65 results about "Mission critical" patented technology

The invention discloses an intelligent resource scheduling method and system based on task characteristics and system state perception, and relates to an operating system kernel optimization technology. According to the method, resource demand types, importance labels and time sensitivity of tasks are captured in real time through an eBPF technology, system bottlenecks are recognized by combining / proc and sysfs file system data, a dynamic scheduling strategy is generated by adopting an improved Q-Learning model, and resource allocation is executed through a schemed * function and a cgroup v2 interface. The problems that a traditional scheduler is poor in self-adaptive capacity and resources are mismatched are solved, the actually-measured resource utilization rate is increased to 85%-92%, and the key task delay standard reaching rate gt is achieved; the method is suitable for edge computing, cloud servers and other high-concurrency scenes.

The invention provides a lightweight intelligent control method for a low-altitude operation scene, and the method comprises the steps: focusing a low-altitude key target through an attention mechanism based on a lightweight deep learning model; data enhancement is carried out through a dynamic data enhancement module so as to expand the diversity of training samples; calling a space-time calibration model to process the multi-source data, and controlling a time synchronization error and a space positioning deviation within a preset range; based on a dynamic obstacle trajectory prediction module, historical motion data and environmental constraints are fused, and a lightweight LSTM network is adopted to predict a trajectory of a dynamic target in a future time period; and calling a task priority-computing power load dynamic matching mechanism to realize task allocation, and adjusting computing power occupation of non-critical tasks according to a designed energy consumption perception scheduling strategy. According to the method, the autonomous perception, decision making and resource management capabilities of the low-altitude operation unmanned aerial vehicle in a complex environment are comprehensively improved, so that the low-altitude operation unmanned aerial vehicle better meets the requirements for safety, efficiency and continuity in actual operation.

Examples relate to an adaptive AI coworker system for enhancing organizational operations. The system generates personalized AI coworkers based on role requirements, employing adaptive learning to understand unique organizational practices. It utilizes multi-agent coordination for complex task execution, automatically generating, prioritizing, and allocating tasks based on organizational context. The system integrates data from various sources, implementing data governance measures. Customized large language model instances are created for specific roles and organizations, incorporating organization-specific data and operational practices. The system provides explainable AI features for operational decision-making, ensuring transparency in critical tasks. Security measures and access controls are implemented to maintain data integrity and compliance with relevant regulations and standards.

The invention discloses an aircraft multi-target performance constraint collaborative optimization method based on multi-dimensional virtual and real parameter mapping, and the method comprises the steps: constructing a real parameter space and a virtual parameter space, and uniformly organizing the task key elements, such as target arrival, obstacle risk, formation maintenance error and minimum safety margin, into multi-dimensional real parameter input; speed scheduling quantity is uniformly organized into virtual parameters to be output, so that consistent parameter expression and a unified decision interface of cross-scene and cross-risk levels are realized, and engineering applicability and reusability in a task constraint scene are improved; interaction response data are obtained in a multi-scene set, a track sample set is established, and PPO reinforcement learning is adopted to train a mapping network from actual parameters to speed virtual parameters, so that the system does not need to explicitly construct complex manual rules or segmented threshold control logic; therefore, self-adaptive tradeoff can be formed among multiple targets such as arrival efficiency, formation keeping and speed stability, so that the manual parameter debugging cost is reduced, and the strategy generalization capability is improved.

The invention discloses a flexible manufacturing resource collaborative allocation optimization method and system oriented to variable delivery periods, and relates to the technical field of scheduling control, and the method comprises the steps: installing a process completion confirmation label in each work-in-process link, and directly obtaining an equipment load, a work-in-process state and the completion time; in combination with order arrival prediction and equipment health conditions, a disturbance intensity evaluation algorithm is set, the current scheduling disturbance quantity is calculated, and the disturbance intensity of each sub-problem is quantified; based on the disturbance intensity of each sub-problem and the longest response time of the system, setting an adaptive sub-problem time window algorithm, and dynamically adjusting the time window range of the to-be-rearranged task; and carrying out hierarchical division on the key tasks and the secondary tasks in the sub-problem range, carrying out parallel calculation and then carrying out merging scheduling to form an updated collaborative scheduling scheme. According to the invention, during order change, equipment failure or material shortage, the affected subset tasks can be quickly identified, the scheduling range is limited, global recalculation is avoided, and quick response is realized.

This invention belongs to the field of flight control computer hardware architecture technology, specifically relating to a heterogeneous flight control core circuit and system. This invention integrates a microcontroller unit and an artificial intelligence coprocessor unit on the same printed circuit board, achieving data and command interaction through isolated high-speed interconnect channels. The microcontroller unit constitutes the safety control and real-time decision-making domain, used to execute safety-critical and hard real-time tasks, and to implement operational management and fault isolation for the artificial intelligence coprocessor unit; the artificial intelligence coprocessor unit constitutes the intelligent sensing and computing domain, used to execute computationally intensive and non-real-time critical tasks. This architecture achieves decoupling and collaboration between the safety domain and the computing domain at the hardware level, ensuring both high functional safety and determinism in flight control, while fully releasing the high-performance computing power required for intelligent sensing, thus meeting the dual requirements of advanced aircraft for highly reliable flight control and intelligent function expansion.

A method of managing synchronization source (SSRC) conflicts in a critical task service (MCX) by a server device is provided. The method includes receiving a request message from one or more sender devices for requesting transmission of one or more media streams to one or more receiver devices during a session, determining a unique SSRC identifier for each of the one or more media streams, and transmitting the unique SSRC identifier associated with each of the one or more media streams to the one or more sender devices and the one or more receiver devices.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. Embodiments of the present invention relate to a method and system for managing an ad hoc group call in a mission-critical (MC) communication system. The method for managing an ad hoc group call in an MC communication system comprises a primary MC system (10) and a secondary MC system (30). A first MC service server (25) in the primary MC system (10) receives an ad hoc group call initiation request from a first MC service client (15) including MC service identifiers of target users. The first MC service server (25) invites a second MC service client (20) by forwarding the request using a service ID assigned by the secondary MC system (30). Upon detecting that a third user has migrated to the secondary MC system (30), the first MC service server (25) transmits a redirection notification to the first MC service client (15) including both the old and new MC service IDs and the migration reason. The first MC service server (25) sends an ad hoc group call response indicating success or failure with details, and the ad hoc group call is established across the included MC systems (10, 30, 50).

The invention discloses a multi-terminal parallel authentication authorization and equipment perception method for a key task communication system, which belongs to the technical field of key task communication, and specifically comprises the following steps: S1, configuration preparation: a server pre-configures a terminal initial configuration file for a terminal; the initial configuration file of the terminal comprises lt; m < cpt >-UE-idgt; element, lt; m < cpt >-UE-idgt; the elements comprise the next-level lt; the method comprises the following steps: carrying out Instance-ID-URNgt; an element; lt; the method comprises the following steps: carrying out Instance-ID-URNgt; the elements are instantiated to be unique identifiers by the configuration terminal; s2, configuration issuing and effectiveness: the server issues the initial configuration file of the terminal to the terminal, and the initial configuration file of the terminal is restarted to take effect through the terminal; s3, authentication and information reporting: the terminal initiates an authentication and service authorization request, wherein the request carries the result; the method comprises the following steps: carrying out Instance-ID-URNgt; an element; s4, service authorization and configuration issuing: the server receives the request, analyzes the terminal instantiation unique identifier, records analysis information, and determines whether to issue matched user configuration file data to the terminal; according to the invention, the terminal registration authentication process is deeply coupled with the terminal type and capability evaluation, and intelligent decision-making can be carried out based on terminal difference.

The embodiment of the invention provides an electronic information method and related equipment, and belongs to the technical field of electric power internet of things operating system management. The method comprises the following steps: acquiring system monitoring information; starting of a software high-precision timer and a hardware high-precision timer is controlled through a dynamic resource evaluation model according to system monitoring information; calculating clock cycle data corresponding to the sleep duration according to the system monitoring information, and if it is determined that the clock cycle data is smaller than a preset cycle threshold value, selecting to operate a shallow sleep mode; if it is determined that the clock cycle data is larger than or equal to the preset cycle threshold value, a deep sleep mode is selected to run; the shallow sleep mode is to keep a core clock running, and the deep sleep mode is to close a non-essential clock domain. According to the embodiment of the invention, the timing precision of the key task can be ensured, the overall energy consumption of the electric power internet-of-things operation system can be subjected to refined and adaptive management, and the resource utilization efficiency and the cruising ability can be improved.

This application discloses a task processing method, apparatus, device, storage medium, and program product, relating to the field of industrial internet technology. The method includes: updating the global ready state of task sets with dependencies on each terminal at scheduling time slot boundaries; calculating the scheduling priority of tasks in the global ready state and sorting them by scheduling priority to obtain a ready task list; wherein the scheduling priority of a task defines the criticality of the ready task; traversing the ready task list to generate a set of actionable actions for each ready task in the list; selecting candidate tasks based on the set of actionable actions; and selecting an execution position from the set of actionable actions of the candidate tasks and initiating execution. This solution not only ensures that critical tasks are executed first, reducing the risk of critical tasks being blocked by non-critical tasks, but also eliminates rollback and reselection due to infeasible decisions, significantly improving the stability and reliability of task scheduling in industrial scenarios and reducing end-to-end task processing latency.

The invention relates to the technical field of model deployment, in particular to a cloud aggregation AI model automatic arrangement system which comprises a task scheduling module, a compatibility analysis module, a framework matching module, a deployment optimization module and a scheduling intervention module. According to the method, the real-time load condition of the platform, the calculation requirements of the tasks and the pre-estimated execution time are comprehensively evaluated before task arrangement, and the execution sequence with the priority is dynamically constructed, so that priority processing of key tasks is ensured, and the overall utilization efficiency of calculation resources is improved; resource congestion and scheduling delay caused by simple queuing execution of tasks are avoided, success rate, error rate and performance data in historical execution records of the tasks are deeply analyzed in terms of deployment framework selection, compatibility judgment is formed by combining real-time performance feedback at the initial stage of deployment, and the task scheduling efficiency is improved. Furthermore, the structural features of the AI model are matched with the underlying capability of the frame, and the transformation from coarse-grained resource linkage to fine capability adaptation is realized.

The application discloses a kind of mission critical monitoring method, device and equipment and storage medium, the method comprises: obtaining task dependency relationship and baseline configuration information and the time information of each task in task dependency relationship;Time information includes scheduling time, running time length and actual start time and actual end time;Task dependency relationship is divided into several connected components;For each connected component, the earliest start time of each task is calculated according to scheduling time and actual start time;The earliest end time of each task is calculated according to the earliest start time and running time length and actual end time;According to each connected component and the earliest end time and baseline configuration information, the predicted completion time of each baseline and critical path are determined;According to predicted completion time and critical path and baseline configuration information, it is judged whether to carry out timeout early warning to each baseline.The method of the application can reduce the computing power of monitoring critical tasks, reduce invalid or repeated alarm.

According to an aspect, there is provided a computer- implemented method comprising the following Initially, number of terminal devices per cell for one or more cells is monitored. In response to detecting that the number of terminal devices within a cell is larger than a pre-defined threshold for a pre-defined amount of time, the following is performed. One or more neighboring cells of the cell are detected. One or more first terminal devices operating in any non-mission-critical operating mode in the cell or its neighboring cells are determined. A first set of values for radio transmission power control parameters for the one or more first terminal devices is determined. The first set of values is associated with lower terminal device transmit power compared to current default values. Configuration of the one or more first terminal devices to use the first set of values is caused.

With the development of technologies such as artificial intelligence, edge computing, and the Internet of Things, modern computing systems often need to run multiple computationally intensive tasks simultaneously. These tasks have different requirements for computing resources. Allocating dedicated resources to each task independently would lead to a surge in hardware costs and low resource utilization. Furthermore, in real-time systems such as robotics, autonomous driving, and industrial control, competition for computing resources among different tasks (such as perception, decision-making, and control) is also prominent. Existing real-time operating systems mostly use fixed-priority scheduling, which cannot dynamically adjust the computing resource configuration of tasks, resulting in delays or resource waste in critical task responses. This application provides a resource reuse method, system, and computer-readable storage medium, aiming to achieve efficient multi-task concurrent processing by dynamically scheduling computing units and actively releasing idle resources.

This invention provides a wireless communication device and method that offers low latency and high reliability in communication-based train control (CBTC). [Solution] The wireless communication device includes a transceiver set 120 and a control node 110 having a processor electrically connected to the transceiver set. The transceiver set communicates with a first base station via a first channel. The processor controls the transceiver set to transmit and receive mission-critical data with the first base station in a first communication mode, collect data other than mission-critical data from the first base station, and control the transceiver set to transmit delay-tolerant data, including the collected data, with the first base station in a second communication mode, and decides whether or not to switch the transceiver set from the first communication mode to the second communication mode based on the mission-critical data.

The present invention relates to geofenced Mission Critical Push-to-Talk (MCPTT) talk groups. A dynamically joinable MCPTT talk group can be created in response to a request from an administrator. The request can indicate a geofence within which members can communicate and that the group is joinable by users whose mobile devices are within the geofence. A location estimate of a mobile device can be received and the device can be determined to be within the geofence based on the location estimate. In response to the determination that the device is within the geofence automatically, a user of the device can be added to the MCPTT talk group without selective addition of the user by the administrator.

The invention discloses a distributed priority perception collaborative unloading algorithm based on multi-agent deep reinforcement learning. The algorithm comprises a vehicle-mounted edge computing (VEC) architecture supporting collaboration between edge servers; a distributed partially observable Markov decision process (De-POMDP) framework; the invention discloses a distributed priority awareness cooperative unloading (DPACO) algorithm based on multi-agent deep reinforcement learning (MADRL). The VEC architecture comprises a vehicle layer, an edge layer and a cloud layer; the De-POMDP framework comprises observation and state of a vehicle, vehicle behaviors and a reward function; the DPACO algorithm adopts a distributed SAC framework, and efficient task processing is realized through a shared VEC server pool and a queue perception priority mechanism. The algorithm overcomes the limitation of unloading of a single server, maximizes the utility of resources among a plurality of servers, realizes edge-to-edge collaborative operation, ensures low-delay service by a specially designed task priority mechanism, and particularly has a remarkable guarantee effect on key tasks.

A method for managing location reporting in a mission-critical (MC) service communication system is provided. The method includes receiving, by a location management server, a location reporting trigger from a first location management client device, wherein the location reporting trigger requests to override at least one existing location reporting trigger of the second location management client device, checking, by the location management server, whether the first location management client device is authorized to override the existing location reporting trigger of the second location management client device based on the location reporting trigger, storing, by a location management server, a current location reporting configuration for the second location management client device at a local storage, and initiating, by the location management server, an event triggered location reporting procedure for the second location management client device.

This application provides a method, apparatus, electronic device, medium, and product for voice conversation calls. The method includes: an MCX proxy server determining a target group from multiple pre-configured groups in an Interworking Function (IWF) whose first attribution information is information of interest; receiving a call request initiated by a first user terminal; and establishing a conversational call channel between the IWF and the Mission-Critical Service (MCX) based on the call request. Then, it receives voice information sent by the first user terminal and sends the voice information to the target group through the established conversational call channel, so that multiple second user terminals in the target group receive the voice information. This method, through the MCX proxy server, requires only one conversation between the IWF and the MCX to send voice information to multiple terminals, reducing bandwidth and conversation resource consumption.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. A method performed by a mission critical push to talk (MCPTT) server for handling in-progress imminent peril state in a communication system is provided. The method includes receiving a session initiation protocol (SIP) request message transmitted from an MCPTT client of an MCPTT group to cancel an in-progress imminent peril state of the MCPTT group, wherein the SIP request message includes an imminent peril indication being set to false, setting the in-progress imminent peril state of the MCPTT group to a value of false, clearing all MCPTT identification (ID) of MCPTT users that triggered the setting of the in-progress imminent peril state of the MCPTT group to true, transmitting a SIP notification message including an imminent peril indication set to false for each of affiliated members of the MCPTT group, and transmitting a response to the SIP request message.

The invention relates to an integrated soc industrial personal computer real-time scheduling method, system and device based on dynamic priority and a medium. The method comprises the following steps: collecting system state data of an integrated soc industrial personal computer, determining a potential available resource set by adopting a state quantification method based on the resource state data, and evaluating task priorities in combination with a dynamic priority evaluation rule to generate a task priority sequence; generating a preliminary resource allocation-scheduling path scheme according to a preset state space and an action space; deducing a resource allocation and scheduling path adjustment process by simulating a preset emergency scene to obtain an emergency scene simulation result; optimizing the preliminary scheme by adopting a priority-based compensation strategy to form an optimized resource allocation-scheduling path scheme; and generating a scheduling instruction to drive the integrated soc industrial personal computer to execute the task. By adopting the method, the real-time performance and the self-adaptive capability of resource scheduling can be improved, fluctuations caused by emergency scenes can be effectively dealt with, key tasks are ensured to be executed preferentially, and the overall efficiency and reliability of a system are improved.

The invention relates to the technical field of computer networks and communication, and discloses a network calculation-based key task system network end-to-end delay analysis method, which comprises the following steps of: modeling network equipment by adopting a pNC-QQU method; abstracting a processing unit jointly formed by at least one data queue and at least one quality of service (QoS) strategy associated with the data queue into an independent QQU (Quality of Service) unit in the network equipment; using a pNC-QoSTree method to construct a QoS strategy tree for describing the work logic of the complex QoS strategy in each QQU unit for each QQU unit; traversing each QQU (Quality Quality Unit) passed by the to-be-analyzed service flow f on the path R; for each QQU unit, respectively calculating an arrival curve and a service curve of the service flow f in the QQU unit based on the QoS strategy tree constructed by the QQU unit, and calculating according to the arrival curve and the service curve to obtain a local delay upper bound Dq of the service flow f passing through the QQU unit; and for each network device passing through the service flow f, superposing the local total delays Dd of all network devices on the path R to obtain an end-to-end delay upper bound of the service flow f. According to the invention, the network modeling difficulty of a user can be reduced.

A communication method and system for converging a 5th generation (5G) communication system for supporting higher data rates beyond a 4th generation (4G) system with a technology for Internet of things (IoT) are provided. The communication method and system includes intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. The method includes receiving and selectively applying at least one of a first set of random access prioritization parameters, a second set of random access prioritization parameters, or a third set of random access prioritization parameters, based on whether a random access procedure is initiated for beam failure recovery or handover.

This management apparatus comprises: an acquisition unit that acquires an execution request for requesting execution of one of a plurality of QoS controls; and a quality control unit that, when resources for executing a QoS control of a start candidate indicated by the execution request are not insufficient, executes the QoS control of the start candidate, and that, when some or all resources are insufficient due to ongoing execution of one or more QoS controls other than the QoS control of the start candidate among the plurality of QoS controls, determines whether to execute the QoS control of the start candidate, on the basis of the execution priority order of the QoS control of the start candidate and the execution priority order of the currently executed QoS controls.

The invention provides a conversational AI task execution method and system based on a state diagram, and the method comprises the steps: S3, extracting node conversion logic from a part of the state diagram, judging a priority path guided by a task in combination with the intention of a user, and determining the segment content guided by the next task; s6, extracting a key task instruction from the generated guide information, judging whether the user deviates from an expected path or not in combination with a real-time feedback processing result, and regenerating the corrected partial state diagram if the user deviates from the expected path; s8, extracting user response data from the final task guide content, judging the understanding degree of the guide content by the user in combination with semantic analysis, and generating updated user interaction adaptation parameters; and S9, regenerating the next round of partial state diagram through the updated user interaction adaptation parameters, and outputting the dynamically adjusted task guide information. The task completion rate and the interaction experience of the user are remarkably improved, and the method is particularly suitable for complex multi-stage task scenes.

An apparatus having a mission critical operating environment container architecture includes a plurality of processor cores incorporated in at least a computing device and a memory communicatively connected thereto and containing instructions configuring at least a to deploy an operating system on the computing device, configured to receive a software module to be executed on the at least one multi-core processor, determine an initial resource allocation for the software model, wherein the initial resource allocation includes a memory allocation, create a virtual environment for the at least a software module by generating a virtualization layer and allocating a memory space through the virtualization layer in the memory according to the memory allocation, integrate the software module into the virtual environment by instantiating the software module into at least one software container, wherein the at least one software container comprises a plurality of dedicated software packages, and execute the container.

The application discloses a jitter detection method for a key task process in an operating system, and comprises the following steps: sending a starting signal to each process state parameter monitoring module in a kernel layer by a jitter detection module in a user layer during operating system running; wherein each process state parameter monitoring module is a monitoring module for process state data of a corresponding category; collecting process state data of a corresponding category by each process state parameter monitoring module, and screening target process state data corresponding to a key task process from the collected initial process state data; and performing jitter detection on the key task process according to the target process state data by the jitter detection module. The application greatly reduces time consumption and complexity, and improves the efficiency and accuracy of the analysis of the causes of task process jitter. The application also discloses a device, equipment and storage medium, which have corresponding technical effects.

A mission critical push to talk (MCPTT) server may comprise at least one processor. The at least one processor is configured to establish a call connection between an MCPTT calling device and an MCPTT device by: receiving, from the MCPTT calling device, a call request message including information about a zone; monitoring whether location information about at least one MCPTT device is received in the zone indicated by the call request message of the MCPTT calling device; in response to receiving the location information about the MCPTT device in the zone, transmitting a call request message of the MCPTT server to the MCPTT device; in response to the call request message of the MCPTT server, receiving a call response message from the MCPTT device; and in response to the call request message of the MCPTT calling device, transmitting a call response message of the MCPTT server to the MCPTT calling device.