High-resolution vehicular emissions inventories are important for managing vehicular pollution and improving urban air quality. This study developed a vehicular emission inventory with high spatio-temporal resolution ...High-resolution vehicular emissions inventories are important for managing vehicular pollution and improving urban air quality. This study developed a vehicular emission inventory with high spatio-temporal resolution in the main urban area of Chongqing, based on realtime traffic data from 820 RFID detectors covering 454 roads, and the differences in spatiotemporal emission characteristics between inner and outer districts were analysed. The result showed that the daily vehicular emission intensities of CO, hydrocarbons, PM2.5, PM10,and NO_(x) were 30.24, 3.83, 0.18, 0.20, and 8.65 kg/km per day, respectively, in the study area during 2018. The pollutants emission intensities in inner district were higher than those in outer district. Light passenger cars(LPCs) were the main contributors of all-day CO emissions in the inner and outer districts, from which the contributors of NO_(x) emissions were different. Diesel and natural gas buses were major contributors of daytime NO_(x) emissions in inner districts, accounting for 40.40%, but buses and heavy duty trucks(HDTs) were major contributors in outer districts. At nighttime, due to the lifting of truck restrictions and suspension of buses, HDTs become the main NO_(x) contributor in both inner and outer districts,and its three NO_(x) emission peak hours were found, which are different to the peak hours of total NO_(x) emission by all vehicles. Unlike most other cities, bridges and connecting channels are always emission hotspots due to long-time traffic congestion. This knowledge will help fully understand vehicular emissions characteristics and is useful for policymakers to design precise prevention and control measures.展开更多
超大规模数据中心成为数字社会的关键基础设施。用户端应用的激增使得数据中心网络(Data Center Networks,DCNs)的东西向流量呈指数级增长,同时端应用的多样化也导致了严重的流量倾斜问题。此外,后摩尔时代的到来和Dennard缩放的失效使...超大规模数据中心成为数字社会的关键基础设施。用户端应用的激增使得数据中心网络(Data Center Networks,DCNs)的东西向流量呈指数级增长,同时端应用的多样化也导致了严重的流量倾斜问题。此外,后摩尔时代的到来和Dennard缩放的失效使得数据中心网络设备容量的增速趋缓。数据中心网络面临用户激增、流量倾斜和CMOS性能墙等多重压力。为解决上述问题,可重构数据中心网络(Reconfigurable Data Center Networks,RDCNs)应运而生。文中首先介绍RDCNs的5个研究驱动力,重点概述了两类物理层使能技术;其次,详细阐述RDCNs研究分类和链路重构、层重构以及拓扑重构这三大设计空间关键技术的研究现状;然后,简述RDCNs理论的研究进展;最后,展望未来研究方向并总结全文。展开更多
超可靠低时延业务(ultra-reliable and low-latency communication,URLLC)时延性能与5G系统的带宽资源、边缘速率、调度方式、以及天线数、载波频率、调制编码方案、帧结构等系统参数配置密切相关。针对垂直行业部署URLLC业务时的工程...超可靠低时延业务(ultra-reliable and low-latency communication,URLLC)时延性能与5G系统的带宽资源、边缘速率、调度方式、以及天线数、载波频率、调制编码方案、帧结构等系统参数配置密切相关。针对垂直行业部署URLLC业务时的工程测算需求,建立了一种用于描述URLLC时延性能的通用模型。进一步地,提出一种包括分析URLLC数据传输流程中的时延组成、确定调制编码方案和计算最大传输次数等步骤的时延分析方法。最后,通过对5G NR数据传输过程的链路级仿真,分析了不同可靠性要求与系统参数配置下的URLLC时延分布特性。所提方法为分析URLLC业务性能与5G网络资源需求之间的定量关系提供了一种实用解决方案。展开更多
基金supported by the National Key Research Program(No.2018YFB1601105,No.2018YFB1601102)the Natural Science Foundation of China(No.41975165,No.U1811463)Chongqing Science and Technology Project(No.cstc2019jscxfxydX0035)。
文摘High-resolution vehicular emissions inventories are important for managing vehicular pollution and improving urban air quality. This study developed a vehicular emission inventory with high spatio-temporal resolution in the main urban area of Chongqing, based on realtime traffic data from 820 RFID detectors covering 454 roads, and the differences in spatiotemporal emission characteristics between inner and outer districts were analysed. The result showed that the daily vehicular emission intensities of CO, hydrocarbons, PM2.5, PM10,and NO_(x) were 30.24, 3.83, 0.18, 0.20, and 8.65 kg/km per day, respectively, in the study area during 2018. The pollutants emission intensities in inner district were higher than those in outer district. Light passenger cars(LPCs) were the main contributors of all-day CO emissions in the inner and outer districts, from which the contributors of NO_(x) emissions were different. Diesel and natural gas buses were major contributors of daytime NO_(x) emissions in inner districts, accounting for 40.40%, but buses and heavy duty trucks(HDTs) were major contributors in outer districts. At nighttime, due to the lifting of truck restrictions and suspension of buses, HDTs become the main NO_(x) contributor in both inner and outer districts,and its three NO_(x) emission peak hours were found, which are different to the peak hours of total NO_(x) emission by all vehicles. Unlike most other cities, bridges and connecting channels are always emission hotspots due to long-time traffic congestion. This knowledge will help fully understand vehicular emissions characteristics and is useful for policymakers to design precise prevention and control measures.
文摘超大规模数据中心成为数字社会的关键基础设施。用户端应用的激增使得数据中心网络(Data Center Networks,DCNs)的东西向流量呈指数级增长,同时端应用的多样化也导致了严重的流量倾斜问题。此外,后摩尔时代的到来和Dennard缩放的失效使得数据中心网络设备容量的增速趋缓。数据中心网络面临用户激增、流量倾斜和CMOS性能墙等多重压力。为解决上述问题,可重构数据中心网络(Reconfigurable Data Center Networks,RDCNs)应运而生。文中首先介绍RDCNs的5个研究驱动力,重点概述了两类物理层使能技术;其次,详细阐述RDCNs研究分类和链路重构、层重构以及拓扑重构这三大设计空间关键技术的研究现状;然后,简述RDCNs理论的研究进展;最后,展望未来研究方向并总结全文。
文摘超可靠低时延业务(ultra-reliable and low-latency communication,URLLC)时延性能与5G系统的带宽资源、边缘速率、调度方式、以及天线数、载波频率、调制编码方案、帧结构等系统参数配置密切相关。针对垂直行业部署URLLC业务时的工程测算需求,建立了一种用于描述URLLC时延性能的通用模型。进一步地,提出一种包括分析URLLC数据传输流程中的时延组成、确定调制编码方案和计算最大传输次数等步骤的时延分析方法。最后,通过对5G NR数据传输过程的链路级仿真,分析了不同可靠性要求与系统参数配置下的URLLC时延分布特性。所提方法为分析URLLC业务性能与5G网络资源需求之间的定量关系提供了一种实用解决方案。
