Bottlenecks in urban traffic network are sticking points in restricting network collectivity traffic efficiency. To identify network bottlenecks effectively is a foundational work for improving network traffic conditi...Bottlenecks in urban traffic network are sticking points in restricting network collectivity traffic efficiency. To identify network bottlenecks effectively is a foundational work for improving network traffic condition and preventing traffic congestion. In this paper, a congestion propagation model of urban network traffic is proposed based on the cell transmission model （CTM）. The proposed model includes a link model, which describes flow propagation on links, and a node model, which represents link-to-link flow propagation. A new method of estimating average journey velocity （AJV） of both link and network is developed to identify network congestion bottlenecks. A numerical example is studied in Sioux Falls urban traffic network. The proposed model is employed in simulating network traffic propagation and congestion bottleneck identification under different traffic demands. The simulation results show that continual increase of traffic demand is an immediate factor in network congestion bottleneck emergence and increase as well as reducing network collectivity capability. Whether a particular link will become a bottleneck is mainly determined by its position in network, its traffic flow （attributed to different OD pairs） component, and network traffic demand.展开更多
针对卫星延迟容忍网络(Delay Tolerant Network,DTN)中因卫星节点资源受限引起卫星节点拥塞问题,且由于DTN的保管传输特性不适用于传统拥塞控制机制,提出一种具有通用性的基于节点拥塞状态的队列优先级拥塞控制机制(Queue Priority Cong...针对卫星延迟容忍网络(Delay Tolerant Network,DTN)中因卫星节点资源受限引起卫星节点拥塞问题,且由于DTN的保管传输特性不适用于传统拥塞控制机制,提出一种具有通用性的基于节点拥塞状态的队列优先级拥塞控制机制(Queue Priority Congestion Control mechanism based on Congestion State,QPCC-CS).QPCC-CS机制能适用于多种DTN路由策略,处理拥塞时将卫星节点按拥塞程度进行分类,并按照不同的拥塞状态对卫星节点消息转发进行优先级队列化,同时清除冗余消息副本,通过消息迁移与消息删除相结合的方式处理溢出的消息,管理卫星节点缓存来缓解卫星节点拥塞.经仿真相比原路由策略QPCC-CS策略的加入能提高卫星数据投递率,降低了卫星网络传输开销,能给卫星DTN提供更好的性能需求.展开更多
Many networks in the real world have spatial attributes, such as location of nodes and length of edges, called spatial networks. When these networks are subject to some random or deliberate attacks, some nodes in the ...Many networks in the real world have spatial attributes, such as location of nodes and length of edges, called spatial networks. When these networks are subject to some random or deliberate attacks, some nodes in the network fail, which causes a decline in the network performance. In order to make the network run normally, some of the failed nodes must be recovered. In the case of limited recovery resources, an effective key node identification method can find the key recovering node in the failed nodes, by which the network performance can be recovered most of the failed nodes. We propose two key recovering node identification methods for spatial networks, which are the Euclidean-distance recovery method and the route-length recovery method. Simulations on homogeneous and heterogeneous spatial networks show that the proposed methods can significantly recover the network performance.展开更多
基金the National Basic Research Program of China (Grant No.2006CB705500)the National Natural Science Foundation of China (Grant No.70631001)the Innovation Foundation of Science and Technology for Excellent Doctorial Candidate of Beijing Jiaotong University (Grant No.48040)
文摘Bottlenecks in urban traffic network are sticking points in restricting network collectivity traffic efficiency. To identify network bottlenecks effectively is a foundational work for improving network traffic condition and preventing traffic congestion. In this paper, a congestion propagation model of urban network traffic is proposed based on the cell transmission model （CTM）. The proposed model includes a link model, which describes flow propagation on links, and a node model, which represents link-to-link flow propagation. A new method of estimating average journey velocity （AJV） of both link and network is developed to identify network congestion bottlenecks. A numerical example is studied in Sioux Falls urban traffic network. The proposed model is employed in simulating network traffic propagation and congestion bottleneck identification under different traffic demands. The simulation results show that continual increase of traffic demand is an immediate factor in network congestion bottleneck emergence and increase as well as reducing network collectivity capability. Whether a particular link will become a bottleneck is mainly determined by its position in network, its traffic flow （attributed to different OD pairs） component, and network traffic demand.
文摘针对卫星延迟容忍网络(Delay Tolerant Network,DTN)中因卫星节点资源受限引起卫星节点拥塞问题,且由于DTN的保管传输特性不适用于传统拥塞控制机制,提出一种具有通用性的基于节点拥塞状态的队列优先级拥塞控制机制(Queue Priority Congestion Control mechanism based on Congestion State,QPCC-CS).QPCC-CS机制能适用于多种DTN路由策略,处理拥塞时将卫星节点按拥塞程度进行分类,并按照不同的拥塞状态对卫星节点消息转发进行优先级队列化,同时清除冗余消息副本,通过消息迁移与消息删除相结合的方式处理溢出的消息,管理卫星节点缓存来缓解卫星节点拥塞.经仿真相比原路由策略QPCC-CS策略的加入能提高卫星数据投递率,降低了卫星网络传输开销,能给卫星DTN提供更好的性能需求.
基金Project supported by Zhejiang Provincial Natural Science Foundation of China (Grant No. LQ23F030012)the Fundamental Research Funds for the Provincial Universities of Zhejiang (Grant No. GK229909299001-018)。
文摘Many networks in the real world have spatial attributes, such as location of nodes and length of edges, called spatial networks. When these networks are subject to some random or deliberate attacks, some nodes in the network fail, which causes a decline in the network performance. In order to make the network run normally, some of the failed nodes must be recovered. In the case of limited recovery resources, an effective key node identification method can find the key recovering node in the failed nodes, by which the network performance can be recovered most of the failed nodes. We propose two key recovering node identification methods for spatial networks, which are the Euclidean-distance recovery method and the route-length recovery method. Simulations on homogeneous and heterogeneous spatial networks show that the proposed methods can significantly recover the network performance.
