156 results about "Transport network" patented technology

Failure of an active CU-UP can be managed and mitigated. In connection with an active CU-UP serving a device using a service, CU-CP can employ a node manager component (NMC) that, in connection with failure of active CU-UP, can synchronize operational state parameters, including user plane protocol state parameters, associated with active CU-UP with standby CU-UP, and transition from active CU-UP to standby CU-UP to become an active CU-UP that can serve the device, to maintain service continuity for the device. NMC can inform RAN SMO to reconfigure transport network to switch downlink data and uplink data to standby CU-UP. Standby CU-UP can buffer downlink data and uplink data in buffer memory until the synchronization is completed, after which the formerly standby, now active, CU-UP can communicate buffered downlink data to DU for communication to the device, and buffered uplink data to UPF for communication to a desired destination.

The invention discloses a carbon emission accounting method for a container multimodal transport network, and the method comprises the steps: firstly, determining a modeling boundary and a data set of the container multimodal transport network, and enabling the modeling boundary to comprise a space range, a time range and a modeling object; the data set comprises node attributes, connection edge attributes and node traffic volume data of data required for constructing the multimodal transport network model; then, establishing a data-driven multimodal transport network model, identifying a network topology structure through the model, and estimating network side point traffic; and finally, calculating the network carbon emission by combining the energy consumption characteristics of different transportation modes and different combined transportation transfer modes. The scheme not only can serve carbon emission evaluation of a single hub transportation network to realize hub enterprise freight network carbon emission footprint tracking and driving factor identification, but also can serve carbon emission evaluation of a regional multimodal transportation network to realize regional freight network carbon emission management level evaluation and driving factor identification, so that the economic benefit is improved. And a theoretical tool is provided for measuring the carbon emission reduction development level of the multimodal transport network with different dimensions.

The invention discloses a power-traffic network charging load prediction method and system, and a storage medium. The method comprises the following steps: constructing an electric vehicle basic model, a road network basic model, a charging station basic model and a power distribution network basic model; generating dynamic traffic flow data through a generative adversarial network based on the basic model and the historical traffic data; constructing a traffic travel demand matrix based on a start-end point analysis method, and simulating the whole process of charging decision, queuing waiting and charging service of the electric vehicle in the charging station by using a queuing theory algorithm in combination with the dynamic traffic flow data and the basic model; constructing a space-time diagram attention network model, taking charging demand simulation data, a road network basic model and a charging station basic model as input, obtaining a space-time coupling relationship between a traffic network state and a charging demand through a multi-head diagram attention mechanism, and predicting to obtain space-time distribution of an electric vehicle charging load in a certain period of time in the future. And accurate prediction of the time-space part of the charging load of the electric vehicle is realized.

Computer-implemented methods optimising routes in a transport network for a geographical region are disclosed. Methods comprise obtaining an analysis of the geographical region; generating probabilistic predictions, checking whether at least a subset of the generated probabilistic predictions have previously been solved by a trained machine learning model; based on at least a first subset of the generated probabilistic predictions having previously been solved, retrieving the trained machine learning model previously used to solve the at least a first subset of the generated probabilistic predictions and executing the trained machine learning model to determine a first plurality of suggested routes for the transport network; based on at least a second subset of the generated probabilistic predictions not having previously been solved, training a new machine learning model to solve the at least a second subset of generated probabilistic predictions to determine a second plurality of suggested routes for the transport network.

Apparatuses, systems, and techniques including APIs, subscription services, and controllers to enable one or more fifth generation new radio (5G-NR) networks to share information. For example, a processor comprising one or more circuits can perform an API or subscription service to cause a device in a radio access network (RAN) to share its analytic data with a device in a transport network, and said device in said transport network can use said analytic data to adjust its network settings to improve performance.

Embodiments of the present disclosure relate to methods, devices, apparatuses, and computer readable medium for macro-diversity transmission in a subnetwork. The method comprises: in response to receiving a first header identification associated with a Time Sensitive Communication (TSC) stream, a first device transmits, to a configuration entity of a transport network, a first stream requirement comprising two or more second identifications. Each of the two or more second identifications is associated with a corresponding second device configured for an interface end station in a first protocol plane. The first device receives communication configuration information indicating second header information from the configuration entity. Then, the first device transmits, to a second device operating as a source interface end station, the first header identification and third header information at least indicating the second header information. The second device is associated with a second identification of the two or more second identifications.

Various aspects of this disclosure generally relate to wireless communications. In some aspects, a central entity in an Integrated Access and Backhaul (IAB) network can: determine, at least in part, based on at least one of the following, that triggering conditions for updating transport network layer information of IAB nodes in the IAB network are met: a change in a donor distributed unit associated with an IAB node, a change in a central entity associated with an IAB node, or the establishment, release, or modification of a route including an IAB node; and provide updated transport network layer information to the IAB nodes, at least in part based on the satisfaction of the triggering conditions. Many other aspects are described.

The invention relates to the technical field of composite cables for rail transit, and provides a flexible composite cable for rail transit and a preparation method thereof.The preparation method comprises the steps that a power transmission unit, a signal transmission unit and PBO fiber bundles are constructed into a three-dimensional transmission network framework which is in a hollow tube shape as a whole through three-dimensional weaving; a plurality of upgrading channel pipes are arranged on the inner side of the three-dimensional transmission network framework, and the outer side of the three-dimensional transmission network framework is sequentially coated with a shielding layer and an outer protection layer from inside to outside. According to the flexible composite cable for the rail transit and the preparation method of the flexible composite cable, power transmission and signal transmission can be integrated, meanwhile, the overall anti-pressure capability, flexibility and anti-torsion stability are improved, the integrity of electrical connection and optical paths is effectively protected, the cost and upgrading complexity of the whole life cycle are remarkably reduced, and the service life of the cable is prolonged. And flexibility is provided for long-term technical evolution of a rail transit system, and reliable electromagnetic interference protection capability is maintained.

Handling resets comprises communicating transport packets between a transport network and data processing circuitry, with at least a portion of the data processing circuitry operating in a given reset

A method for configuring a first autonomous system in a transit network is described. The method includes obtaining information according to which the traffic received by an ingress router of the first autonomous system is saturated, and determining a prefix of a destination subnet of a third autonomous system downstream of the first autonomous system. The method also includes extending the path associated with the prefix on at least one target router of the first autonomous system, the prefix and the at least one target router being determined by optimizing an objective function so that the path associated with the prefix must be extended for all the ingress routers of the first autonomous system which are geographically closer to the saturated router than the target router.

Transmitters, receivers, transceivers, transport networks, and methods of use are described herein, including a transmitter comprising a client-side input, transmitter circuitry, and antennas. The client-side input receives baseband signals having client data encoded therein. The transmitter circuitry receives the baseband signals from the client-side input and generates antenna feed signals based on the baseband signals. The antennas receive the antenna feed signals from the transmitter circuitry, generate radiated signals based on the antenna feed signals, and couple the radiated signals into hollow waveguides. The radiated signals are radiated electromagnetic waves configured for coherent detection and having one or more frequencies in a range between 300 Gigahertz (GHz) and 10 Terahertz (THz). The antennas include one of a helical antenna, a waveguide probe antenna, a tapered antenna, a patch antenna, and a slot antenna.

Aspects of the subject disclosure may include, for example, a device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of identifying a public land mobile network (PLMN) identifier associated with a communications network; determining a tracking area code (TAC) range of a plurality of cell sites in a radio access network (RAN) associated with the PLMN identifier; identifying transport network circuits of a transport network connecting the plurality of cell sites with a core network of the communications network; and displaying a user interface comprising a graphical representation of the core network, the transport network and the RAN. Other embodiments are disclosed.

A system for purchasing travel documents and for paying tolls and / or parking fees is based on the use of Blockchain technology. It comprises a VTS Server (10), a Blockchain Server Node (15) synchronized with a Blockchain network (100) and a plurality of Smartphone user devices (20(i)). An application (APP(i), APPAuto(i)) for managing purchases towards at least one Transport company or Operator (40(j), 50(k)) is present on every Smartphone user device (20(i)). The Smartphone user device (20(i)) is provided with a first public address (addAPP(i), addAPPAuto(i)) and said Transport company or Operator (40(j), 50(k)) is provided with a second public address (add40(j), addAPPAuto(k)). The Blockchain Server Node (15) is connected to the Blockchain (100) by means of a connection (30) in Peer to Peer mode, P2P, and locally saves and stores (15w) a copy (BC) of the Blockchain (100), the first public addresses (addAPP(i), addAPPAuto(i)) associated with each user and the private keys (KEYpr(i)) of the users. The VTS Server (10) creates the public addresses (addAPP(i), addAPPAuto(i)) for each application (APP(i), APPAuto(i))) associated with a user, calculates the current balance of the user of the Smartphone (20(i)) and, in the event of sufficient value, creates and delivers, to the application (APP(i), APPAuto(i)), a pass or Token which allows the use of the Transport network and which generates a transaction (TE) on the Blockchain (100), in which the VTS Server (10) authorizes the transaction by means of the user private key (KEYpr(i)) saved (15w) in the Blockchain Server Node (15). The transaction (TE) transfers the content, or part of it, from a first wallet (20w(i)) belonging to the Smartphone user (20(i)) and associated with a first public address (addAPP(i), addAPPAuto(i))) to a second wallet (40w(j)) belonging to the Transport company or Operator (40(j), 50(k)) and associated with a second public address (add40(j), add50(k)).

Embodiments of present disclosure disclose internet protocol (IP) assignment and secure traffic for network elements deployed over untrusted transport network. In an embodiment, base station (101) transmits an Open Cloud (O-cloud) available registration request to an operator network system (103) through First Secure Tunnel (FST) (133) established between operator network system (103) and base station (101). The FST is terminated upon receiving network information related to each of plurality of O-cloud entities of O-cloud through FST from operator network system. Thereafter, base station (101) transmits second authentication request to operator network system for establishing Second Secure Tunnel (SST) (135) between operator network system and base station. Finally, base station establishes SST between operator network system and base station when network information is authenticated. The established SST allows bi-directional traffic related to each of plurality of O-cloud entities. The present disclosure helps in handling the traffic at the operator network system.

A kind of wisdom road full-time space instant simulation system, including data acquisition subsystem, data transmission subsystem, edge computing subsystem, interface display subsystem, situation expansion subsystem;Data acquisition subsystem relies on the data provided by road camera, unmanned aerial vehicle fleet and large map database, data transmission subsystem establishes the two-dimensional transmission network of ground-ground, ground-air, edge computing subsystem provides real-time data processing, calculation and analysis services for road conditions by serving the built-in computer processor in road camera, unmanned aerial vehicle fleet of road, interface display subsystem provides simulation interface, can visually show road real-time situation, situation expansion subsystem provides hierarchical, intelligent interface selection for interface display subsystem.The beneficial effects of the present application are: real-time analysis of road information, through the deployment of road-air computing power, provide full-time space, intelligent, visual wisdom road service.

The application provides an optimization method, system and equipment for a public and railway combined transport delivery network under external set internal matching, and belongs to the technical field of logistics distribution network optimization. The method is aimed at the problem that the traditional optimization algorithm in the prior art is prone to local optimization and difficult to obtain a globally satisfactory solution, and uses a deep learning assisted genetic algorithm to solve a pre-constructed public and railway combined transport network model. The algorithm performs real-time sensing on the population evolution state through a deep Q network, dynamically and intelligently selects a genetic operation strategy, and combines an experience playback mechanism to perform self-training and parameter updating, and finally outputs an optimal two-stage public and railway combined transport hub site selection and network freight flow distribution scheme. The application uses the above optimization method, system and equipment for a public and railway combined transport delivery network under external set internal matching, effectively improves the global search capability and adaptive level of the algorithm, and can obtain a public and railway combined transport network optimization scheme which is lower in cost, better in layout, and stable and reliable.

Provided in the embodiments of the present application are a network anomaly analysis method, a transport network and a related device, which can collaboratively analyze anomaly events of cable layers, optical layers, electrical layers or service layers comprised in transport networks, thereby improving the efficiency of discovery of hidden risks of networks. The method comprises: a network management device receives an anomaly message from a target optical device; the network management device obtains an anomaly event of a first optical layer channel caused by the anomaly message, and the network management device obtains an anomaly event of a first electrical layer channel caused by the anomaly event of the first optical layer channel; and the network management device obtains an anomaly event of a target service caused by the anomaly event of the first electrical layer channel.

The invention relates to a computer-implemented method for managing and optimizing logistics operations using autonomous transport platforms, the method comprising the following steps: - constructing a representation of a transport network comprising paths between strategic points, the strategic points including transfer zones, - constructing a representation of the autonomous transport platforms, - iteratively planning to establish, for each logistics operation, a route and the autonomous transport platform that will execute the route, by carrying out the sub-steps: - assigning a platform, - determining possible routes being the paths between an initial position, transfer zones and a final position, by reducing a discrepancy between the schedules of the possible routes and the time constraints of the logistics operation, - determining, for each possible route, the energy consumed.- Select the route from the possible routes. Figure for the abbreviation: Figure 1,

A process, method, architecture, apparatus, system, apparatus, and computer program product for a network node may be configured to receive configuration information from a second network node, the configuration information indicating a set of rules for allocating differentiated service code point (DSCP) values; obtaining a first protocol data unit (PDU) associated with the first PDU set and a second PDU associated with the second PDU set, wherein the first PDU set and the second PDU set are associated with the same quality of service (QOS) flow; determining a first DSCP value and a second DSCP value, wherein the first DSCP value and the second DSCP value are different; and generating a first packet including the first PDU and the first DSCP value and a second packet including the second PDU and the second DSCP value.

The network system triggers registration of the start of a transport journey in response to a communication of a transport user device and a transport provider device with each other, performs a continuous coordinated proximity monitoring to verify the identity of a transport user and a transport provider vehicle, and triggers registration of the end of the transport journey through communication of the transport user device and the transport provider device with each other.

The application provides a kind of metropolitan area transport network adaptive protection path planning method and device.The method is executed on metropolitan area transport network, and metropolitan area transport network is composed of multiple nodes.Network topology information of metropolitan area transport network is stored as graph data, and the traffic load of each service flow in the next time period is predicted based on the pre-trained traffic prediction model and the obtained historical traffic information, and the residual capacity of each link in the next time period in the metropolitan area transport network, the available time slot type and the corresponding number are estimated.The traffic prediction model uses graph convolution network to perform multi-layer feature extraction on the structure of network topology graph, constructs load balancing constraint, minimization blocking rate constraint and minimization resource consumption constraint, and generates protection path and protection time slot allocation scheme for each service flow according to the residual capacity of each link in the next time period, the available time slot type and the corresponding number, to realize more efficient fault recovery and protection path selection.

A multi-constraint route recommendation method for an air-rail transport network comprises the following steps: 1) constructing an air-rail transport network model; 2) using a prediction model to predict the user acceptance rate of the currently feasible routes between the starting point and the destination; and 3) prioritizing the route recommendations with reference to the user acceptance rate of the feasible routes. In step 1), the air-rail transport network model is composed of an upper aviation network layer and a lower high-speed rail network layer, and the two layers are connected by an intra-city transfer system. In step 2), the prediction model is as follows: using air-rail transport route screening conditions to filter out route data in the air-rail transport network model; combining the time cost, economic cost, and user acceptance rate of each route under different departure times into a triplet data set; constructing a linear regression equation as an air-rail transport route prediction model; importing the triplet data set into the linear regression equation, calculating the unknown parameters in the linear regression equation, and obtaining the air-rail transport route prediction model.

Aspects of the subject disclosure may include, for example, receiving a service request relating to an mIoT application, identifying service delivery and feature requirements, resulting in identified requirements, obtaining first information from an AIC regarding resources in access network(s), second information from a TIC regarding resources in transport network(s), and third information from a CIC regarding resources in core network(s), selecting a first resource in the access network(s), a second resource in the transport network(s), a third resource in the core network(s), and at least one treatment function, generating an SRH that identifies the first, second, and third resources and the at least one treatment function, and causing the SRH to be provided to the AIC to facilitate embedding of the SRH into packets relating to the mIoT application, thereby enabling connectionless E2E service delivery for the mIoT application. Other embodiments are disclosed.

Apparatuses, systems, and techniques including APIs, subscription services, and controllers to enable one or more fifth generation new radio (5G-NR) networks to share information. For example, a processor comprising one or more circuits can perform an API or subscription service to cause a device in a radio access network (RAN) to share its analytic data with a device in a transport network, and said device in said transport network can use said analytic data to adjust its network settings to improve performance.

Provided are an apparatus and a method for computing a path for forwarding user data through the following steps: receiving a state measurement value or a state prediction value corresponding to the state measurement value of a state of a plurality of network resources within a mobile core network and a transport network; and computing the path for forwarding the user data, on the basis of either the state measurement value or the state prediction value, and topology of the mobile core network and topology of the transport network.

The application discloses a kind of building waste tracking methods based on graph neural network, constructs pre-processing building waste transport multi-source data;Building waste transport network weighted heterogeneous graph is constructed based on pre-processing building waste transport multi-source data;Generation and update GraphSAGE node embedding vector;The breakpoint event composed of interrupt position, occurrence time and state element is output;Fixed hop local subgraph is extracted on building waste transport network weighted heterogeneous graph;Get the priority of the set of detour candidate paths, and select the highest score of self-healing tracking path;Form the updated building waste transport path tracking expected path, combine the compliance risk information in GraphSAGE node embedding vector, mark potential illegal dumping risk node, and output building waste path tracking result.The application realizes detour path optimization and exclusion of high-risk path, so that path reconstruction is more in line with urban transportation scheduling and regulatory requirements.

Methods and devices for a mobile communication system are disclosed. According to an embodiment, there is provided a method in a mobile communication system comprising a radio access network, RAN, comprising a first RAN node and a second RAN node connected by a transport network comprising a first transport node and a second transport node, wherein the first RAN node is connected to the first transport node and the second RAN node is connected to the second transport node, the method comprising, by the first transport node: determining a status of the transport network connection between the first transport node and the second transport node; generating a message indicating the status of the transport network connection; and initiating transmission of the message to the first RAN node.

The application relates to a multimodal transport planning method and device, computer equipment, medium and computer program product. The method comprises the following steps: constructing a coal transport network topology graph according to nodes and transport edges in a coal transport network; the number of nodes and transport edges is multiple, and the transport edge is a transport path between nodes; obtaining node parameters of the nodes and transport parameters of the transport edges in the coal transport network; constructing a target optimization model based on the coal transport network topology graph, the node parameters, the transport parameters and a preset optimization target; determining the transport path, the transport mode corresponding to the transport path and the transport quantity of each type of coal based on the target optimization model. The method can plan a transport path, a transport mode corresponding to each transport path and a transport quantity of different types of coal that can meet the actual demand of a user under the premise of meeting the actual transport condition, so that the actual demand of the user can be met, and the overall transport efficiency is improved.

The invention specifically relates to a BIM-based hydraulic engineering design earthwork volume calculation method, and relates to the technical field of hydraulic engineering design, and the method comprises the steps: generating a cross-regional scheduling instruction through a high layer, and carrying out the coevolution process of intra-regional precise optimization and cost feedback iteration through a bottom layer until the overall total cost is converged, and obtaining an optimal cross-regional scheduling and intra-regional deployment scheme. According to the method, qualitative engineering constraints such as soil matching, construction time sequence and transport distance economy are converted into quantifiable transport network graph theory rules such as effective edge filtering, time sequence verification and flow limitation, and it is ensured that the measurement and calculation process strictly conforms to the actual construction logic; the risk that a deployment scheme is not feasible due to the fact that constraint consideration is not comprehensive in a traditional method is avoided from the source, and double improvement of measurement and calculation precision and construction adaptability is achieved.

The invention provides a train control system time series data enhancement method based on semantic guide diffusion. The method comprises the steps of periodically collecting data transmission network performance index data in a train operation process according to operation characteristics of an urban rail train control data transmission system, and constructing a time sequence data set; constructing a semantic guidance diffusion framework SG-DiffTS model, wherein the SG-DiffTS model comprises a semantic guidance network and a time sequence decomposition denoising reconstruction network; using the time sequence data set to train an SG-DiffTS model, and after the training is completed, obtaining a trained SG-DiffTS model; and performing enhancement processing on the real data transmission network performance index data in the actual operation process of the train control system by using the trained SG-DifITS model. According to the method, trend and periodic semantics in a time sequence are extracted and fused in an unsupervised mode by using a conditional denoising diffusion probability model, so that the key problem that the performance of a deep learning model is restricted due to data scarcity in a train control system is solved.