14 results about "On Demand Routing" patented technology

A system can execute a containerized application that comprises a microservice in a decentralized service mesh architecture, and a sidecar. The system can intercept, by the containerized application, a call from the microservice that is directed to a remote endpoint, and direct the call to the sidecar. The system can communicate, by the sidecar to an identity manager, service account credentials associated with the microservice, resulting in receiving an identity token associated with the microservice. The system can determine, by the sidecar, connectivity information of the remote endpoint based on a virtual address of the remote endpoint identified in the call. The system can communicate, by the sidecar to a token exchanger, the identity token and the connectivity information, resulting in receiving an access token and a network route to the remote endpoint. The system can relay, by the sidecar, network traffic between the microservice and the remote endpoint.

Some embodiments of the invention provide a method of facilitating routing through a software-defined wide area network (SD-WAN) defined for an entity. A first edge forwarding node located at a first multi-machine site of the entity, the first multi-machine site at a first physical location and including a first set of machines, serves as an edge forwarding node for the first set of machines by forwarding packets between the first set of machines and other machines associated with the entity via other forwarding nodes in the SD-WAN. The first edge forwarding node receives configuration data specifying for the first edge forwarding node to serve as a hub forwarding node for forwarding a set of packets from a second set of machines associated with the entity and operating at a second multi-machine site at a second physical location to a third set of machines associated with the entity and operating at a third multi-machine site at a third physical location. The first edge forwarding node serves as a hub forwarding node to forward the set of packets from the second set of machines to the third set of machines.

The invention discloses a dynamic QoS on-demand routing method oriented to service requirements, belongs to the field of industrial Internet of Things, and realizes self-adaptive routing optimization in an industrial Internet scene through multi-dimensional state perception, dynamic weight generation, unified reward modeling and a deep reinforcement learning strategy based on a software defined network (SDN) control architecture. According to the method, a dynamic weight adjustment mechanism based on a user portrait and a depth deterministic strategy gradient algorithm of priority experience playback are introduced, so that a routing strategy can keep stable and rapid convergence capability in a complex industrial environment, and the optimal dynamic QoS (Quality of Service) requirement can be automatically matched according to different service types; and therefore, the requirements of the industrial internet on high reliability, self-adaptive capability and intelligent network decision can be effectively met.

The invention relates to a routing method suitable for a high-dynamic flight ad hoc network, and the method comprises the steps: introducing a distributed clustering method based on multi-dimensional feature K-means clustering in an on-demand routing framework of a standard AODV, so as to construct a logical topology with clear hierarchy and high stability; power lightweight reverse expectation transmission counting PLR-ETX composite link measurement is used to replace a hop count to become a new routing index, and an optimal end-to-end path is intelligently evaluated and selected in a clustering forming process; the method specifically comprises the steps of node feature collection and processing, routing discovery based on a PLR-ETX routing index, directional routing discovery based on a K-means clustering method and the PLR-ETX routing index, hop-by-hop clustering routing establishment, network state updating and strategy iteration. Therefore, the routing stability is obviously improved, the overhead is reduced, and the data transmission efficiency is improved.

The invention relates to the technical field of information, and discloses a dynamic integration system and method for an electric power large model platform and heterogeneous systems, and the dynamic integration system comprises a protocol adaptation layer which is used for processing original heterogeneous data of a plurality of heterogeneous systems through a three-layer conversion engine, obtaining a standardized data stream, and dynamically adapting a transmission protocol of the standardized data stream; the service perception layer is used for generating a real-time routing rule by adopting a three-layer linkage mechanism based on the standardized data flow to control on-demand routing of the standardized data flow so as to obtain a routed data flow; the data pipeline layer is used for acquiring a binary log event of each heterogeneous system in real time, processing the routed data flow through a three-layer guarantee mechanism, generating training data consistent with the binary log event, and outputting the training data to each heterogeneous system; in complex cross-platform data interaction, high consistency and high reliability of data are realized.

The application discloses a mixed wireless mesh network routing method and system based on node type and interference perception, and the method comprises the following steps: nodes in a network periodically exchange Hello messages to maintain neighbor information and topology state, and the Hello messages carry queue length, residual energy, position and speed information of the nodes; according to the Hello messages, weight values of Mesh routers and Mesh clients in the network are respectively calculated; based on the weight values, routing metrics of gateway-oriented traffic and client-oriented traffic are respectively calculated; on-demand routing discovery is performed by using a route request and a route reply message, wherein an intermediate node updates the routing metrics based on the weight values, a destination node or a Mesh router which knows a path to the destination node replies to the route reply, and a source node selects a path for data transmission according to the routing metrics; when a link is broken or a network topology changes, a source node is informed by a route error message, and a new routing discovery process is triggered.

The present application relates to the field of mobile communication technology, especially to a kind of software defined wireless Mesh network adaptive networking method based on multi-link cooperation, comprising the following steps: each node discovers neighbor node, is connected by three different frequency band links to form Mesh network;Introduce SDN controller, real-time collection node state information, combine network topology change and service demand, according to different message type and link characteristic on-demand selection optimal route;When node fails or off-line, combine node mobility management mechanism, routing protocol converges quickly, simultaneously adjusts transmission path.The present application adopts software defined routing, is uniformly distributed by controller route and link selection, can be realized on-demand routing according to service type;By collecting network state information, adaptively change link weight, according to link condition and service type selection suitable route and link;Adopt E-Dijkstra algorithm, can realize the fast decision of route and link selection, reduces processing delay.

The embodiment of the invention provides an on-demand routing agent system for a low earth orbit satellite network and a generation method, and relates to the technical field of satellite communication, the agent system comprises a planning decision module, a network sensing module and an execution module, the planning decision module comprises a large model integrating well-designed system cues, and the network sensing module comprises a network sensing module and an execution module; the user demand text is analyzed to obtain communication demand parameters, the network sensing module is used for sensing the time-varying network state of the low-orbit satellite network and outputting a network topological graph, and the execution module comprises a satellite access tool and a route selection tool. The satellite access tool is used for determining uplink and downlink access satellites corresponding to longitude and latitude coordinates of a start-stop user in combination with the network topological graph, and the routing selection tool is used for selecting the uplink and downlink access satellites corresponding to the longitude and latitude coordinates of the start-stop user according to the network topological graph and the uplink and downlink access satellites by taking QoS parameter values as constraint conditions based on a routing calculation strategy corresponding to QoS parameter types. And the routing path between the uplink and downlink access satellites is determined, so that the service quality and the intelligent level of the low-orbit satellite network are improved.

According to the discrete event driven network simulation system and method based on the GPU, network events are recombined according to function causal dependence and time sequence dependence to form same-type event batches, and the same-type event batches are scheduled to the GPU for execution in a minimum propagation delay slot according to a protocol stack sequence, so that the SIMT architecture of the GPU is fully adapted, and the parallel efficiency is remarkably improved; the invention further provides a specific implementation method of GPU-driven discrete event network simulation, dynamic task scheduling is realized by constructing a global workload pool and a hierarchical alignment algorithm, and the GPU-driven discrete event network simulation is realized by combining a chained fragmented packet structure, on-demand routing calculation and a GPU-host collaborative caching mechanism on the premise of ensuring NS-3-level simulation fidelity. According to the method, the memory occupancy is greatly reduced, the simulation speed is improved, full-automatic simulation of tens of thousands of node-scale networks can be efficiently completed on a consumer-level GPU, manual intervention is not needed, and high expandability and engineering practicability are achieved.

The application discloses a satellite multi-hop task unloading optimization method and system based on edge computing, and the method comprises the following steps: when the access satellite computing resource of a ground user is insufficient, a on-demand routing protocol is adopted, and under the constraint condition, based on environment exploration information, a task unloading optimization problem is obtained by taking the minimum energy consumption of a system model as a target; the task unloading optimization problem is constructed into a Markov decision process, and a deep reinforcement learning algorithm is combined to solve the problem, so that a task unloading and routing selection optimization strategy is obtained. In the application, in the case that the access satellite computing resource is insufficient, the on-demand routing protocol is combined to support efficient multi-hop task transmission unloading, so that the selection of an intermediate satellite node on a routing path from a source satellite node to a destination satellite node is optimized on the basis of the minimum number of hops, the energy consumption is comprehensively considered, the multi-hop is dynamically used to reach a processing node, and the control overhead of the whole network topology in the task unloading process is maximally reduced.

The application provides an on-site IO device on-demand communication routing system and method, relates to the technical field of device communication, and the system comprises an application arrangement layer, an on-demand routing decision layer and a device layer; the application arrangement layer outputs data to the on-demand routing decision layer; the on-demand routing decision layer issues configuration to the device layer; the device layer reports state data to the on-demand routing decision layer; the application arrangement layer is used for defining system control tasks and generating a standardized system model; the on-demand routing decision layer is used for intelligent decision of a communication mode and configuration conversion; the application arrangement layer, the on-demand routing decision layer and the device layer are logically linked in sequence and constitute an end-to-end on-site IO device on-demand communication routing architecture. The application realizes intelligent on-demand selection of a communication mode, takes into account the advantages of centralized scheduling and direct communication, improves the real-time performance of data interaction and the flexibility of the system, adapts to dynamic process requirements, and improves the intelligent level and the self-adaptive level of an industrial control system.

This application provides an on-demand routing intelligent agent system and generation method for low-Earth orbit (LEO) satellite networks, relating to the field of satellite communication technology. The intelligent agent system includes a planning and decision-making module, a network perception module, and an execution module. The planning and decision-making module includes a large model integrating carefully designed system prompts and parses user request text to obtain communication request parameters. The network perception module is used to perceive the time-varying network state of the LEO satellite network and output a network topology map. The execution module includes a satellite access tool and a routing selection tool. The satellite access tool is used to determine the uplink and downlink access satellites corresponding to the latitude and longitude coordinates of the originating and ending users based on the network topology map and the uplink and downlink access satellites, using QoS parameter values ​​as constraints and a routing calculation strategy corresponding to the QoS parameter type, to determine the routing path between the uplink and downlink access satellites, thereby improving the service quality and intelligence level of the LEO satellite network.

The invention discloses a hybrid wireless mesh network routing method and system based on node types and interference awareness, and the method comprises the steps: nodes in a network periodically exchange Hello messages so as to maintain neighbor information and a topological state, and carry queue length, residual energy, position and speed information of the nodes; according to the Hello message, respectively calculating weight values of a Mesh router and a Mesh client in the network; respectively calculating routing metrics of the gateway-oriented traffic and the client-oriented traffic based on the weight values; on-demand routing discovery is carried out by using a routing request and a routing reply message, an intermediate node updates a routing metric based on a weight value, a destination node or a Mesh router knowing a path to the destination node replies a routing reply, and a source node selects a path according to the routing metric to carry out data transmission; and when the link is broken or the network topology is changed, notifying a source node through a routing error message, and triggering a new routing discovery process.

The application discloses a service demand-oriented dynamic QoS on-demand routing method, belongs to the field of industrial internet of things, and is based on a software defined network (SDN) control architecture, realizes adaptive routing optimization in an industrial internet scene through multi-dimensional state perception, dynamic weight generation, unified reward modeling and a deep reinforcement learning strategy. The method introduces a dynamic weight adjustment mechanism based on user portrait and a deep deterministic policy gradient algorithm with priority experience replay, so that the routing strategy can maintain stable and rapid convergence ability in a complex industrial environment, and can automatically match optimal dynamic quality of service (QoS) demand according to different service types, thereby effectively meeting the requirements of the industrial internet on high reliability, adaptive capability and intelligent network decision.