4 results about "Link weight" patented technology

The application provides a signaling communication network topology determination method and device, electronic equipment and a storage medium. The method comprises: obtaining an original optical network topology; determining the original carrying traffic, original security attribute value and original link weight of each link; deleting a first target link with the lowest original link weight to obtain a first updated network topology, and determining whether the first updated network topology meets the connectivity requirement; if the first updated network topology meets the connectivity requirement, determining the first updated carrying traffic and first updated security attribute value of each link; determining whether the first updated carrying traffic is not greater than the maximum carrying traffic of the link, and whether the first updated security attribute value reaches a preset security attribute value; if the first updated carrying traffic is greater than the maximum carrying traffic of the link, and / or the first updated security attribute value does not reach the preset security attribute value, adding the first target link to the first updated network topology to determine a target network topology.

The application provides a production management method based on artificial intelligence, comprising the following steps: constructing a space-time correlation traceability graph based on a production network topology and taking time sequence characteristic values of micro-variable mark sequences as node and link weights according to the micro-variable mark sequences, determining a congestion diffusion conduction direction and a network topology boundary coordinate; obtaining a real-time delay of a production task transmission path, performing space-time dimension feature correlation on the congestion diffusion conduction direction, the network topology boundary coordinate and the real-time delay of the corresponding production task transmission path, and determining a congestion risk; and monitoring a path utilization rate in real time, if the path utilization rate breaks through a preset critical buffer threshold, switching a new task to a next available path in order, and obtaining a final task bearing scheme that adapts to production load demand.

The application discloses a routing method, medium, equipment and product of a low-orbit satellite constellation, relates to the technical field of satellite routing, and comprises the following steps: according to a quality of service parameter, performing snapshot freezing on a current network topology to construct a static topology graph structure; constructing a basic quality of service parameter cost function for each link; performing an offline ant colony optimization algorithm to globally evaluate a satellite topology library constructed in advance, constructing a heuristic function according to a link basic quality of service parameter cost; initializing a pheromone value for each link, and updating the pheromone in an iteration process according to the heuristic function; adjusting the cost function based on the pheromone; taking the cost of the discounted pheromone as the final link weight of the satellite network, constructing a weighted graph structure, and adopting a shortest path search algorithm to calculate a routing path between a source node and a target node, so that an optimal routing path is obtained. The application solves the problems of high-speed time-varying satellite link state adaptability and poor quality of service.

This invention discloses a method, medium, device, and product for dynamic OSPF link weight optimization, relating to the field of OSPF link weight optimization technology. The method includes: acquiring OSPF link bandwidth, link latency, maximum utilization, and link error rate in real time via the SNMP protocol to construct a state vector; using the state vector as input and the weight adjustment values ​​of each link as output to construct a deep reinforcement learning model; calculating new link weights based on the weight adjustment values ​​output by the model; writing the new weight values ​​into the interface configuration of the OSPF router to trigger OSPF to recalculate routes. This invention directly applies deep reinforcement learning technology to OSPF link weight optimization, achieving intelligent and automated dynamic OSPF link weight optimization.