331 results about "Software-defined networking" patented technology

The embodiment of the invention provides a security authentication method, device and system for a test platform, and a storage medium, and relates to the technical field of network security. The method comprises the following steps: performing fingerprint acquisition on virtual and real equipment to generate a unique identifier, dynamically slicing based on a software defined network to form an isolated test environment, and injecting a zero-trust access strategy associated with the fingerprint; and based on the zero-trust access policy and the device fingerprint, allocating a minimum permission through an attribute-based access control model, continuously evaluating device behaviors to calculate a dynamic trust score, and adaptively updating the permission according to the trust score. By constructing a full-process security certification system and through multi-dimensional mechanism cooperation, dynamic risk perception and timely strategy adjustment, fine-grained control of virtual and real equipment access in an industrial control scene is realized, the dynamic adaptability and risk resistance of a test platform in a complex network environment are improved, and the test efficiency is improved. Equipment access safety, authority distribution minimization and behavior monitoring continuity are ensured, and the safety risk of the industrial control system is reduced.

The invention relates to the technical field of power distribution station supervision, in particular to an intelligent auxiliary and artificial intelligence visual gateway control method and system for a station building, which monitors network state parameters in real time, calculates a network quality score and dynamically selects an optimal transmission path based on a reinforcement learning algorithm. Comprising a high bandwidth mode, a low delay mode and a disaster recovery backup mode, stage processing and dynamic compression are performed on transmission data according to data types and network quality scores, link switching and a local caching mechanism are automatically triggered when a network is abnormal, and finally, multi-gateway load balancing and visual monitoring are realized through a software defined network architecture. The problem of transmission delay or interruption caused by the fact that a static data transmission framework cannot adapt to network state changes in the prior art is effectively solved, and the reliability and the real-time performance of data transmission are remarkably improved through dynamic path optimization, intelligent hierarchical transmission and a fault self-healing mechanism.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, perform certain acts. The acts can include generating a digital twin network simulation of a physical computer network controlled through a software-defined-network (SDN) control system. The acts also can include training a routing agent model on the digital twin network simulation using a reinforcement-learning model on traffic that flows through nodes of the digital twin network simulation. The routing agent model includes a machine-learning model. The acts additionally can include deploying the routing agent model, as trained, from the digital twin network simulation to the SDN control system of the physical computer network. Other embodiments are described.

The invention discloses a road roller construction quality real-time monitoring system based on digital twinning, and relates to the technical field of road roller construction intelligent monitoring, and the road roller construction quality real-time monitoring system comprises a data acquisition module which uses a multi-modal fusion sensor network and edge calculation to comprehensively acquire and preprocess data; the digital twinborn model building module is used for modeling by combining physical-data dual drive with geological characteristics; the data transmission module is used for ensuring efficient and safe transmission by using a software defined network and a block chain; the real-time monitoring and analysis module is used for carrying out multi-scale space-time correlation analysis and generating virtual data; and the decision support module fuses deep reinforcement learning and a knowledge graph, supports man-machine cooperation decision, and provides intelligent suggestions for construction. According to the invention, the advantages are obvious, multi-modal acquisition and edge calculation ensure accurate and real-time data, a dual-drive model truly simulates construction, an advanced transmission technology ensures data safety, multi-scale analysis comprehensively evaluates quality, full-process coverage improves construction quality and management intelligence, and cost reduction and efficiency improvement are realized.

The embodiment of the invention provides a distributed medical equipment management platform and method based on a zero-trust network. In the distributed medical equipment management platform based on the zero-trust network, an edge trusted access module adopts a hardware root of trust mechanism, so that equipment accessed for the first time is connected to a temporary supply network isolated from a medical core network, and a zero-trust security normal form is followed; the distributed trust anchor point cluster constructs a distributed identity verification network based on federated learning, and the access pre-authorization authority is verified through a device distributed identity identification (DID); the dynamic permission arrangement engine injects an attribute-based access control strategy, generates a permission token in combination with network micro-segmentation, and realizes two-way encryption communication between the equipment and a target service; the intelligent isolation gateway cuts off temporary connection through a software defined network technology and sends a network access state proof through a block chain mechanism, and edge module initialization is executed by a trusted node outside the medical cloud.

The invention discloses a welding process parameter intelligent optimization system based on digital twinning, which relates to the technical field of welding intelligent manufacturing and comprises a plurality of modules, a data holographic acquisition module, a multi-modal sensor array, an advanced algorithm for noise reduction to obtain accurate data, a digital twinning model building module, a digital twinning model building module, a digital twinning model building module, a digital twinning model building module and a digital twinning model building module, a digital twinning model building module and a digital twinning model building module. In combination with a multi-physics field coupling equation and a microstructure evolution model, deep simulation is realized, a data transmission synchronization module uses terahertz and software to define a network fusion architecture, the transmission quantity is reduced through edge federation transfer learning, data consistency is ensured by dual mechanisms, an optimization algorithm fusion module fuses multiple algorithms, and the data transmission efficiency is improved. The parameter adjustment feedback module updates the model in real time according to feedback by means of multi-agent cooperation and fuzzy prediction control. By means of digital twinning, the welding process is comprehensively monitored and accurately simulated, parameters are intelligently optimized, the welding quality stability is improved, the production efficiency is improved, the frontier technology is fused, and intelligent development of the welding industry is promoted.

The invention relates to the technical field of Internet of Things communication transmission, and discloses an Internet of Things data intelligent transmission method and system, and the method comprises the steps: abstracting the performance of a multi-source heterogeneous link through a software defined network controller, dynamically generating a slice template, carrying out the traffic marking and priority scheduling, constructing a multi-path target constraint optimization model, and carrying out the optimization of the multi-path target constraint optimization model. And in combination with a network function virtualization mechanism, multi-level intelligent transmission is implemented at edge nodes, and a final transmission control instruction is generated. In the prior art, in a heterogeneous multi-network environment, low-delay, high-reliability and high-bandwidth transmission cannot be guaranteed at the same time, and especially in an industrial automation scene, technical problems that a control instruction is easy to delay and a monitoring data bandwidth is limited exist. According to the invention, the overall transmission reliability and bandwidth utilization efficiency are improved through the dynamic priority traffic scheduling based on network slices, the multipath reliability product model and the dynamic batch processing and progressive compression technology based on real-time link feedback.

The invention provides a collaborative data migration scheduling method based on topology awareness and deep reinforcement learning, and the method comprises the steps: initializing system configuration, constructing a weighted graph comprising a source server, a working machine, a target storage and network equipment, carrying out the embedded processing of a graph structure through a graph neural network, and generating a node and a path representation vector; in combination with source data, a working machine and a target storage state, constructing a system state vector, inputting the system state vector into a deep reinforcement learning agent for decision making, and outputting a composite action including data block selection, working machine selection, path indexing and migration rate suggestion; the network control module converts path information into flow rules, the flow rules are issued and executed through the software defined network controller, the task management module continuously monitors the migration state and processes failed data blocks, and the integrity and non-repeatability of migration tasks are ensured. According to the method, the defects of an existing data migration system in the aspects of task allocation, path selection, resource control and dynamic adaptability can be overcome.

The invention relates to the technical field of smart home, and discloses a gateway configuration method, system and equipment, and the method comprises the steps: obtaining a gateway connection request from the equipment, and transmitting the identification information and load information of a physical gateway to the equipment; if an access request of the equipment is received, whether the equipment is legal is verified, if the equipment is legal, a target virtual gateway corresponding to the equipment is determined based on the position information, contained in the access request, of a logic partition where the equipment is located, and an access success reply is sent to the equipment based on a physical gateway, and the physical gateway is configured to bear a plurality of virtual gateways; and performing logical partitioning of the virtual gateway based on the software defined network. According to the invention, cooperative work and reliable disaster recovery of multiple gateways in the smart home system are realized, and a flexible, efficient and reliable solution is provided for smart home application in scenes of multi-floor villas and the like.

The invention relates to the technical field of network communication and intelligent optimization, in particular to a multi-mode network global routing optimization method and device, electronic equipment and a medium. Comprising the following steps: constructing a data plane and a control plane according to a hierarchical structure of the software defined network, performing multi-modal analysis on an actual network topology of the data plane according to a modal type supported by a switch, and dividing the actual network topology into logic subnets of different modals based on a multi-modal analysis result; generating a set of N paths satisfying a preset condition between the source switch and the destination switch by using a preset path searching algorithm based on a network topology relationship between the logic subnets of different modalities; and based on the N path sets and the global controller of the control plane, generating a global route of the multi-modal network by using a preset global strategy model. Therefore, the problems that a traditional network optimization method is insufficient in collaboration and low in global characteristic utilization rate in a multi-domain data environment are solved, and the network transmission efficiency and the cross-domain collaboration capability are improved.

The invention provides a flow control method based on a software-defined network, which belongs to the technical field of data processing, and comprises the following steps of: 1, acquiring port data and link data of a switch in the software-defined network, and determining a network topology structure; 2, acquiring real-time flow data in the software defined network, and analyzing a network topology structure and the real-time flow data to determine adjustment path data; 3, determining a traffic adjustment strategy and a traffic forwarding rule based on the network topology structure and the adjustment path data; and step 4, executing the flow forwarding rule to realize the flow control of the software defined network. The method can deal with sudden flow fluctuation and link faults in the network and quickly respond, automatically optimize flow distribution and route selection, improve the bandwidth utilization rate and resource utilization rate of the network, reduce congestion and delay, adapt to a complex flow mode and a high-load and time-varying network environment, and improve the flexibility, reliability and efficiency of the network.

A method for deep packet inspection (DPI) in a software defined network (SDN). The method includes configuring a plurality of network nodes operable in the SDN with at least one probe instruction; receiving from a network node a first packet of a flow, the first packet matches the at least one probe instruction and includes a first sequence number; receiving from a network node a second packet of the flow, the second packet matches the at least one probe instruction and includes a second sequence number, the second packet is a response of the first packet; computing a mask value respective of at least the first and second sequence numbers indicating which bytes to be mirrored from subsequent packets belonging to the same flow; generating at least one mirror instruction based on at least the mask value; and configuring the plurality of network nodes with at least one mirror instruction.

A method for detecting network attack based on kernel operating characteristics of a software switch, comprising: collecting kernel operating characteristic data of the software switch during network management and packet forwarding of the software switch, wherein the kernel operating characteristic data of the software switch can reflect characteristic data of a fine-grained operating state of a network; preprocessing the kernel operating characteristic data of the software switch; and inputting the preprocessed kernel operating characteristic data of the software switch into a pre-trained attack detection model to detect a potential attack behavior in a network. The method is applicable to all scenarios where the software switch is applicable, especially a software-defined network and a cloud data center, an industrial Internet, 5G, edge computing based on the software-defined network. More accurate and timely detection and early warning of potential anomalies and attack behaviors in the network can be implemented.

A technique for determining security attacks in wireless communication systems is disclosed. A method implementation of the technique is performed by a controller and includes obtaining a first statistics based on an amount of messages received from at least one packet forwarding entity within a pre-defined time interval, t, wherein the first statistics is a time-domain data; obtaining a second statistics based on at least one arriving-time difference, Td, between two consecutive messages; detecting an anomaly based on the second statistics; determining, if the anomaly is detected, a security attack based on the first statistics; and initiating a security attack notification to an orchestrator.

The present disclosure relates generally to an SDN providing DNS resolution for a non-SDN service. In particular, the SDN hosts a first endpoint communicatively coupled with the non-SDN service. The SDN also hosts a DNS proxy in support of a second private network of a customer. A second endpoint of the customer can be accessible via the second private network The non-SDN service can send a DNS resolution request (that includes, for example, an FQDN of the second endpoint) to the first endpoint. The first endpoint forwards this request to the DNS proxy. In turn, the DNS proxy determines the IP address of the second endpoint and returns a reserved IP address corresponding to the DNS proxy and mapped to the second endpoint's IP address. The first endpoint sends this DNS resolution to the non-SDN service that then learns that the FQDN is resolved to the reserved IP address.

The invention discloses a method for automatically inspecting equipment in intelligent manufacturing, which comprises the following steps of: 1, deploying edge computing nodes, combining with 5G network slices, cleaning and compressing inspection data in real time, dividing priorities, performing low-delay transmission on key data through a special bandwidth, and locally caching or filtering non-key data; 2, developing a controller based on the software defined network, monitoring a link state, introducing a reinforcement learning algorithm, and dynamically optimizing a transmission path; 3, deploying a TinyML framework at an equipment end, integrating a model compression technology to operate a lightweight AI model, and combining sensor data to perform real-time early warning and support offline analysis; 4, constructing an incremental learning framework, dynamically updating model parameters through knowledge distillation, and only adjusting part of parameters to adapt to state change; and step 5, an analysis result is fed back to the system by using a message queue, and a patrol strategy is dynamically adjusted in combination with a rule engine to form a closed-loop optimization mechanism of data acquisition-transmission-analysis-decision.

In communication with components of a cloud platform, namely a software-defined network constructed to overlay at least one public cloud network, a controller features a virtual processor and a data store. The data store includes network address translation (NAT) processing logic configured to determine whether a control plane message from tenant resources is associated with a network address overlapping condition, which represents a first network address included in the control plane message overlaps a network address range relied upon by either (a) at least one of the components of the cloud platform or (b) a component associated with other tenant resources. The NAT processing logic is further configured to alter routing data stores that maintain routing information for each of the components of the cloud platform to substitute the first network address with a first virtual network address for subsequent data message routing.

The invention discloses a dynamic optimization method for an intelligent security convergence protection strategy of a power system, and belongs to the technical field of power system security protection. According to the method, a'perception-evaluation-decision-execution 'four-layer dynamic optimization framework is constructed; a perception layer collects multi-source data at a sampling rate greater than or equal to 1kHz through a lightweight edge agent, and the multi-source data is fused through an adversarial generative network; the evaluation layer evaluates threats by using an improved space-time diagram convolutional network in combination with a dynamic threat index; the decision-making layer introduces a depth deterministic strategy gradient algorithm to generate a protection strategy; and the execution layer deploys and feeds back a result through a software defined network. The problems of static defense, data splitting, insufficient real-time performance and the like in the traditional technology are solved. Simulation verification shows that the attack detection rate is increased to 98.7%, the strategy optimization time consumption is shortened to 457ms, the energy loss is reduced by 19.8%, and the safety protection level of the power system is effectively improved.

An automated system provides end-to-end (E2E) orchestration for machine learning (ML)-enabled and software-defined network (SDN)-enabled reactive and predictive (e.g., 5G) cell-on-drone (COD) dispatch and deployment. The system may be configured to detect or predict traffic surges (e.g., relative to typical or baseline levels) in a given cell site and orchestrate provisioning of resources, including COD deployment, to address the surge. COD deployment may involve one or more clusters or colonies of drones equipped with low-powered cellular radio access (or small cell) nodes, where each cluster includes (or is led by) one or more SDN-equipped drones that provide intelligent SDN-on-drone (SOD) functionality.

The present application provides a network configuration information processing method. For the process of virtual machine live migration, a function of delaying deletion of a virtual machine on an original node computer is realized on the network control plane, so that when a node in the network system sends a message for accessing the live migration virtual machine, even if the node does not refresh the corresponding relationship between the live migration virtual machine and the destination node computer, the message for accessing the live migration virtual machine can still be sent to the original node computer for relaying or processing, and the packet loss probability of the message for accessing the live migration virtual machine can be reduced in the process of virtual machine live migration and within a certain period after the virtual machine live migration is completed.

The invention discloses a software-defined satellite network load balancing routing algorithm, belongs to the technical field of software-defined satellite network load balancing routing algorithms, and constructs a satellite network architecture based on an SDN, applies a software-defined network technology to a satellite network, and sets SDN controllers at a ground station or a plurality of different geographic positions. The controller is used for managing control functions of a satellite network, including regional division of the network according to satellite orbit position, coverage range and service requirements, unified or collaborative management of resource allocation and routing strategies of each region, stage division of services in the satellite network, and management of the services in the satellite network. According to different requirements of the services for time delay, bandwidth and time delay jitter QoS indexes, the services are divided into different levels which at least comprise high-level services and common-level services, and higher priority guarantee is set for the high-level services.

The present application relates to the technical field of network security. Disclosed are a software-defined-network-based cloud-edge collaborative defense system and method for unknown attacks. The system comprises a main station deployed at a cloud end and a plurality of edge stations deployed at an edge end. A software defined security platform comprises a main controller, a security controller and a security component resource pool. Any one of the edge stations comprises an edge controller. The security controller is configured to receive network security information uploaded by the main controller and / or any one of the edge controllers, identify an unknown attack on the basis of the network security information, generate a corresponding defense strategy and issue the defense strategy to the security component resource pool, the main controller and / or any one of the edge controllers. The security component resource pool is configured to virtualize a security protection function into a security component, and configure the main station and / or any one of the edge stations with the security component on the basis of the network security information or the defense strategy. The problem of traditional static and rigid defense measures and strategies being unable to meet the requirements for defending against unknown attacks is solved.

The invention provides a communication method based on a dynamic satellite network and a controller. The method is applied to a centralized controller for controlling a dynamic satellite network of a target geographic area, the dynamic satellite network is composed of a plurality of satellites in the target geographic area, and the dynamic satellite network realizes communication management by adopting a software defined network architecture. The communication method comprises the following steps: generating a geographic topology network intention corresponding to a target geographic area according to a network communication requirement in the target geographic area; obtaining the state information of each satellite in the dynamic satellite network in the current time slice, and predicting the network state of each satellite in the next time slice according to the state information; determining the network topology of the dynamic satellite network in the next time slice according to the geographic topology network intention and the network state; and controlling data transmission of the dynamic satellite network in the next time slice according to the network topology. According to the invention, the reliability of the communication mode based on the dynamic satellite network can be obviously improved.

A software-defined network controller includes at least one processor and memory storing computer-executable instructions coupled to the at least one processor. The at least one processor is configured to execute the computer-executable instructions to cause the software-defined network controller to monitor performance characteristics of a machine learning trust manager, and evaluate the performance characteristics to determine whether the machine learning trust manager satisfies a performance threshold. In response to determining that the machine learning trust manager fails to satisfy the performance threshold, the processor deactivates the machine learning trust manager, and activates a deterministic trust manager in place of the machine learning trust manager.

Techniques are disclosed for processing data packets and implementing policies in a software defined network (SDN) of a virtual computing environment. At least one network device is configured to disaggregate enforcement of policies of the SDN from hosts of the virtual computing environment. Tier-0 devices are communicatively coupled to network interfaces of the network device. The network device comprises a plurality of data processing units that are configured to implement functionality of the network device.

The invention discloses a gray scale test method of a cloud mobile phone server and related equipment, and relates to the technical field of cloud computing, and the method comprises the steps: obtaining a file system of an old version server and a file system of a new version server; based on the file system of the old-version server and the file system of the new-version server, performing difference analysis, and generating an incremental snapshot file; selecting a part of nodes in the server cluster to load the incremental snapshot file, and constructing a gray scale test environment; distributing the user request to a gray level test environment and a stable environment according to a preset distribution proportion through the software defined network; and collecting performance indexes of the gray test environment in real time, triggering a rollback mechanism when detecting that the performance indexes of the gray test environment exceed a preset threshold value, unloading the incremental snapshot file, and switching the corresponding node to an old version.

The invention provides a self-adaptive data packet scheduling method based on approximate quantiles and multiple queues on a programmable data plane, and aims to solve the problem that the scheduling performance and the resource efficiency are difficult to balance in the prior art. According to the method, lightweight ranking scoring, dynamic queue mapping and a cascade enqueue strategy are combined. A relative priority score of the data packet is efficiently calculated through a minimum-maximum normalization mechanism; adaptively mapping the data packets to one of a plurality of FIFO queues according to the scores and real-time congestion conditions of the queues, and providing a fast channel for extremely high priority traffic; and when the target queue is full, trying to store the data packet into a queue with a lower priority in a cascading manner so as to avoid unnecessary discarding. According to the method, resource consumption and implementation complexity are remarkably reduced while the approximate ideal PIFO scheduling performance is achieved, and the method is particularly suitable for resource-limited environments such as a software-defined network and edge computing.

Embodiments are described for a method and system of applying data protection software mechanisms to network devices to auto-discover the networking equipment, save changes from memory (TCAM) to local storage, backup changes to protection storage, provide auditing and tracking history of changes, and provide the ability to deploy test / development copies of changes using software defined networking techniques. A coordinator protects network devices organized into a plurality of partitions by creating a backup of each network device, pushing backup policies to individual data protection units for the network devices within each partition to provide a consistent-state backup of the network devices, and backing up the configuration changes of the network devices to a protection storage device.

The invention belongs to the field of network communication, and provides a network fault automatic processing method and system, and the method comprises the steps: collecting a multi-source monitoring signal, and constructing a space-time matrix used for representing a network state; training the decision tree model by using a reinforcement learning algorithm, and constructing a reward function according to the root cause positioning accuracy and the repair effect; when the decision tree model determines a fault root cause, calling a software defined network (SDN) controller interface, generating a corresponding rerouting strategy according to the fault root cause, and issuing the rerouting strategy to network equipment for path adjustment; applying the rerouting strategy in a simulation environment, collecting QoS (Quality of Service) indexes before and after adjustment, and verifying the validity of a repair strategy; and feeding back a repair verification result to a training process of the decision tree model, and updating parameters of the reinforcement learning algorithm. According to the invention, the accuracy of network fault automatic processing can be improved.

The present invention relates to the technical field of communications, and provides a 6G space-air-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration, comprising: three tiers of cloud nodes from low to high: an edge cloud, a space-based cloud, and a core cloud; the edge cloud comprises 6G-enabled ships based on software-defined networking and mobile edge computing technologies; the space-based cloud comprises low earth orbit satellites based on software-defined satellite technology and low earth orbit satellite constellations connected by means of an inter-satellite link; the core cloud comprises a space-based 6G core network; the edge cloud, the space-based cloud, and the core cloud follow a task offloading mechanism and an information feedback mechanism; the task offloading mechanism is configured to select, on the basis of characteristics of a task, a cloud node of a target tier for task processing; and the information feedback mechanism is configured such that the cloud node of the upper tier sends feedback information to a cloud node of the lower tier, so as to optimize task processing of the lower tier. The present invention achieves fast and flexible networking for a 6G space-air-ground-sea integrated fusion network, thereby realizing efficient utilization and collaborative management and control of resources.