985 results about "Event trigger" patented technology

The invention relates to a 5G network slice dynamic scheduling method and system based on multi-modal space-time perception and an event knowledge graph, and belongs to the technical field of mobile communication network resource management. According to the method, the change of a physical scene is sensed in real time by constructing a dynamically evolved event knowledge graph and designing a double-flow space-time cross network in combination with visual semantic analysis; dynamically adjusting the resource prediction model by adopting an event-scene dual-drive mechanism, dynamically adjusting parameters of the gated recurrent neural network through an elastic adjustment factor, and optimizing a multi-target resource allocation strategy based on a reinforcement learning algorithm; a two-stage resource scheduling mode is adopted, non-preemptive resource allocation of priority guarantee is implemented in an event triggering stage, and an optimization strategy of continuous adjustment is deployed in a steady-state stage. According to the method, the resource utilization efficiency and the service quality in a high-concurrency scene are remarkably improved, the method is compatible with an O-RAN standard interface, and the method is suitable for high-reliability and low-delay communication scenes such as smart cities and industrial internet.

The invention discloses an MES work order dynamic scheduling and resource self-adaption system based on real-time event triggering, and relates to the technical field of intelligent manufacturing and industrial automation, equipment states and material events are monitored in real time through interfaces such as a PLC and an OPCUA, event types and validity are analyzed through hardware filtering, feature code recognition and double verification, and the real-time event triggering is realized. Event data, MES batch information and equipment load data are integrated to generate standardized scheduling input, a preset strategy is matched, an optimal dispatching scheme is generated through a priority algorithm, material, equipment and logistics resource allocation and dispatching operation are completed, synchronization and MES interaction ensure that page logic is consistent, full-process automation of dynamic work order scheduling is achieved, and work order scheduling efficiency is improved. The equipment state and the material event are responded in real time, the production cooperation efficiency is improved by more than 30%, the resource adaptation accuracy rate reaches 95% or above, manual intervention is reduced, and the consistency of data and MES is guaranteed.

The invention relates to the technical field of network operation and maintenance, in particular to an automatic operation and maintenance method and system based on artificial intelligence, and the method comprises the steps: collecting detailed log information containing a security event in real time through a security information and event management system configured at a target endpoint; performing cleaning, labeling and structured processing on the log data by utilizing a proxy artificial intelligence system to generate standardized metadata, and performing MITRE ATTamp with the standardized metadata; mapping the CK knowledge base, identifying technical features and behavior patterns of attacks, comparing enriched log data with an external threat intelligence source, analyzing TTP of a known attack group, generating a threat intelligence association report, generating a targeted response plan by using a large language model, generating an executable command sequence according to the response plan, and generating a threat intelligence association report; the proxy executor is connected with the server through a WebSocket protocol, executes a command in a POSIX shell environment, captures and returns an execution result, verifies the execution result, carries out necessary command optimization, records an optimized response to a vector database, and automatically matches a historical event and triggers a predefined response process through a vector retrieval mechanism. And continuous threat monitoring and adaptive response are realized. According to the method, the problem that a closed loop aiming at a terminal executor, data enrichment and historical event recall cannot be formed by security operation and maintenance in the prior art can be solved.

The invention discloses a front-end task scheduling and event processing method and device, equipment and a storage medium, and relates to the field of distributed systems and network technologies, and the front-end task scheduling and event processing method comprises the steps of capturing events triggered by all sub-elements; processing the captured events into standard task objects in a unified format; adding the standard task objects into a scheduling queue according to a priority sequence, and performing de-duplication processing and task merging processing on all the standard task objects in the scheduling queue to obtain a cleaned scheduling queue; all the standard task objects are sorted again according to the priority in the multi-task priority queue; according to the priorities of the standard task objects in the multi-task priority queue, dynamically adjusting the resource allocation of each standard task object in the multi-task priority queue in combination with the current load of the system; and executing the standard task object allocated with the resources by combining an asynchronous execution mode with a user feedback mechanism. According to the method, the problems of task conflict and resource competition in high-concurrency interaction can be effectively solved.

The invention relates to the technical field of data sharing, and discloses a multi-department data sharing method and device, equipment and a storage medium. The method comprises the following steps: carrying out acquisition and standardized preprocessing on multi-department data required by enterprise project application to generate an intermediate data packet; establishing an event trigger distributed data control mechanism based on the intermediate data packet, calculating a dynamic trigger threshold, monitoring data change, and generating a target control data stream; performing template-free adaptive learning to generate an optimal data processing flow definition file; executing data classification, self-adaptive compression and increment processing at the edge computing node to generate an optimized data packet and metadata thereof; and inputting the optimized data packet and the metadata thereof into a SaaS cloud server central data warehouse to generate a project declaration data packet, thereby realizing consistency coordination and conflict automatic resolution of data of multiple departments, and realizing unified access and standardized processing of heterogeneous data sources.

The invention belongs to the technical field of Internet of Things, and relates to a data transmission method based on event driving and dynamic allocation, which comprises the following steps of: S1, data acquisition and integration: triggering a sensor to acquire when an environment changes drastically by using an event triggering acquisition mode; s2, calculating data volatility based on a sliding window, and dynamically adjusting a threshold value of incremental data transmission according to the data volatility to realize dynamic adjustment of transmission frequency; s3, dynamically allocating QoS levels according to the priority and timeliness of the data by using a dynamic QoS allocation mechanism, and performing data transmission according to the QoS levels; and S4, data storage. Data are collected in a condition triggering mode, meanwhile, a dynamic sampling algorithm is introduced, and the sampling frequency is automatically adjusted according to changes of environment variables. And the real-time performance of the key data and the economical efficiency of the data are ensured.

The invention discloses an intelligent simulation system and method based on a power distribution digital system, and relates to the technical field of power distribution network intelligent simulation. The event triggering module is used for constructing a composite triggering condition and obtaining an operation event based on the power distribution network data and the composite triggering condition; the event classification module is used for constructing an event template library and obtaining a target event type based on the running event and the event template library; the event-modeling demand mapping module is used for constructing an association rule base and obtaining a scene structure body and a modeling task package based on the association rule base and the target event type; and the modeling module is used for constructing a simulation model based on the modeling task package and the scene structure body, and obtaining an execution result based on the simulation model, so that the problem that the intelligence degree of event perception and response of the current dynamic modeling system of the power distribution network is insufficient is solved.

The invention discloses a resource collaborative awareness-based Storm flow calculation dynamic scheduling method, and provides the following technical scheme aiming at the problem that the performance of a Storm default scheduling algorithm is reduced in node abnormity, resource fluctuation and rescheduling scenes: firstly, dynamically sensing node busy, downtime and data flow fluctuation events through a real-time monitoring module; triggering a rescheduling process; secondly, constructing a resource collaborative optimization model based on historical task instance resource requirements, node performance indexes and communication overhead, and generating a task instance allocation scheme by taking minimization of inter-node communication cost as a target and combining CPU / memory dynamic threshold constraints; further, a greedy algorithm is adopted to sort high-relevance task instances, the high-relevance task instances are preferentially distributed to nodes with the optimal historical performance, and it is ensured that the node resource utilization rate does not exceed a dynamic threshold value; meanwhile, node load balancing parameters are corrected in real time through time window smoothing processing, and the remaining resource state is updated; and finally, outputting an optimized topology division result, so that the system delay after rescheduling is remarkably reduced, and the throughput is improved. According to the method, rapid recovery and stable operation of the heterogeneous cluster are realized through resource collaborative modeling, historical data driven dynamic scheduling and load balancing optimization.

The invention relates to a method for improving the calculation speed of a model based on a mercuric chloride AI processor. The method comprises the following steps: deploying the mercuric chloride AI processor and a deep learning model in a server, and carrying out adaptation and optimization on the mercuric chloride AI processor; before the data in the first buffer area is read, predicting and preloading the data to be processed, and loading the data from the global memory to the second buffer area in advance; a double-buffer mechanism is arranged in the mercuration AI processor, interrupt and event trigger points are set, the operation of loading data to a next buffer area is immediately started when a specified calculation stage is finished, and the time sequence of data circulation is accurately controlled; and a control parameter is automatically adjusted based on monitoring data of the real-time monitoring module, the calculation process is decomposed into a plurality of stages, different buffer areas are allocated for each stage, and access to the shared memory is optimized by setting a specified cache replacement strategy and the size of a cache line. According to the process, the calculation speed of the model in the deep learning field is improved, the resource utilization rate is improved, and the defect of manual adjustment and optimization is overcome.

The invention relates to the technical field of mechanical arms, in particular to a man-machine interaction system of an intelligent mechanical arm with a body. The system decomposes a long time sequence task into sub-tasks through a large language model, and introduces a task acquisition module, a task queue management module, a task re-planning module and a control execution module, uses visual detection to identify gestures and environment events to trigger temporary tasks, and maintains interruptible marks and safety anchor points based on priorities and interruption risks. And during interruption, the mechanical arm with the timestamp and the environment state are collected, during recovery, the states are compared, local re-planning is carried out, transition sub-tasks are automatically generated for failure sub-tasks, and the mechanical arm is controlled to execute after constraint verification. According to the system, on the premise that the structure consistency, the space consistency and the time consistency are guaranteed, safe interruption and efficient recovery in a long-time-sequence task can be achieved, and the autonomy, the real-time performance and the operation safety of the mechanical arm in a man-machine cooperation scene are remarkably improved.

The invention relates to the field of clean energy, and provides a distributed secondary control method for an island micro-grid system based on event triggering, which comprises the following steps: S1, connecting adjacent distributed units in an island micro-grid through a local communication link, and constructing a distributed control architecture to eliminate dependence on a central controller; s2, triggering communication of the local communication link based on a preset threshold value, and transmitting a secondary control signal when the system state deviation exceeds the threshold value; s3, performing cooperative calculation on the secondary control signal by using the distributed control architecture, adjusting frequency and voltage deviation, and shielding original power data; and S4, connecting a newly added distributed unit to the distributed control architecture through the local communication link, thereby reducing high communication burden and single-point fault of centralized control of the island microgrid.

A system, includes processing circuitry; and a memory connected to the processing circuitry, wherein the memory is configured to store executable instructions that, in response to being executed by the processing circuitry, facilitate performance of operations to receive, by a policy manager, one or more events from a databus; trigger, based on the one or more events, an existing assurance policy; trigger, based on the existing assurance policy, a prediction request to an artificial intelligence (AI) / (ML) machine learning application; receive, by the policy manager, a change recommendation from the AI / ML application; create, by the policy manager, a new assurance policy based on the change recommendation from the AI / ML application; and trigger, by the policy manager, a corrective action to be taken based on a triggering of the new assurance policy implementing the change recommendation.

The embodiment of the invention discloses an interface interaction method which comprises the steps that drawing attribute information of all components in source codes of a target interface and interaction event information corresponding to all the components are read, and the source codes are written in a component form; generating an interface canvas based on the drawing attribute information of each component, the interface canvas containing each component of the target interface; generating an interaction canvas based on the position attribute information and the size attribute information of each component; based on the interface canvas, rendering the target interface in the browser page; in response to the monitored event triggered based on the target interface, determining a pixel coordinate of an event triggering position in the interaction canvas; and based on the pixel coordinates, obtaining a target component for the event, and executing a response operation of an interaction event corresponding to the target component. According to the embodiment of the invention, the consistency of the user interfaces in the browser pages of the terminals can be realized, so that the consistency of event interaction response is ensured.

The invention belongs to the technical field of computers, and discloses a resource elastic scaling method and system based on the average consistency of a multi-agent system, and the method comprises the steps: obtaining the state information of a current server, and estimating user input based on the state information and a scaling decision at the last moment; an event trigger is designed, and if the event trigger based on the edge is triggered, the server sends own state information to the neighbor and receives the state information of the neighbor; if the event trigger based on the node is triggered, the server records the state of the load observer of the server and the information of the self-adaptive variable; and forming a scaling decision according to the state information of the server at the last triggering moment, the state information of the neighbor server and the state information of the load observer, executing the scaling decision and updating the state information of the server. According to the method, on the premise that global information of communication topology is not used, the security resources of the server cluster under DSS attack are elastically expanded and contracted, and the server cannot be misguided by tampered information.

The invention discloses a power data communication network security situation prediction method, which comprises the following steps of: aiming at a hot spot multi-dimensional orientation description vector, acquiring a network security event log, adopting a time sequence event chain construction technology, and determining event triggering frequency and service interruption duration related to a hot spot through matching of event triggering frequency and event association strength, so as to predict the security situation of the hot spot. Obtaining an event chain sequence; extracting an event trigger frequency, a service interruption duration and a hotspot influence range from the event chain sequence, and judging a hotspot life cycle stage through quantification of a node load state and traffic abnormal fluctuation to obtain a life cycle quantitative index; and extracting a hot spot influence range and traffic abnormal fluctuation from the global security situation view data, and if the hot spot influence range or the traffic abnormal fluctuation exceeds a preset threshold, adjusting weight redistribution through a node load state to obtain an incremental change feature set. According to the method, the hotspot situation in the power data communication network can be comprehensively and dynamically analyzed, and powerful support is provided for network security management and decision making.

The invention discloses a spacecraft cluster robust formation control method based on a dynamic event trigger mechanism, which is applied to the technical field of spacecraft cluster formation control, and aims to solve the problem that the prior art still has certain limitations under the complex conditions of limited communication, unknown control input of a virtual leader, external disturbance and the like. The method comprises the following steps: firstly, constructing a six-degree-of-freedom attitude and orbit coupling spacecraft cluster system model influenced by external disturbance and model uncertainty; on the basis, a robust formation control scheme based on a dynamic event trigger communication mechanism is designed, and the scheme comprises three key components, the three mechanisms are respectively a self-adaptive second-order expansion system based on local discontinuous communication, a multi-spacecraft robust formation device based on neural network self-adaptive estimation and a unified dynamic event trigger communication mechanism.

An information handling system node includes a hardware processor, a memory device, a power management unit with a peripheral device node operatively coupled to the information handling system node. The hardware processor may execute computer-readable program code of a custom event and device manageability service sub-agent to discover the peripheral device node operatively coupled to the information handling system node including a unique peripheral device identification (ID), request and receive, via a unified device application programming interface module, peripheral device capabilities and event IDs, where the event IDs describe custom events that are transmittable via any bus protocol from the peripheral device node, and register for custom event notifications with the peripheral device node by sending callback messages to the peripheral device node describing which custom events to receive custom event notifications about and setting custom event triggers that trigger the custom event notifications.

The invention relates to an event trigger system based on an openGauss database. The system comprises: an event trigger definition module supporting a user to define a trigger rule of an event trigger; the trigger function execution module provides an execution environment for a function associated with the trigger and executes function logic; and the event monitoring and processing module monitors database operation events, matches corresponding event triggers according to trigger rules, and coordinates the execution sequence and error processing of correlation functions of the event triggers. According to the system, flexible trigger rule definition is supported through extension grammar, the metadata management efficiency is guaranteed by combining semantic verification and a special storage structure, the execution performance is optimized by utilizing pre-compiling and caching technologies, accurate monitoring and trigger coordination of events are realized through a kernel hook mechanism, and the reliability of the system is improved. The limitation that a traditional trigger only covers a DML event is effectively solved, the reliable management and control capability of full-type operation (DML / DDL) is provided for the openGauss database, and the safety, maintainability and application stability of the database are remarkably improved.

The present invention relates to the technical field of wireless sensor networks, and to an average consistency time synchronization method based on a multi-hop virtual link and event triggering. According to the method, in the case that a communication delay is present in a wireless network, a least squares estimator is used to restrain the effect of the delay in the relative frequency offset estimation process; clock information of nodes is fully called by means of the multi-hop virtual link for update, thereby effectively increasing the clock synchronization speed; an event triggering policy is used to reduce a transmission frequency between the nodes, thereby effectively reducing communication overhead; and a consistency algorithm is used to update logic clock parameters of the nodes, thereby realizing global consistency of clocks of the nodes in a wireless sensor network. According to the present invention, the effect of the communication delay in the wireless sensor network is taken into consideration, an iterative least squares estimator is used to obtain a high-precision relative frequency offset value to improve the synchronization precision, and by using an interaction mechanism of the multi-hop virtual link and event triggering, the communication overhead is effectively reduced while increasing the convergence speed of a clock synchronization error.

The invention provides a power grid operation analysis method based on a cloud platform, and relates to the technical field of power grid operation analysis, and the method comprises the steps: configuring a semantic event template library, configuring multi-source power grid operation data access and time reference synchronization, configuring an event triggering rule and an event judgment mechanism, and extracting an event fragment data set, and configuring a semantic abstract vector, executing semantic compression, generating a unique analysis task number, registering a task metadata directory, and setting a task priority and priority queue arrangement. By configuring the semantic event template library and realizing the access and time reference synchronization of the multi-source power grid operation data, the unity and timeliness of the event fragment data set can be ensured in a mass data environment, the problem of analysis errors caused by non-uniform data formats and non-uniform time sequences in the prior art is solved, and the analysis accuracy is improved. Therefore, the reliability of power grid operation state identification and analysis results is improved.

The invention relates to the technical field of network detection, and provides a dynamic event trigger fault detection method under DoS network attack, which comprises the following steps: establishing a linear state space model of a network control system; defining a non-attack interval and an attack interval of system operation, and constraining attack frequency and duration; the observer gain is switched according to the current non-attack interval or attack interval of the system; a dynamic event triggering mechanism is constructed, and the triggering condition depends on the output state and the internal dynamic variable of the full-order switching observer and is used for dynamically adjusting the data transmission frequency; establishing a closed-loop switching system model; and analyzing system index stability according to the closed-loop switching system model, and cooperatively designing observer gain, controller gain and event triggering parameters. According to the invention, through quantification of the DoS attack model, the dynamic event triggering mechanism and collaborative optimization design, the effects of effectively detecting the system fault and improving the utilization rate of the network channel are achieved.

The invention discloses a CAN message priority dynamic arbitration method and system based on event triggering, and the method comprises the steps: obtaining a discrete sampling signal of a CAN node of an engineering vehicle and a state register value of a CAN controller, converting the discrete sampling signal into a working condition data sequence, and obtaining a bus load rate through the state register value; obtaining an event state sequence according to the working condition data sequence; all CAN messages to be sent are constructed into a message data record, and the message data record with event semantics and dynamic priority labels is obtained according to the protocol data unit and the event state sequence; and according to the bus load rate and the event state sequence, sending a message data record with event semantics and dynamic priority annotations by adopting a token bucket mechanism through a three-level priority queue linked with a three-state state machine. According to the invention, the security key message in the system can still be transmitted in time under high load, and the bandwidth occupation and delay jitter caused by the low-priority message are avoided at the same time.

The invention discloses an event-driven business agent dynamic construction method and equipment, belongs to the technical field of intelligent application, and is used for solving the technical problems that the intelligent transformation cost of a traditional business system is high, and a manually constructed business agent is logically solidified and cannot quickly cope with business requirements and environment changes. The method comprises the following steps: monitoring a service event occurring in a service system, obtaining corresponding service event information and extracting upstream service context information corresponding to the service event; identifying a downstream service of the service event in the service system according to the service event and the upstream service context information, and acquiring service information of the downstream service; based on the business event information and the business information of the downstream business, constructing a business agent for executing the downstream business action, and storing the business agent to a business agent center; and when the new business event is monitored, a corresponding business agent is matched in the business agent center, so that the business agent executes a downstream business action triggered by the business event.

Provided in the present application is a function management method. The method comprises: receiving a function call trigger event triggered by a user for a target function; on the basis of a function identifier of the target function, acquiring functionality classification information of the target function; on the basis of the functionality classification information of the target function and a mapping relationship between a function functionality and a container type, determining a target container type matching the functionality classification information of the target function; allocating, from a container resource pool, a container of the target container type to the target function; and loading, in the container, a code package of the target function, so as to execute a corresponding system call behavior. In the method, isolation technology for matching differentiated containers for functions according to requirements is provided, the functions are classified from a security dimension, and the functionalities of containers are separated, such that the functions of different security types are operated in different types of containers, and thus the calculation and data security of the functions themselves are achieved, and the security guarantee for a serverless platform is realized, thereby preventing a malicious function from performing container escaping to destroy an operation environment of the serverless platform.

The invention discloses a power load prediction method, and the method comprises the steps: firstly solving an extreme event data sparsity problem through a generative adversarial network, and constructing an event time sequence library through a time sequence anomaly detection algorithm; then analyzing the causal relationship between the event and the load by applying a causal discovery algorithm, and converting prediction output into probability distribution by adopting a Bayesian neural network to quantify uncertainty; constructing a prediction model triggered by an event, and generating a multi-time scale probability prediction interval; and finally, generating a multi-scene prediction result through Monte Carlo simulation, quantifying the system recovery capability in combination with a toughness index, and integrating the system recovery capability to a decision support system to generate a risk response scheme. According to the method, the accuracy and robustness of load prediction under the extreme climate are remarkably improved, full-chain risk insight from early warning to recovery is realized, and prospective decision support is provided for safe operation of a power system.

Methods, systems, and apparatuses are provided for event triggered reporting in a wireless communication system, wherein a method of a User Equipment (UE) comprises triggering a first report in response to a first condition being fulfilled, transmitting a request in response to the triggering of the first report, receiving a first Downlink Control Information (DCI) scheduling a first Physical Uplink Shared Channel (PUSCH), determining whether to transmit the first report on the first PUSCH based on whether a Channel State Information (CSI) request field in the first DCI indicates a first code-point which is associated with a first CSI triggering state associated with a first CSI report configuration for the first report, and transmitting the first report on the first PUSCH if the CSI request field in the first DCI indicates the first code-point.

The invention provides a communication method, the communication method is applied to a terminal device, and the communication method comprises the following steps: receiving measurement configuration information from a network device, the measurement configuration information comprising an event triggering condition; the physical PHY layer measures a reference signal to be measured, determines that an event triggering condition is satisfied and sends first indication information to a medium access control (MAC) layer; and the MAC layer sends a measurement result to the network equipment through MAC layer signaling according to the first indication information. In the application, the PHY layer can measure the reference signal to be measured to determine the measurement result; the MAC layer can send the measurement result through MAC layer signaling (such as MAC CE), so that the network equipment can perform mobility management such as scheduling strategy updating or cell switching, beam switching and the like based on the measurement result. According to the method, the uplink resource occupation of the terminal equipment can be reduced while the measurement result is reported quickly and timely.

The invention provides a component freezing recovery method based on a page life cycle interface. In the frame compiling stage, page life cycle event monitoring logic is injected into the component, a freezing and recovering event monitor is automatically registered, a large-data-volume rendering component tree is recognized, a freezing identifier is added, and butt joint of the Vue component tree and a browser freezing event is achieved. When a freezing event is triggered, dependence of a responsive memory for releasing a virtual rolling component in a background label page is ensured by pausing virtual rolling rendering, generating a component state snapshot, creating a rolling position anchor point record, removing non-visual area nodes, retaining placeholder elements and releasing responsive data binding. And after a recovery event is triggered, positioning a rolling position based on anchor point parameters, preferentially reconstructing a visual area component in stages, and recovering the responsive system, so that rolling position zero offset and state zero loss are realized when the page is recovered, and the reconstruction process has no perception delay. According to the method, manual intervention is not needed, and front-end development efficiency and performance optimization are both considered.

The invention provides a data processing method and device, electronic equipment and a storage medium, and the method comprises the steps: in response to a user interaction event triggered for a network page, screening a sub-tree matched with event attribute information of the user interaction event from a plurality of sub-trees contained in a structure tree of the network page; wherein the structure tree is used for representing a plurality of webpage sub-regions, and the sub-tree is used for representing webpage elements in the webpage sub-regions; according to the matched sub-tree, determining a webpage element to be identified in the network page; obtaining a trigger operation corresponding to the to-be-identified webpage element, and identifying the trigger operation through a first strategy to obtain a first identification result; performing content identification on the to-be-identified webpage element through a second strategy to obtain a second identification result; and under the condition that it is determined that the to-be-recognized webpage element contains the interference information according to the first recognition result and the second recognition result, shielding processing is executed. The method can improve the comprehensiveness and accuracy of identification.

The invention provides a multi-microgrid load frequency control method based on dynamic event triggering, which can be applied to the technical field of intelligent microgrids. The method comprises the steps that a local sampling error of the micro-grid system is acquired, the local sampling error is obtained based on a global neighborhood error and a local neighborhood error of the micro-grid system, and the local neighborhood error is used for representing a state difference between the micro-grid system and a neighbor micro-grid system at a sampling moment; under the condition that the local sampling error meets a dynamic event triggering rule, updating an initial weight matrix of the action-evaluation neural network based on the local sampling error to obtain a target action-evaluation neural network; and determining a load frequency control strategy of the micro-grid system based on the system state of the micro-grid system at the sampling time and the target action-evaluation neural network. The invention further provides a multi-microgrid load frequency control device based on dynamic event triggering.