14 results about "Elastic network" patented technology

The embodiment of the invention relates to a resource configuration method and device, computer equipment and a storage medium, when it is detected that a first virtual private cloud creates a product instance, bottom layer resources corresponding to the product instance are deployed to a target subnet of a second virtual private cloud, and a target address field is preset in the second virtual private cloud; the target address field comprises a target subnet; binding an elastic network card in the first virtual private cloud with a cloud server of a second virtual private cloud to enable the first virtual private cloud and the second virtual private cloud to communicate through the bound elastic network card; and configuring the underlying resources of the product instance in the communication process. Therefore, the bottom layer resource of the product instance of the first virtual private cloud can be deployed in the fixed second virtual private cloud, and communication between the two virtual private clouds is constructed, so that configuration of the deployed bottom layer resource is realized, direct configuration of the bottom layer resource on a user side is avoided, and the security of cloud product resource deployment is improved.

In one implementation, a device receives one or more constraints from a user interface regarding an acceptable level of performance of a computer network. The device forms, based on the one or more constraints, a policy to control performance of actions in the computer network to reduce its energy consumption. The device determines whether a particular action to reduce energy consumption by the computer network would violate the policy. The device causes performance of the particular action in the computer network, when doing so does not violate the policy.

According to some embodiments, system and methods are provided, comprising receiving, from a network configuration module, configuration data at a network driver of a communication network; configuring the network driver based on the received configuration data; receiving one or more data packets at the network driver from an application; determining that one or more segregation features are present in the data packet based on the received configuration data; transmitting the one or more data packets based on the one or more segregation features; and controlling one or more operations of an installed product based on the transmitted one or more data packets. Numerous other aspects are provided.

The present application relates to computer network technical field, specifically for a kind of configuration VPC multi-availability zone isolation FIP network method and system, comprising the following steps: in product configuration file, the FIP network name corresponding to VPC multi-availability zone is configured;Tenant logs in console interface, click to create virtual machine private network, select the availability zone of VPC, create VPC under two availability zones;Tenant logs in console interface, check virtual private network list;Tenant logs in console interface, create elastic network card;Beneficial effect is: the configuration VPC multi-availability zone isolation FIP network method and system proposed in the present application, when VPC is created in virtual private network console, availability zone is selected, and the corresponding FIP network is obtained according to availability zone.The subnet availability zone under VPC is consistent with the selected VPC availability zone by default.Different FIP networks in different availability zones are realized by configuring different FIP networks under VPC multi-availability zone, and cloud resources in the same availability zone can be interconnected through FIP network.

This application relates to a gateway determination method, apparatus, computer device, and storage medium. The method includes: determining whether a target association entry containing the protocol address exists in a preset association flow table based on the protocol address of the target virtual network interface card (NIC) to which the data to be transmitted belongs; the preset association flow table is used to indicate whether the target virtual NIC is associated with a flexible network address; if it exists, determining the target gateway for the data to be transmitted based on the target association entry and the routing address corresponding to the target virtual NIC; if it does not exist, determining the target gateway for the data to be transmitted based on the protocol address and routing address of the target virtual NIC. This method can accurately determine whether a target virtual NIC is associated with a flexible network address by setting a preset association flow table, and accurately determine the target gateway for the data to be transmitted, avoiding gateway selection confusion caused by identical routing configurations of target gateways, and further improving the accuracy of gateway selection.

A cloud system based on a public cloud service including a virtual private cloud (VPC) and a load balancer. The VPC includes a first subnet, a second subnet, and a third subnet. The load balancer includes a first elastic network interface ENI and a second ENI. In the cloud system provided in this solution, when sending a request packet to a second instance in the second subnet, a first instance in the first subnet forwards the packet to a packet processing service node in the third subnet via the first ENI and the second ENI. In this way, the packet is forwarded by the packet processing service node in the third subnet without additional packet header encapsulation, thereby simplifying a packet processing operation, and improving performance of the cloud system.

A data transmission method based on a cloud network, a device, and a medium are provided. The method includes: receiving a first data flow transmitted through a first elastic network interface in an elastic network interface pair connected to a first cloud server, in which the elastic network interface pair includes the first elastic network interface and a second elastic network interface, and the first elastic network interface is configured to transmit a data flow to a second cloud server through the second elastic network interface connected to the second cloud server; and when it is determined that the first data flow is transmitted through the elastic network interface pair, querying an address of the second elastic network interface in a fast channel, and forwarding the first data flow to the second cloud server based on the address of the second elastic network interface.

This invention relates to the field of intelligent transportation technology, specifically a digital system for traffic safety facilities based on intelligent connected vehicles. The system acquires facility status and traffic environment data in real time through a data acquisition module; a data processing module constructs a heterogeneous, fusion-based, self-healing, and resilient network to achieve dynamic scheduling and fault self-healing of multi-protocol links, generating structured real-time data streams; a strategy output module constructs a traffic facility association map, uses a diffraction chain pre-simulation sandbox to perform risk path deduction, and generates a risk pre-control strategy set; a system optimization module parses and executes strategies through a compensatory control engine, and achieves closed-loop optimization by combining effect quantification evaluation. This invention, by deploying an adaptive control loop of detection input – data link – strategy generation – signal drive – parameter optimization, completes the logical leap of signal control from open-loop response to feedforward control, and from fixed parameters to dynamic generation, significantly enhancing the throughput of road network nodes and the utilization rate of spatiotemporal resources.

The invention provides a comprehensive monitoring system for a hydropower station, which constructs a high-fidelity virtual model of power station equipment through a total-factor digital twin engine module, predicts the state of the equipment and provides situation pre-judgment capability. A deterministic transmission network which can be dynamically reconfigured is constructed by means of an intelligent elastic network architecture module, and differentiated service quality and transmission reliability are guaranteed. And the multi-modal data fusion center integrates and fuses multi-source heterogeneous data and a prediction result to generate unified panoramic situation awareness information, so that a comprehensive basis is provided for decision making. And the intelligent strategy generation module can form a distributed cooperative control strategy, so that the intelligence and cooperative efficiency of system control are improved. And the disaster recovery autonomous recovery module realizes rapid positioning and automatic recovery of system faults by using the strategy and the panoramic information. And finally, an intelligent resource scheduling module ensures efficient utilization of system resources and smoothness of overall operation. Therefore, comprehensive improvement of operation efficiency, safety and reliability is finally achieved.

In one implementation, a device queries an ontology that represents entities in a computer network and their relationships for a particular topology in the computer network. The device computes a mathematical system that represents traffic in the particular topology, based on traffic for only a portion of the particular topology. The device uses the mathematical system to compute traffic in the particular topology for a potential change to the particular topology expected to reduce energy consumption by the computer network. The device causes, based in part on the traffic computed using the mathematical system, the potential change to be made to the computer network.

The invention discloses a fault diagnosis model training and application method and device, and a medium, and relates to the technical field of anode fault diagnosis, and the fault diagnosis model training method comprises the steps: obtaining a training set; the training set comprises sample performance influence data of the aluminum electrolysis cell and an anode fault type corresponding to each piece of sample performance influence data; taking the sample performance influence data as input, taking the anode fault type corresponding to the sample performance influence data as a label, training a fault diagnosis model, and obtaining a trained fault diagnosis model; the fault diagnosis model is a regularization kernel extreme learning machine, and the regularization kernel extreme learning machine introduces an elastic network regularization formula into the kernel extreme learning machine, so that the over-fitting phenomenon is significantly reduced, the generalization ability of the model is improved, and the training speed of the model is improved.

In one implementation, a device assigns a budget to a bidding agent associated with a networking entity in a computer network. The device obtains a bid from the bidding agent selected by the bidding agent based on the budget. The device conducts an auction using the bid. The device excludes the networking entity from being eligible for performance of an energy-saving action, based on a result of the auction.

The invention provides a corn breeding intelligent question-answering system based on a large language model, which comprises an infrastructure layer, a knowledge processing layer, an intelligent layer, a business layer and a user layer, and is characterized in that the infrastructure layer comprises basic resources of virtualization, an elastic network, a cloud server and an NAS (Network Attached Storage); the knowledge processing layer is used for effectively processing and organizing knowledge to form structured knowledge resources; the intelligent layer is used for intelligently applying and analyzing knowledge and providing intelligent support for the business layer; the business layer is used for constructing a weeding platform; the user layer interacts with the millet platform through terminal equipment to obtain various services provided by the system, and the system integrates mixed retrieval, context understanding and distributed task processing, and specially provides professional intelligent question and answer services for the corn breeding field. And mixed retrieval is adopted, synonym replacement is integrated, the retrieval accuracy and the recall rate are improved, streaming response, real-time answer pushing and buffer area and performance optimization are achieved.

A gateway determination method, comprising: on the basis of a protocol address of a target virtual network interface card to which data to be transmitted belongs, determining whether there is a target association table entry including the protocol address in a preset association flow table (202), wherein the preset association flow table is used for indicating whether the target virtual network interface card is associated with an elastic network address; if there is a target association table entry including the protocol address in the preset association flow table, on the basis of the target association table entry and a routing address corresponding to the target virtual network interface card, determining a target gateway of said data (203); and if there is no target association table entry including the protocol address in the preset association flow table, on the basis of the protocol address of the target virtual network interface card and the routing address of the target virtual network interface card, determining the target gateway of said data (204).