259 results about "Cloud networking" patented technology

The invention relates to the technical field of computer vision, and discloses a jade defect intelligent detection method and system based on machine vision and deep learning, and the method comprises the following steps: S1, based on a high-resolution industrial camera and a laser three-dimensional scanner, adopting a multi-mode synchronous collection strategy, and rotating a jade sample through a precise motion control system, a jade surface high-resolution two-dimensional color image and high-precision three-dimensional point cloud data are respectively obtained, and a jade multi-mode original data set is generated. A high-resolution two-dimensional color image and high-precision three-dimensional point cloud data are integrated through a multi-modal synchronous acquisition strategy, and multi-dimensional feature expression under unified coordinates is constructed, so that the limitation of a single data source is effectively overcome; an image registration algorithm and a feature pyramid network are combined with a point cloud network to perform multi-modal feature fusion, complementarity of color texture and geometric morphology information is enhanced, and image quality is optimized based on adaptive histogram equalization and non-local mean filtering.

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. A first AI agent associated with a first entity obtains a machine-readable data structure defining one or more operative boundaries for a second AI agent associated with a second entity. The system generates a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set, and transmits the unique fixed reference value to a multi-agent storage to store the value. The system receives, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value based on internal operational data of the second AI agent corresponding to the operative boundaries. The first AI agent determines a verification status of the verification artifact by comparing the unique fixed reference value with the observed value, and autonomously generates a verification record including a representation of the verification status.

The invention discloses a crop harvesting progress monitoring method and system based on multi-source remote sensing data fusion and depth time sequence analysis, and the method comprises the steps: obtaining multi-source remote sensing image data of a to-be-monitored region, carrying out the standardization processing of the multi-source remote sensing image data, and obtaining the processed remote sensing image data; constructing a fusion cloud removal network, and performing fusion cloud removal on the processed remote sensing image data to obtain cloudless image data; performing space-time fusion on the cloudless image data by using an enhanced space-time adaptive reflectivity fusion model to obtain a continuous cloudless optical image sequence; constructing a depth time sequence classification model based on a convolutional neural network and a long-short term memory network, and inputting the continuous cloudless optical image sequence into the depth time sequence classification model to obtain a crop harvesting monitoring result; and performing spatial superposition on the crop harvesting monitoring result and the field piece vector boundary data of the to-be-monitored area to obtain a harvesting progress diagram of the to-be-monitored area.

The invention discloses a disaster recovery resource scheduling method and device based on a heterogeneous cloud environment, and the method comprises the steps: constructing a multi-dimensional resource portrait model and a cross-cloud network topological graph in the heterogeneous cloud environment, and generating a standardized resource vector set and a topological affinity scoring matrix; aggregating the local SLA default risk prediction model of each cloud node through federated learning, and performing fine tuning through transfer learning to obtain a global prediction model; calculating load fluctuation entropy based on the SLA constraint template and real-time load data, and inputting the load fluctuation entropy into a global model to predict and obtain an SLA default probability set; constructing and solving a dynamic weight multi-objective optimization function to obtain an optimal takeover cloud node list and a migration strategy identifier set; a target cloud node and a migration strategy are determined through SLA simulation verification, and an adaptive execution adapter is called to complete virtual machine incremental snapshot migration or cross-cloud arrangement deployment of containerized services. According to the invention, intelligent and automatic scheduling of disaster recovery resources is realized, and the fault takeover speed and the cross-cloud resource utilization rate are improved.

A computer implemented method for managing and remediating security drift in a public cloud network is disclosed. A security drift event may be received at a contextual impact classification engine of a server. An impact tier for the received security drift event may be assigned at the contextual impact classification engine. A queue shaping orchestrator at the server may reorder a queue with entries that include the received security drift event based on the assigned impact tier. A remediation engine of the server may determine a remediation for the received security drift event based on the assigned impact tier, and / or one or more contextual inputs received by the server.

A system featuring a controller and a plurality of nodes operating as a Kubernetes cluster. The plurality of nodes includes a master node communicatively coupled to the controller, and an ingress node being configured to (i) access the master node to obtain at least a first attribute associated with a data flow received by the ingress node based on a network address associated with a source of the data flow, (ii) determine one or more network policies applicable to the data flow based on at least the first attribute, and (iii) determine a classification identifier based on the one or more network policies. The classification identifier provides context associated with the data flow and a reliable association between an application and the data flow associated with the application during propagation of the data flow over a cloud network.

The invention discloses a cross-virtual private cloud network scheduling method based on a cloud computing infrastructure, a cross-virtual private cloud network scheduling system based on the cloud computing infrastructure, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining network configuration information of a virtual private cloud; establishing a cross-virtual private cloud access channel according to the network configuration information, wherein the access channel comprises a peer-to-peer connection channel and a terminal node channel; configuring an address translation rule and a routing rule for the access channel; and carrying out forwarding and access control on the network access flow among the applications and / or the computing resources in the virtual private cloud according to an address conversion rule and a routing rule. Uniform configuration and dynamic management of the network access path are realized while independence of each virtual private cloud is kept, so that the access relationship across the virtual private cloud is clearer, configuration is more concentrated, operation and maintenance are more simplified, and interconnection flexibility and manageability in a cloud multi-network environment are improved.

The invention relates to the technical field of traffic information collection, in particular to a tunnel traffic flow detection method based on a video cloud networking technology, and the method comprises the following steps: obtaining video flow data collected by each monitoring camera in a tunnel in real time; performing compression coding processing on the video stream data; performing noise filtering and frame synchronization preprocessing on the coded video data; in a preset edge computing node, inputting the structured video data into a vehicle flow detection model to extract vehicle feature parameters in the video frame; performing tracking association on the target vehicle in the video frame through an asymmetric Kalman filtering algorithm, and comparing the vehicle flow detection data with a preset vehicle flow threshold; and in the cloud analysis platform, analyzing the structured detection data through the tunnel traffic flow prediction model. According to the invention, noise filtering and time-space alignment can be carried out on the collected vehicle operation video data, and the accuracy of tunnel traffic flow detection is improved.

This disclosure provides systems, methods and apparatus, including computer programs encoded on computer storage media, for centralized management cloud connecting multiple enterprise networks. A network agent may be deployed within a private cellular network and act as an interface between the node(s) of the private cellular network and a cloud network controller. The network agent may obtain a local-based request to initiate a cloud-based procedure associated with network parameter(s), the network parameter(s) being associated with cloud network credential(s) that correspond to the private cellular network. The network agent may output a cloud-based request to the cloud network controller to initiate the cloud-based procedure. The cloud-based request may indicate at least a portion of the network parameter(s) and omit at least a portion of local credential(s) of the private cellular network. The cloud-based request may hide the cloud network credentials of the private cellular network from the cloud network controller.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

A computing platform may train, using historical node performance information and historical application parameter information, a node selection model, which may configure the model to select nodes for application cloud deployment. The computing platform may receive a request to deploy an application to a cloud network. The computing platform may select a node, of the plurality of nodes of the cloud network, to which the application should be deployed. The computing platform may queue, along with other applications scheduled for deployment to the plurality of nodes, the application for deployment to the node. After identifying that the application is first in the queue, the computing platform may deploy the application to the node of the cloud network, which may create, at the node, a container corresponding to the application.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are off-line (or may potentially go off-line). For example, the systems and methods may mitigate issues related to providing services while resources are off-line (or may potentially go off-line) by monitoring network services at an aggregate level.

The invention provides a network traffic forwarding method and device, electronic equipment and a storage medium, and is applied to an intelligent network card, the method comprises the following steps: obtaining link quality information measured by the intelligent network card for a cross-cloud link; reporting the link quality information to a forwarding gateway in the cloud; receiving a path selection strategy issued by the forwarding gateway, the path selection strategy being generated by the forwarding gateway based on the link quality information and preset strategy information; and forwarding the network traffic according to the path selection strategy. Therefore, real-time perception of cross-cloud link quality and quick path selection based on real-time quality are realized, the problem of path selection strategy lag caused by the fact that detection and decision-making functions are concentrated on a control level in the background technology is fundamentally solved, and the quality and real-time performance of cross-cloud network transmission are remarkably improved.

The invention relates to a network unified monitoring and operation and maintenance management system in a multi-cloud environment, and belongs to the technical field of cloud computing and network operation and maintenance crossing. The system is characterized in that an intelligent perception and adaptation access module performs bidirectional communication with a heterogeneous cloud platform through a dynamic protocol adaptation engine, and an edge preprocessing unit completes data primary processing and security authentication; the data processing and analysis module constructs a stream batch integrated architecture, establishes a cross-cloud unified topology model by using a knowledge graph technology, and realizes multi-dimensional data analysis through a distributed time sequence database; the strategy generation and scheduling module performs strategy pre-verification, issues an operation and maintenance instruction through a transaction consistency mechanism, and establishes a closed-loop feedback loop to continuously optimize a decision; the unified operation and maintenance portal module integrates three-dimensional topology, visualizes security situations and operation and maintenance decisions, and provides fault traceability and strategy interaction capability. According to the invention, unified monitoring, intelligent analysis and automatic operation and maintenance of a multi-cloud network environment are realized.

Techniques for providing multi-operator core SASE solutions (e.g., for 5G SASE) are disclosed. In some embodiments, a system, a process, and / or a computer program product for providing multi-operator core SASE solutions for 5G SASE includes receiving mobile network traffic, at a Secure Access Service Edge (SASE) cloud network, via a service provider interconnect between a plurality of mobile service provider networks and the SASE cloud network; monitoring the mobile network traffic at the SASE cloud network from the plurality of mobile service provider networks for a tenant of the SASE cloud network provider; enforcing a security policy based on one or more parameters associated with the mobile network traffic, wherein the security policy is associated with the tenant of the SASE cloud network provider; and forwarding the secured data plane traffic from the SASE cloud network to its original destination if allowed by the security policy, and block or drop the data plane traffic from the SASE cloud network if not allowed by the security policy.

The invention discloses a water hammer eliminating device and method based on cloud network intelligent interconnection, and belongs to the technical field of fluid conveying system safety protection. Aiming at the problems of response lag, node isolation, lack of predictive ability and poor fault tolerance of a traditional water hammer elimination device, the invention provides an intelligent protection scheme fusing cloud edge collaboration and physical data hybrid modeling. The device comprises a distributed data acquisition module, a water hammer elimination execution module, an intelligent control module and a cloud platform, real-time fluid parameters are collected, pipe network topological information is combined, the action time sequence is calculated based on the pressure wave propagation speed and the node distance, and pre-action is started before pressure waves arrive; a physical simulation model and an LSTM data driving model are fused to predict the water hammer risk, the safety redundancy time and the execution strategy are dynamically adjusted, and local autonomy and fault tolerance under communication interruption are supported. Millisecond-level pre-action and multi-node cooperative pressure relief are achieved, the water hammer peak pressure is remarkably reduced, and the safety and the intelligent operation and maintenance level of a complex pipe network are improved.

The invention discloses a network access control method and electronic equipment, and relates to the technical field of computers, network resources and access strategies thereof are visually presented in a graphical user interface in a node and connecting line mode, logic conflict judgment and strategy optimization recommendation are synchronously completed when a user drags and generates the strategies, and the network access control method and the electronic equipment have the advantages that the user experience is improved, and the user experience is improved. The abstract configuration process originally depending on a command line or a rule form is converted into a visual and interactive operation process, so that the degree of dependence of network access strategy configuration on professional experience is reduced, the probability of occurrence of artificial configuration errors is reduced, potential risks are controlled in the strategy generation stage, and the strategy generation efficiency is improved. And the overall efficiency and security of private cloud network access policy management are improved.

A data exfiltration protection system that uses machine learning to analyze traffic between multiple end-user devices and multiple vendors. The data exfiltration protection system consists of a tenant using a vendor's application and an app connector transmitting traffic at an application layer of a cloud network. The data exfiltration protection system further consists of a machine learning module that monitors traffic for an event at the app connector and an alert generator. The machine learning module monitors traffic for the event at the application for a period, generates expected traffic behavior using historical logs, and generates forecasted traffic for the event for different periods of time in the future. The machine learning module further determines a difference between monitored traffic and forecasted traffic and flags the event as an anomalous dip when the difference is below a threshold. Finally, the alert generator notifies the tenant about remediation flags.

The invention provides a cloud network monitoring data acquisition method and device, a storage medium and a program product, and relates to the technical field of cloud computation.In the embodiment, damage time corresponding to a damaged monitoring index is determined in monitoring indexes obtained through calculation on the basis of operation data of cloud network equipment, and the damage time corresponding to the damaged monitoring index is determined; according to the method, the operation data corresponding to the damaged time is calculated again, and the monitoring indexes obtained through recalculation and the undamaged monitoring indexes are used as the monitoring data of the cloud network equipment to be sent to the user terminal, so that data missing caused by data damage is avoided, the accuracy of state judgment of the cloud network equipment can be improved, and the user experience is improved. And the stability of the cloud network service is improved. Moreover, the calculation is carried out based on the damage time, the calculation of total data is not needed, and the calculation resources can be saved on the premise of ensuring the accuracy of the calculation result.

Computer-implemented systems and methods provision a virtual machine sandbox for evaluating software. Firewall means are provisioned for a cloud network to permit access to an internet site from which source code is downloadable. A client computer device, via virtualization, controls a virtual machine. The client computer device is on an on-premises network that is different from, and in communication with, the cloud network. The virtual machine is controlled to: (a) download to the virtual machine, via the firewall means, the source code from the internet site; and (b) execute the source code for evaluation of the source code. The virtual machine is deleted after a predetermined time period. The source code is prohibited, after provisioning the virtual machine and through deletion of it, from being downloaded from the virtual machine to computer devices on the on-premises network.

The embodiment of the application provides a network communication architecture, a communication method, an electronic device and a storage medium, relates to the public cloud network technical field, and the network communication architecture comprises a public cloud computer room and a private cloud computer room in communication with the public cloud computer room; the public cloud computer room comprises an SDN controller, a first special line switch, a Spine switch, a Leaf switch and a first device; the private cloud computer room at least comprises a second special line switch, an access switch and a second device; a BGP EVPN session connection is established between the SDN controller and the access switch, the SDN controller is used for sending first routing information corresponding to the public cloud computer room to the private cloud computer room through the BGP EVPN session connection, and the access switch is used for sending second routing information corresponding to the private cloud computer room to the public cloud computer room through the BGP EVPN session connection.

Systems and methods for encrypting data between a customer and a virtual cloud network (VCN) for end-to-end encryption, where the customer manages the encryption keys.SOLUTION: The network head end device, VCN Head End 704, accepts the first key provisioned by the customer, receives the first data packet sent from the customer's device, and decrypts the first data packet using the first key to obtain the information. The network virtualization device 624 receives the information from the network head-end device, confirms that the information is to be sent to the virtual machine in the virtual cloud network, confirms that data in the virtual cloud network is to be encrypted, encrypts the information using the second key to generate a second data packet, and routes the second data packet to the virtual machine in the virtual cloud network 312.SELECTED DRAWING: Figure 7

A method of virtual network function (VNF) placement for mapping service function chain requests (SFCRs) includes, at the node mapping stage, receiving a SFCR including a plurality of virtual network function requests (VNFRs) from a user, ranking server nodes with initiated virtual machines (VMs) of a required type to obtain a first best-ranked server node, and placing a VNFR onto the first best-ranked server node; if the VNFR cannot be placed onto any server node in the server nodes with the initiated VMs, ranking server nodes without the initiated VMs of the required type to obtain a second best-ranked server node, initiating a new VM having a type same as the required type on the second best-ranked server node, and placing the VNFR onto the second best-ranked server node; and after placing the VNFR onto the first or second best-ranked server node, selecting a source node for video synchronization.

A network entity associated with the virtual cloud network is transitioned through a certificate packet distribution process for distributing a new certificate authority certificate to the network entity. The operations may include performing, with respect to each of the network entities, a first operation associated with a first stage of processing; for each particular network entity, obtaining individual entity information associated with the progress of the particular network entity with respect to the first phase; calculating an aggregation metric indicating an aggregation progress of the network entity with respect to the first phase based on the individual entity information; determining, based on the aggregation metric, that one or more transition criteria for transitioning the network entity from the first phase to a second phase of the processing are satisfied; and, with respect to each of the network entities, performing a second operation associated with the second stage of processing.

The invention relates to creating a secure, decentralized, cloud-based network or physical / virtual infrastructure that enables the payments industry to redefine payment processing and information sharing. The innovative network addresses key pain points by reducing payment delays and touch points, realizing faster and comprehensive payment tracking, real-time sanctions, AML and fraud management tools.

The application discloses a cloud network service level agreement guarantee system and method based on a distributed speed limiting strategy, wherein the distributed speed limiting strategy is realized through an equal packet loss rate control algorithm, and a core purpose of the equal packet loss rate control algorithm is to update a speed limiting value of each gateway node in a distributed speed limiting gateway cluster when each round time is exhausted; the guarantee system comprises a management module and a routing module; the management module is used for starting, monitoring and configuring the distributed speed limiting gateway cluster based on the distributed speed limiting strategy; and the routing module is used for forwarding data packets in a cloud network and performing bandwidth speed limiting based on the distributed speed limiting strategy in the forwarding process. The system and method utilize the distributed speed limiting strategy, realize cloud network service level agreement guarantee, and are favorable for improving cloud network service quality.

The systems and methods disclosed herein provide for coalescing data packets into jumbo frames in order to maximize the throughputs inside the service provider Local Area Network (LAN), thereby increasing the amount of traffic forwarded between internal services. The systems and methods outlined herein enable a source service on a LAN to receive a plurality of data packets from a public cloud-based network (e.g., the Internet) having a packet size limit less than the MTU limit of the LAN, and coalesce the plurality of data packets into a jumbo frame having a size based on the MTU limit of the LAN. The jumbo frame is then transmitted over the LAN to a destination service on the LAN. The destination service then separates the jumbo frame back into the plurality of data packets for further transmission back to the public cloud-based network.

Techniques for providing language localization for traffic egressing from a distributed Service Access Service Edge (SASE) infrastructure are disclosed. In some embodiments, a system, a process, and / or a computer program product for providing client IP persistence for traffic egressing from a distributed SASE infrastructure includes receiving traffic associated with a user application (app) session at a Secure Access Service Edge (SASE) cloud network via a proxy node; processing the traffic associated with the user app session using a security processing node (SPN), and wherein a source network address translation (SNAT) rule is configured for the SPN; and egressing the traffic associated with the user app session from the SASE cloud network to its original destination using a fixed public IP address based on the SNAT rule to facilitate language localization for all network connections associated with the user app session.

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. A first AI agent associated with a first entity obtains a machine-readable data structure defining one or more operative boundaries for a second AI agent associated with a second entity. The system generates a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set, and transmits the unique fixed reference value to a multi-agent storage to store the value. The system receives, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value based on internal operational data of the second AI agent corresponding to the operative boundaries. The first AI agent determines a verification status of the verification artifact by comparing the unique fixed reference value with the observed value, and autonomously generates a verification record including a representation of the verification status.

A disclosed method of operating an emergency data management system includes: obtaining emergency data related to an emergency call to an emergency communication center (ECC) by a cloud server of the emergency data management system independent from the ECC; obtaining an address for the emergency call via a connectivity device located at the ECC, where the connectivity device is operatively coupled to the cloud server; matching the address to an ECC computer-aided-dispatch (CAD) system incident record address; and sending the emergency data to the ECC CAD system incident record corresponding to the matched CAD system incident record address.