximum power required by the vehicles in the charging lane increases by more than 50%.
基金This work was supported by the Basic Science Research Program through the NationalResearch Foundation ofKorea(NRF)funded by the Ministry of Education under Grant RS-2023-00237300 and Korea Institute of Planning and Evaluation for Technology in Food,Agriculture and Forestry(IPET)through the Agriculture and Food Convergence Technologies Program for Research Manpower Development,funded by Ministry of Agriculture,Food and Rural Affairs(MAFRA)(Project No.RS-2024-00397026).
文摘The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart agriculture.Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes.This paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks.The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies.The protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base station.The performance of the proposed protocol is evaluated through the network simulator NS3.40.For different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network lifetime.For 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.
基金ACKNOWLEDGEMENT This work was supported by the National Na- tural Science Foundation of China under Gra- nts No. 61172079, 61231008, No. 61201141, No. 61301176 the National Basic Research Program of China （973 Program） under Grant No. 2009CB320404+2 种基金 the 111 Project under Gr- ant No. B08038 the National Science and Tec- hnology Major Project under Grant No. 2012- ZX03002009-003, No. 2012ZX03004002-003 and the Shaanxi Province Science and Techno- logy Research and Development Program un- der Grant No. 2011KJXX-40.
文摘The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy Resource Management(SDHRM)algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic.In network-level resource allocation,the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility.In connection-level network selection,based on the above resource allocation and the pre-defined QoS requirement,three typical network selection policies are provided to assign traffic flow to the most appropriate network.Furthermore,based on multidimensional Markov model,we analyse the performance of SDHRM in HWNs with heavy tailed traffic.Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.
基金funded by Beijing Major Science and Technology Projects(grant number Z191100008019002)Fundamental Research Funds for the Central University(FRFTP-19-050A1,FRF-BD-19-001A,FRF-MP-19-014)Technology Innovation and Demonstration Project(2021)of the Department of Transport of Yunnan Province。
文摘Pavement is an important part of transportation infrastructure.In order to maintain pavement before the damage and improve the service quality,it is necessary to develop an intelligent and durable pavement information monitoring system.However,the pavement dynamic response monitoring is highly costly,easily obsolete and statistically redundant.The emergence of the Internet of Things(IoT)technology promises to change that.In this paper,an architecture of a distributed road IoT monitoring system is proposed,which has an acquisition layer,a preprocessing layer,a processing layer,an interaction layer,an energy layer and a network layer.Then,a prototype wireless pavement vibration monitoring system based on the IoT is developed,which consists of a number of wireless sensing nodes,a gateway,a remote server and a browser.Finally,data preprocessing,wireless communication,time synchronization,data processing and visualization,which represent the key to an effective system,are tested and discussed.The prototype wireless pavement vibration monitoring system provides a viable scheme for upgrading the IoT system and its application in the road infrastructures.In the future,any smart road will have an IoT wireless monitoring system to monitor the traffic,environment,and pavement information,which help enable traffic guidance,signal control,danger warning,scientific maintenance decision-making.
文摘移动业务流量在过去几年呈指数型增长,给移动运营商的核心网带来了巨大的冲击。3GPP提出了LIPA/SIPTO(Local IP Access/Selected IP Traffic Offload)的网络架构来卸载选定核心网络的移动业务流量。然而,如何选择流量并进行卸载没有给出具体的解决方案。针对这一问题,提出了一套基于业务识别的流量卸载机制,包括无线网络环境中的在线实时业务识别算法METCS及动态流量卸载路径选择算法。仿真结果表明METCS与现有的方法相比,识别准确率提高了5%-8%,复杂度降低了40%。基于METCS的流量卸载机制能使核心网流量减少60%,同时能根据网络负载变化实时动态的选择最优卸载路径以满足不同类型业务的QoS需求。
基金supported by National Basic Research Program of China (973 Program) 2012CB821200 (2012CB821206)National Natural Science Foundation under Grant No. 61170113, No.91024001, No.61070142+1 种基金Beijing Natural Science Foundation(No.4111002)KM201010011006, PHR201008242
文摘Internet of Car, resulting from the Internet of Things, is a key point for the forthcoming smart city. In this article, GPS technology, 3G wireless technology and cloud-processing technology are employed to construct a cloud-processing network platform based on the Internet of Car. By this platform, positions and velocity of the running cars, information of traffic flow from fixed monitoring points and transportation videos are combined to be a virtual traffic flow data platform, which is a parallel system with real traffic flow and is able to supply basic data for analysis and decision of intelligent transportation system.
