537 results about "Cloud networking" patented technology

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 relates to an intelligent equipment access system and access method based on an AI large model, and relates to the field of artificial intelligence and Internet of Things. According to the technical scheme, a dynamically adaptive universal object model access framework is constructed, functional attributes, control instructions and data formats of intelligent devices of different brands and protocols are mapped into a standardized logic model, meanwhile, a multi-mode AI large model engine is combined, high-precision voice recognition, voiceprint feature detection and multi-level semantic intention analysis capabilities are integrated, and the intelligent devices of different brands and protocols can be obtained. And an intelligent interaction closed loop of end-cloud collaboration is formed. Semantic analysis adopts a mixed strategy, a natural language instruction is converted through function mapping, a local knowledge base is utilized to match user scene requirements, and external data is queried by means of cloud networking to optimize instruction logic. According to the scheme, the multi-device access and operation and maintenance cost is remarkably reduced, the semantic understanding accuracy and scene adaptability are improved, and the method is widely applied to the fields of smart home, smart medical treatment and industrial Internet of Things.

A multi-cloud overlay network for supporting communications between a first public cloud network and a second public cloud network. The overlay network features a management virtual private network, which includes a network load balancing (NLB) component and a controller registered as a target on a port of the NLB component. The overlay network further includes one or more spoke or transit gateways and a multi-cloud access virtual private cloud (VPC) operating within the first public cloud network, and a remote cloud load balancer component operating the second public cloud network. The remote cloud load balancer component is communicatively coupled between the multi-cloud access VPC and one or more remote spoke or transit gateways. The multi-cloud access VPC includes a VPC endpoint that is assigned a private IP address and communicatively coupled to the NLB component and a virtual private network (VPN) gateway communicatively coupled to a private transport.

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.

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.

Disclosed are systems, apparatuses, methods, and computer-readable media for inventory monitoring in a multi-cloud network environment. A method includes receiving user input via a controller's interface, wherein the input includes first account information granting access to a first virtual private cloud and a second virtual private cloud, both hosted by a cloud service provider (CSP). The controller queries the first and second virtual private clouds using the respective account information and the CSP's APIs to identify resources, gathering them into an inventory, and maintains a mapping of tags to the resources, associating each tag with a specific security policy. The controller forwards a first subset of tag-resource mappings to a first security gateway in the first virtual private cloud, enabling automatic application of corresponding security policies upon instantiation of tagged resources.

Techniques for facilitating connectivity to vPLCs created in a CSP-provided infrastructure in a region. Within the CSP-provided infrastructure in a region, when the destination of a packet is determined to be an endpoint associated with a particular vPLC, the packet is tagged with information related to the particular vPLC. The vPLC-related information for the particular vPLC can include, for example, a vPLC identifier identifying the particular vPLC, an identifier identifying a customer associated with the endpoint, a virtual cloud network identifier identifying a virtual cloud network (VCN) belonging to the particular vPLC and where the endpoint is part of the VCN, and other vPLC-related information. The packet is then routed or communicated within the CSP-provided infrastructure in a region along with the tagged vPLC-related information. The vPLC-related information is used as part of the connectivity and for routing of packets within the CSP-provided infrastructure in a region.

The invention provides a reliability-aware dependent task unloading method based on topology reconstruction in industrial internet edge computing, which comprises the following steps of: constructing a system model covering an edge cloud network platform, an industrial cloud platform and internet of things equipment, and establishing a transmission delay model and a reliability model; constructing a task unloading mathematical model with the maximum reliability level; the method comprises the following steps: modeling a micro-service dependency relationship into a weighted directed acyclic graph based on a network flow theory, and carrying out topology reconstruction on micro-services applied to the Internet of Things through a Ford-Fulkerson approximation algorithm to obtain a micro-service grouping structure formed by minimum cut division; the micro-service grouping structure serves as priori knowledge to be input into the deep Q network, the deep Q network is used for solving a task unloading mathematical model, a task unloading strategy is dynamically adjusted, resource allocation is optimized, and an optimal calculation unloading scheme in the industrial internet edge calculation environment is obtained. The micro-service deployment is optimized, the communication overhead is reduced, and the system reliability and the resource utilization rate are improved through real-time network state dynamic decision making.

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 described embodiments set forth techniques for transferring cellular wireless service from a source wireless device to a target wireless device with multi-factor authentication and consent of a mobile network operator (MNO) account owner of a multi-user MNO account that includes one or more MNO account members. Terms and conditions for transfer of the cellular wireless service can be presented via a native operating system user interface of a wireless device of the MNO account owner. When the target wireless device belongs to an MNO account member, the MNO account owner wireless device facilitates transfer of the cellular wireless service by allowing the MNO account owner to review terms and conditions and provide one-time passcode authentication to the target wireless device. An original equipment manufacturer (OEM) cloud network service can be used for transfer of terms and conditions information and / or the one-time passcode.

Techniques for providing explicit proxy solutions for 5G Service Access Service Edge (SASE) with service provider network attach are disclosed. In some embodiments, a system, a process, and / or a computer program product for providing explicit proxy solutions for 5G SASE with service provider network attach includes receiving data plane traffic associated with a User Equipment (UE) from a mobile core network at a Secure Access Service Edge (SASE) cloud network via a service provider network attach using an interconnect between the mobile core network and the SASE cloud network; enforcing a security policy on data plane traffic associated with the UE based on contextual information associated with the UE to provide secured data plane traffic using the security policy configured per user group and / or per user; and forwarding the secured data plane traffic from the SASE cloud network to its original destination if allowed by the security policy, and blocking or dropping the data plane traffic from the SASE cloud network if not allowed by the security policy.

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.

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.

Techniques are described for routing traffic through an interconnect cloud gateway based on cloud traffic routing indicators. The interconnect cloud gateway can advertise the cloud traffic routing indicators, which can include cloud indicators and transport gateway indicators. The cloud indicators can include cloud tags utilized to route cloud traffic. The transport gateway indicators can include transport gateway flags utilized to identify private networks utilized to route the cloud traffic. The cloud traffic can routed during normal private network operation through private networks, which can be dynamically replaced by public networks due to occurrences of failures preventing the data traffic from being routed through the private networks and to cloud networks.

Techniques for a container orchestration system are disclosed. A virtual agent may be executed in a first service tenancy of a cloud network manager. The virtual agent may be executed on a virtual node of a container orchestration system. A container orchestration API server may be executed in a second service tenancy of the cloud network manager. A request from the container orchestration API server to the virtual agent may be routed through a customer tenancy of a customer of the cloud network manager.

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.

Techniques for leveraging the MASQUE protocol to provide remote clients with full application access to private enterprise resources are described herein. One or more network nodes may be configured to execute a MASQUE proxy service to provide a remote client device with full access to an enterprise / private application resource executing on an application node and hosted in an enterprise / application network, behind the MASQUE proxy service. In some examples, the MASQUE proxy service may execute on a single proxy node hosted at an edge of a cloud network or at an edge of an enterprise network. Additionally, or alternatively, a first instance of the MASQUE proxy service may execute on a first proxy node hosted at an edge of a cloud network (e.g., an ingress proxy node) and a second instance of the MASQUE proxy service may execute on a second proxy node hosted at an edge of the enterprise network.

Various arrangements of a hybrid cellular network system are detailed herein. The system can include a cellular radio access network (RAN) comprising a plurality of base stations (BSs). Each BS can include an antenna, a physical router; a radio units (RU), and a distributed unit (DU). The system can include multiple pass-through edge data centers (P-EDCs). Each P-EDC is in communication with a different subset of BSs. The system can include an aggregation data center (ADC) in communication with the P-EDCs. The system can further include a breakout edge data center (EDC) executed at an EDC of a cloud computing platform, the B-EDC including a second transit gateway and a virtual router.

System for controlling tinting of one or more zones of windows in a building based on clear sky models for the building site maintained on a cloud network.

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.

In order to manage virtual private cloud (VPC) network configuration, a network topology and configuration of each network element are firstly obtained, and then a reachability intention including a target function and an intention attribute is defined. In one embodiment, a network representation is generated that describes how traffic is processed in a network element through an operable filter function, and a minimization problem is defined by converting the network representation into a MaxSAT formula that is used to minimize the number of decision variables to be modified. And according to a target function, defining a decision weight for the decision variable, and obtaining a solution of a minimization problem through a MaxSAT resolution algorithm weighted by the decision weight to generate an optimized network configuration.

An edge gateway deployed within an overlay network interconnecting a first public cloud network with an on-premises network is described. Coupled to a controller, the edge gateway is configured to receive a configuration file and attestation data from a controller, analyze the configuration file to obtain at least a first network address being used as an interface for secure communications with the controller, establish a secure interconnect with the controller based on the attestation data, and conduct a provisioning operation to initiate a request to the controller for edge gateway software thereby automated provisioning the edge gateway without human intervention. The edge gateway experiences automated provisioning based on a configuration file and attestation data upload.

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.

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.

Systems and methods are provided for implementing automated cloud buildout and / or run state management using cloud hosted orchestration of configuration and installation of cloud services. A configuration file, which outlines configurations and services to be applied to servers installed within a data center, is used by a computing system to orchestrate configuration or reconfiguration of the servers during buildout operations and / or run state operations of a cloud network(s). The computing system monitors for configuration changes or inconsistencies in the servers, as compared with the configuration file. If the configurations have been changed or are otherwise inconsistent with the configuration file, the computing system automatically restores, resets, or reconfigures the first servers or services / apps to be consistent with the configurations as outlined in the configuration file. A user interface may be provided to enable a user to view statuses of the buildout operations and / or the run state operations.

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.

A computer-implemented method is disclosed for predicting a future usage of a cloud-based computing resource based on a previous usage of the resource by users, and predicting an anomaly event at the resource. The method also includes identifying a top contributing user responsible for the anomaly event, throttling an access of the top contributing user, evaluating a speed of data requests received from the top contributing user, and maintaining a utilization level of the resource within a predetermined target range. The method further includes dynamically controlling the speed of data requests based on the evaluation of the speed of data requests and a controlling speed of data request recommended by a first artificial intelligence model. The recommendations of the first artificial intelligence model may be validated by a human reasoning based model configured to monitor and mitigate a risk associated with a counter-intuitive recommendation of the first artificial intelligence model.