43 results about "Cloud systems" patented technology

The application discloses an unmanned aerial vehicle intelligent sensing and intention reasoning system and device, which comprises image acquisition, target detection, knowledge graph, multi-modal large model, airborne computing power and edge-cloud cooperation module. The system is guided by target detection, enhances scene knowledge through the knowledge graph, improves the analysis ability of the multi-modal large model, and realizes the intelligent monitoring of the unmanned aerial vehicle based on the RK3588 platform. Real-time monitoring is realized by using the maneuverability of the unmanned aerial vehicle, which can not only analyze the scene, but also infer and predict the behavior intention and situation, thereby realizing early warning. The local and cloud systems are equipped with a historical database, a visual interface and a large parameter model, and the returned information is deeply analyzed. The system can be applied to the scenes of border patrol, city security, animal protection and the like.

This application discloses a logical node management method and cloud system based on cloud computing technology, belonging to the field of cloud service technology. The method includes: a cloud management platform creating a target logical node in the infrastructure, wherein the target logical node includes a virtual CPU, a first virtual extended processor, and a virtual bus network, the virtual CPU and the first virtual extended processor being logically connected to the virtual bus network respectively; if the cloud management platform confirms that at least one first extended processor in the extended processor device pool has failed, it unloads the first virtual extended processor from the target logical node; the cloud management platform then attaches a second virtual extended processor to the target logical node, the second virtual extended processor implementing all or part of the functions of at least one second extended processor in the extended processor device pool, the second virtual extended processor being logically connected to the virtual bus network. This application improves the utilization rate of cloud resources.

Embodiments of the present application provide an edge resource expansion method, an edge cloud system, a device and a storage medium. In the embodiments of the present application, a center service node in a center cloud can request a server producer to produce a target server based on an edge resource expansion request of a target user; and install an operating system on the target server and deploy a cloud service; then, a logistics transportation party can be instructed to transport the target server to a target edge cluster corresponding to the target user, so as to deploy the target server in the target edge cluster and expand an edge node in the target edge cluster. In the embodiments, a whole-link expansion process integrating the user's edge resource expansion request, server production, transportation and edge cluster deployment is implemented, and the edge node expansion is integrated and end-to-end edge node expansion is implemented.

A hybrid AI cloud system includes at least one distributed node configured to execute an artificial intelligence (AI) service, and a hybrid server configured to monitor the workload of a first distributed node configured to execute the AI service, and prepare in advance at least one second distributed node configured to assist or replace the first distributed node according to the result of the monitoring. The second distributed node is selected from a previously prepared distributed node pool including distributed nodes of the hybrid AI cloud system, or from a distributed node of an external cloud system. Through this, if there is a shortage of distributed nodes capable of executing AI services in the distributed cloud, distributed nodes included in a centralized cloud can be utilized, thereby achieving the advantages of both the distributed cloud and the centralized cloud.

This application provides a vehicle-cloud collaborative instruction execution method and a vehicle-cloud system. The method includes: receiving a message sent from the cloud, wherein the message includes at least one instruction; extracting the message sequence number to obtain a message sequence number, and extracting the instruction sequence number to obtain an instruction sequence number; determining that there is no packet loss when multiple message sequence numbers, multiple instruction sequence numbers, complete instructions, and the execution of the corresponding preceding instructions are all satisfied, wherein complete instructions mean that the instruction content is not missing, the preceding instructions and the corresponding instructions have a dependency relationship, and the instruction sequence number of the preceding instructions is less than the instruction sequence number of the corresponding instructions; and, given that there is no packet loss, executing the instructions sequentially according to their priority, wherein the instruction priority is positively correlated with the importance of the instructions. This solution solves the problem of poor reliability in the execution of vehicle-cloud collaborative control instructions in existing technologies.

Methods, systems, and computer-readable storage media for receiving a request of an API call from a client, the request including a query, determining a score for the request, the score representative of a burden that the request would place on technical resources, if the request were to be executed, in response to the score, providing a response including a set of actions without executing the request, orchestrating a set of API sub-calls based on the set of actions, each API sub-call returning a sub-call response, merging the sub-call responses to the set of API sub-calls to provide a final result, and returning the final result in response to the API call to the client.

The application is suitable for the computer technical field, and provides a training method and device of a detection model, a quality of service detection method and device. The training method of the detection model comprises the following steps: obtaining a first feature data set, the first feature data set containing a plurality of first input features and corresponding quality of service; taking all the first input features and the corresponding quality of service as model input samples and model output samples respectively, training a detection model to obtain an intermediate detection model; the intermediate detection model is used for learning effective features related to the quality of service in the first input features; determining a second feature data set based on the first feature data set and the intermediate detection model; and training the intermediate detection model based on the second feature data set to obtain a target detection model. Through the above training method, the target detection model can accurately predict the quality of service of monitoring data, and ensure that the cluster resource scheduling in the cloud system matches the quality of service demand.

There is disclosed devices, systems and methods for nonverbal multi-input and feedback devices for user intended computer control and communication of text, graphics and audio. The system comprises sensory devices comprising sensors to detect a user inputting gestures on sensor interfaces, a cloud system comprising a processor, for retrieving the inputted gestures detected by the sensor on the sensory device, comparing the inputted gestures to gestures stored in databases on the cloud system, identifying at least a text, graphics and / or speech command comprising a word that corresponds to the inputted gesture; showing the command to the user; and transmitting the command to another device.

The application discloses a high-rise building fire fighting and escaping early warning monitoring device and method, and relates to the technical field of linkage fire safety.The application is configured with early warning monitoring boxes in each floor area of the high-rise building floor ladder, which timely and effectively monitors the surrounding environment airflow temperature and smoke concentration when a fire occurs, analyzes the temperature safety factor and smoke concentration safety factor of the floor area where the fire exists in real time, analyzes the longest safe time that can be separated from the floor where the fire occurs, and according to the position of the trapped person and the state of fire spread, the cloud system timely sends corresponding escaping safety signals to the trapped person's mobile phone APP, provides a relatively accurate and safe escaping scheme for the trapped person, so that when a fire occurs in the high-rise building, the trapped person can timely and relatively safely escape from the fire area, and the trapped person can also avoid the danger caused by rashly breaking out.

A method for identifying logical mistakes in a cloud-based decision management system, comprising, providing an interface configured to present decision logic using a structured rule language; defining a plurality of functional breakpoints within the structured rule language; pausing execution of the decision logic at one or more of the plurality of functional breakpoints to allow inspection of underlying logic and associated data changes, wherein the pausing and synchronization are facilitated by a distributed breakpoint execution engine operating within the cloud-based decision management system; providing a visualization of a plurality of parameters through a properties tab; and resuming the execution of the decision logic to facilitate identification of the logical mistakes in the decision logic, wherein the visualization provides real-time updates and aids in pinpointing logical mistakes.

Systems and methods for dynamic traffic routing include monitoring connectivity to a plurality of available Data Centers (DCs) associated with a cloud-based system; generating real-time connectivity information based on the monitoring, the real-time connectivity information including a performance level of the plurality of available DCs; determining a best performing DC from the plurality of available DCs; and switching a connection from a current DC to the best performing DC.

Systems and methods for a Cloud Service Provider (CSP) event capture and processing system include retrieving a change feed from one or more Cloud Service Providers (CSPs) associated with a customer of the cloud-based system; analyzing the change feeds to identify modifications of one or more resources within network environments associated with the customer, wherein the network environments are provided by the one or more CSPs; updating a data store of the customer with any new or modified resources based on the analyzing; and providing a customer-specific dashboard including analytics for all CSPs associated with the customer of the cloud-based system.

This invention discloses an AI-powered BeiDou vehicle-road-cloud system and method for source control of vehicle violations, relating to the fields of traffic safety and vehicle-road-cloud integration technology. Currently, most traffic violations are handled post-incidentally, resulting in shortcomings such as insufficient source control (e.g., drunk driving, unlicensed driving, fatigued driving, inadequate screening of hazardous and prohibited items), data gaps across departments, and delayed early warnings. The nation's vigorous promotion of the strategies of a safe China, a strong transportation nation, national security governance, and vehicle-road-cloud integration urgently requires proactive and preemptive safety control technologies. This invention relies on AI large-scale models and BeiDou high-precision positioning, with hardware integrated and deployed in key areas of the vehicle. It enables driver facial recognition verification, identity verification, intelligent alcohol control, fatigue driving intervention, in-vehicle status perception, detection of drugs, dangerous goods, and explosives, multilingual sensitive word monitoring, biometric comparison of rear-seat occupants, and multi-dimensional risk assessment. Combined with vehicle-road-cloud collaborative interaction and black box full-process evidence storage, it connects with the public security system, enabling silent and unobtrusive reporting of abnormal risks and tiered, humane handling. It blocks traffic violations and public safety hazards at the source, deeply aligning with national security governance strategic needs, balancing road traffic management and national security prevention and control requirements, and is suitable for large-scale deployment and application of various commercial and social vehicles.

Provided is a resource usage prediction model-based orchestration method in an SDI implementation environment. The orchestration method according to an embodiment may dynamically allocate resources to tasks according to importance, based on prediction of future resource usage through real-time monitoring of resource usage of an SD-mobility device such as an SDV, an SRD, an SDA in an SDI implementation environment, and may predict the occurrence of resource overload of the SD-mobility device and offload the tasks in association with a cloud system. Accordingly, limited resources of the SD-mobility device may be efficiently used and the SD-mobility device may be supported to maintain optimal performance.

This invention discloses an alarm convergence method, apparatus, device, and medium based on heuristic rules and a large language model. The method includes: acquiring alarm data streams from a distributed cloud system; dividing the alarm data streams based on a preset time window to construct a target alarm pair set; calculating a first relevance score for each alarm pair in the target alarm pair set based on heuristic rules; classifying alarm pairs into high-confidence alarm pairs and low-confidence alarm pairs based on the first relevance score; inputting the low-confidence alarm pairs into a large language model; using the large language model to call operation and maintenance knowledge documents and system topology data to perform causal inference on the low-confidence alarm pairs to determine a second relevance score; generating a relevance matrix based on the first and second relevance scores; and aggregating the alarm data streams based on the relevance matrix to generate alarm clusters. This achieves the technical effect of improving the accuracy of alarm aggregation.

Disclosed are a multi-satellite collaborative dynamic micro cloud building method and a distributed micro cloud system. The method includes step S101: triggering to build an initial state of a micro cloud satellite group according to a task instruction; after a satellite node closest to a task center receives the task instruction, each satellite node will perform matching analysis according to its position and existing resource conditions; if the current position of a satellite node meets requirements and carried resources also meet requirements, the satellite node joins the micro cloud satellite group; step S102: beginning task planning and task execution after the satellite nodes join a micro cloud, so as to provide on-orbit service support. The multi-satellite collaborative dynamic micro cloud building method and the distributed micro cloud system can provide more reliable and efficient satellite communication services.

The present invention provides a dynamic immune end-to-end trusted sharing method for multimodal data in a vehicle-road-cloud system, belonging to the field of information security technology. The method includes: using a vehicle-side or roadside unit with a digital certificate as the sending end, securely encapsulating the original multimodal data to generate a secure encapsulation result, and transmitting the secure encapsulation result to a cloud platform; using the cloud platform as the receiving end, recovering the original multimodal data; using the cloud platform to perform a trustworthiness assessment of the sending end based on the recovered original multimodal data (both current and historical), obtaining multi-dimensional assessment indicators; using a preset trust fusion model combined with the multi-dimensional assessment indicators to calculate and generate a dynamic trust value for the sending end; and triggering corresponding security handling strategies based on the dynamic trust value. This invention, through the synergistic linkage of dynamic trust value and security strategies, enables the system to possess adaptive perception and proactive immunity against internal threats, effectively ensuring the trustworthiness of shared data.

Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides mechanisms for managing, optimizing and configuring a WiFi network at a location. The framework provides network management utilizing edge processing capabilities to bridge local WiFi and cloud systems. The framework implements comprehensive device typing through multi-layered analysis combining passive monitoring, deep packet inspection and hybrid deterministic-probabilistic classification methods. State synchronization between local and cloud networks can be achieved through hierarchical data modeling and differential synchronization algorithms. The framework can implement advanced features that include automated channel optimization, QoS management, and security monitoring. The framework incorporates self-healing capabilities using reinforcement learning techniques and maintains operational efficiency through intelligent resource management and workload distribution. The framework can operate autonomously while requiring minimal cloud connectivity, featuring extensible architecture through a plugin system that enables adaptation to evolving network requirements while maintaining stable operation of existing capabilities.

This invention discloses a method and system for locating the root cause of a fault, relating to the field of cloud technology. The method includes generating read-only fault analysis data based on multimodal telemetry data and resource topology data within the fault attribution time period; constructing an anomaly relationship graph with abnormal states as graph nodes based on this data, dividing it into multiple fault groups, where nodes within the same group satisfy physical topological reachability and temporal causal relationships; generating candidate fault source location results for each group through retrieval, and selecting the result from the candidate results that satisfies the following conditions: a directed connected path exists between the fault source and the symptom object in the resource topology; the fault source's anomaly start time is earlier than the symptom object's; and at least two different modalities of anomaly data simultaneously support the result. This invention can solve the problem that related technologies cannot accurately determine the root cause of cloud system faults, achieving automated root cause location and evidence verification for complex cloud system faults.

Cloud systems store metadata for multiple tenants in cache memory. In uncompressed form, caching the metadata for an entity for multiple properties uses memory that is proportional to the number of tenants. As disclosed herein, global metadata is generated for one or more entities. The global metadata of an entity includes all properties of the entity from all tenants. For each entity, only one set of global metadata is stored. For each tenant, only the differential data for the entity is stored. As a result, the size of a tenant's differential metadata is substantially smaller than the tenant's original full metadata, saving cache resources of the cloud system. Full entity metadata for a tenant can be retrieved by making a copy of the global metadata for the entity and modifying the copy based on the tenant's differential data for the entity.

This application provides a virtual private cloud (VPN) simulation communication method, apparatus, device, and storage medium, relating to the field of computer network technology. The method includes: responding to a simulation command instructing the simulation of a target VPN, and determining a target external network that interacts with the target VPN indicated by the simulation command. Simulation processing is performed on both the target VPN and the target external network to obtain corresponding simulated VPNs and simulated external networks. Then, the simulated VPN is configured, and a communication connection is established between the simulated VPN and the simulated external network. If the communication connection is successfully established, configuration information of the simulated VPN is obtained and applied to the target VPN. This method avoids directly configuring the target VPN in the actual production environment, improving the availability and security of the public cloud system and saving unnecessary costs.

Techniques are disclosed for enabling dynamic routing of identity and access (IA) requests to a cloud identity and access management (IAM) system. In some embodiments, the health (or service quality) of a cloud IAM system is continuously monitored in the background to update routing information for dynamically routing IA requests for client cloud services to the cloud IAM system in the foreground. In some embodiments, background monitoring is performed by sending first-type IA requests to the cloud IAM system to discover traffic patterns. In some embodiments, routing information may be mappings between client cloud services and identity endpoints of service cells in the cloud IAM system with configurable attributes that help rebalance and distribute the IA traffic.

A system and method of interacting with cloud systems using a first cloud system (“FCS”) and an application programming interface (“API”) that interacts with a second and third cloud system, the method comprising: receiving, by the API, a user instruction associated with a file; accessing, in a database of the FCS, metadata for the file to identify a storage setting of the file; accessing, by the processor and when the storage setting is an infrequent identifier, an infrequent storage of the FCS; accessing, by the processor and when the storage setting is a frequent identifier, the frequent storage of the FCS; monitoring, by the processor, a change to the media in the FCS; and implementing, by the processor, the change to the media in the second and third cloud systems thereby syncing and performing real-time reconciliation across the first, second, and third could systems.

The embodiment of the specification discloses a data processing method, device and electronic equipment, the method comprises the following steps: receiving an application modification request, sending the object identifier to the server of a private cloud system, receiving the configuration file corresponding to the request object returned by the server, and acquiring the access mode of the application to be modified according to the identification information or modification demand of the application to be modified; the access mode of the application to be modified is acquired from the configuration file according to the access mode of the application to be modified; based on the modification demand, the configuration information in the modified configuration file is modified, the updated configuration file is obtained and returned to the server, so that the server publishes the updated configuration file online and replaces the modified configuration file in the private cloud system. By using the technical scheme provided in the specification, the application access configuration and the system are decoupled, the system bottom code does not need to be written, and the application access configuration can be flexibly modified during the system running.