1302 results about "System service" patented technology

The invention discloses a computer system service optimization scheduling method for a photoelectric system, and particularly relates to the technical field of computer service optimization, which comprises the following steps of: sensing and extracting information such as task types and time constraints through task characteristics, and constructing a multi-dimensional resource model such as processing capability and idle degree by combining resource modeling; a weighting mechanism is used for evaluating task priorities and generating a scheduling queue, tasks are dynamically mapped to matched resources, a scheduling strategy is adjusted according to system loads and feedback, model parameters are optimized through service feedback, and efficient, self-adaptive and intelligent optimization of task scheduling of the photoelectric system is achieved; according to the method, a dynamic scheduling mechanism based on task characteristics and resource prediction is realized, and the response speed of the high-optimal task is improved; optimizing the resource utilization rate by adopting resource state modeling and prospective mapping; and reinforcement learning and a feedback closed loop are introduced, a sustainable optimization scheduling system is constructed, and the adaptability and stability of the system in a complex photoelectric task environment are enhanced.

The invention discloses a cross-container application fusion switching method of a swan monk system, which comprises the following steps: a system service layer deploys a container application management service, an application framework layer realizes a proxy application manager, when a container application is started, a container side allocates a shared memory and configures authority, the container manager collects metadata to initiate registration, and the application framework layer realizes a proxy application manager; the container application management service converts a memory handle into a texture handle, allocates a unique identifier and triggers a proxy application manager to generate a proxy application, and the proxy application initializes a Vulkan rendering environment; the container side renders an application interface to a shared memory, the proxy application imports texture and constructs a lightweight Vulkan rendering pipeline, and scaling sampling is carried out to generate a thumbnail of the container application; and when the container application exits, the shared memory is released, the container application management service cleans the shared memory reference, triggers and destroys the proxy application, and recycles the texture resources through the reference counter, so that seamless fusion, low-delay switching and efficient resource utilization of the container application in a native application thumbnail form are realized.

The invention relates to the technical field of road condition intelligent perception and application, in particular to a road condition adaptive topology perception and application system and method. A condition cluster perception module monitors road condition parameters in real time; the data transmission communication module realizes differential data transmission strategies; a road section dynamic risk grade evaluation module calculates a road section risk index and grade according to the road structural state parameters and a risk evaluation model; the node adjustment and resource allocation module adjusts the activation state and sampling frequency of each sensor according to the road section risk level, simulates and verifies the implementation effect of a resource allocation scheme under different road section risk levels by using a constructed road system digital twin model, and optimizes the resource allocation scheme by using a multi-objective optimization algorithm; the application service module converts the risk level into a specific service action; the cooperative operation of the modules realizes the flexible allocation of road condition perception, communication and computing resources, and improves the utilization efficiency of the resources and the service efficiency of the system.

The invention discloses a power equipment data acquisition and processing system, which comprises a multi-protocol compatible acquisition module, an intelligent network detection module, a system service performance monitoring module and a high-concurrency processing module, the multi-protocol compatible acquisition module is responsible for adaptation and data acquisition of different power equipment protocols and normalization processing of the acquired data; the intelligent network detection module monitors a network link state, diagnoses a network fault reason and pushes fault information in real time; the system service performance monitoring module collects key performance indexes of a server, displays performance data through a visual interface, and triggers an alarm when the indexes are abnormal; the high-concurrency processing module compresses the collected data, realizes efficient pushing and priority processing of the data through a message queue, and guarantees the data processing efficiency in a high-concurrency scene; comprehensive monitoring of power equipment communication and system performance is realized, and data acquisition efficiency and system reliability are improved.

The invention discloses a dynamic load balancing optimization method for AI intelligent computing system server equipment, which relates to the technical field of load balancing optimization, and comprises the following steps: acquiring equipment performance data, and preprocessing the acquired equipment performance data; based on the preprocessed equipment performance data, extracting equipment state features through time sequence analysis and periodic fluctuation detection; predicting the future load change of the equipment based on the state characteristics of the equipment, dividing the priority of the equipment according to the prediction result, and analyzing the resource demand; generating a resource allocation strategy by applying a resource matching algorithm according to the device priority and the resource demand; and executing the resource allocation strategy, receiving feedback information in real time in the execution process, and optimizing the resource allocation strategy according to the feedback information. According to the method, the response speed and the service quality of the server equipment are remarkably improved, and the resource utilization efficiency is maximized.

Methods and systems for managing services provided by a data processing system are disclosed. A service of the services may be managed by accounting for other services and dependencies on which the service of the service relies. To account for the other services, the dependencies may need to be validated. To validate the dependencies, the other services may be checked to see if they are implemented. If the other services are not implemented, the other services may be supplemented. Otherwise, the other services may be validated and therefore the dependencies may be validated. Once the other services and the dependencies are validated, then a service of the services may be deployed.

The invention discloses an intelligent government affair service platform and a data processing method applied by the intelligent government affair service platform, and relates to the technical field of government affair service management, and the method comprises a public configuration module which is used for carrying out hierarchical configuration on system service capability according to a configuration instruction, and the hierarchical configuration comprises capability application management configuration, public template configuration and service model configuration; the service model configuration comprises a service overall planning model and a service implementation model; the reservation rule engine module comprises multi-level reservation rules of a hall reservation rule, a special area reservation rule and an item reservation rule, rule parameters can be dynamically adjusted, and the multi-level reservation rules comprise a reservation time period, a government affair service number allocation strategy and a conflict detection mechanism; the business handling module is used for realizing automatic material verification and document generation in a certificate-free business scene; and carrying out data interaction with an external system through the capability application management module, and carrying out system service capability authorization. The service efficiency of government affair services is improved, and the government affair handling experience of the masses is improved.

The invention relates to the technical field of computers, in particular to a server running state monitoring method and system and a medium. The method comprises the steps of obtaining time sequence operation and maintenance data of a system service; the method comprises the following steps: mapping an unstructured log text into a low-dimensional dense text vector by adopting an embedded learning method, splicing the text vector and a standardized numerical vector of a structured index to obtain a unified high-dimensional feature vector, and forming a cross-time vector database; constructing an AI model used for time sequence prediction, anomaly detection and cascade reasoning of classification decision based on a multi-model fusion architecture; training the AI model based on the vector database; and inputting the real-time feature vector into the trained AI model, and outputting to obtain a decision result of the system service operation state. Uniform expression of cross-modal features is effectively realized, cascade model architecture design is cooperated, the dynamic adjustment capability of the model and the accuracy of composite fault detection are improved, and rapid decision-making of fault types is realized.

The present disclosure relates to methods and systems based on a transformer model, in which an elastic transformer service system, referred to herein as an online lexical adaptation system (OTAS), is involved that accommodates diversified user requests with fluctuating query loads, while optimizing output accuracy and runtime delay. The OTAS uses lexical adaptation techniques that involve adding cue lexical elements to improve accuracy and removing redundant lexical elements to accelerate reasoning. To handle fluctuating query loads and diversified user requests, the OTAS also applies a perceptual selective batch processing algorithm for online lexical adaptive design. In a system service process, OTAS firstly processes incoming queries with similar requirements in batches to improve ingress throughput. Then, in order to balance between the overhead of lexical element growth and the potential of improving accuracy, OTAS adaptively adjusts lexical element execution settings by solving an optimization problem.

The invention discloses a firmware upgrading method and system, a server, equipment, a medium and a product, relates to the technical field of servers, and does not enter a memory of a management controller so as to wait in at least one network equipment buffer area as long as there is no response of an input instruction. When the incoming instruction is responded, at least one data block with the preset size is intercepted from at least one waiting data packet, verification processing is carried out in the form of the data block, the whole firmware mirror image file does not need to be verified, and the granularity of a verification object is reduced so as to save memory resources of the management controller. The method comprises the following steps of: checking and comparing target data blocks obtained by segmenting a second mirror image file stored in a flash memory, abandoning the data blocks when the checking results are identical, and writing the data blocks into the flash memory when the checking results are different, so that repeated writing in the flash memory is avoided, the storage space occupation of the flash memory is reduced, and the storage efficiency of the flash memory is improved. And the memory space utilization rate of the management controller is improved.

The invention provides an automatic vulnerability processing method and system.The method comprises the steps that multi-source heterogeneous data and temperature field distribution of a target system are obtained, vulnerability data and historical repair records are subjected to semantic association, and vulnerability propagation path features are generated in combination with a dynamic dependency chain; and identifying a hardware load abnormal region by matching the temperature field distribution with a thermodynamic mode of known vulnerability attacks. And based on a dynamic graph attention mechanism, collaboratively analyzing vulnerability propagation path characteristics and hardware abnormal data, and generating a patch deployment strategy which comprehensively considers the repair priority and resource allocation. In the execution process, the topological sequence and the data throughput of patch distribution paths are dynamically adjusted, the resource occupation proportion is optimized, and it is ensured that the cross-system service interruption duration is controlled within a safety window. According to the method and the device, the vulnerability repair accuracy and the system stability are improved.

A system and method comprising collecting analytics data or other types of analytics-related information from client devices in an anonymous and authenticated manner. A client device may use or provide a token or token-relation information, which may have been obtained from system servers beforehand, with a request to log the analytics data to the system servers in order to authenticate the analytics data being logged. The system servers may then authenticate the token or the token-related information, and in response to successful authentication, process the analytics data. Advantageously, the use of the token or token-related information allows the analytics data to be logged by client devices anonymously to preserve privacy, but also in a highly secure manner.

The invention provides a signal exception processing method and system, a server and a storage medium, and relates to the field of servers, the method is applied to the signal exception processing system, the signal exception processing system comprises a substrate management controller and a hardware extension module, and the hardware extension module is used for performing function extension on a central processing unit and a universal input and output interface. Wherein the substrate management controller does not immediately respond to the signal sent by the hardware extension module, but can firstly take the signal as a to-be-detected signal, and detect the signal according to a preset signal parameter to determine whether the signal form is abnormal or not. And if the to-be-detected signal is determined to be abnormal, in order to distinguish whether the to-be-detected signal is a normal signal, the substrate management controller can also actively acquire a register value corresponding to the signal from the hardware extension module, and determines whether to respond to the to-be-detected signal according to whether the logic meaning of the to-be-detected signal is consistent with the logic meaning of the register value. In this way, signal abnormity can be actively detected, and error response can be avoided.

The airport available runway monitoring and early warning system and method based on multi-source data fusion are high in real-time performance, good in forecasting effect and large in monitoring range. The system comprises a laser wind finding radar (1), a CFD numerical simulation module (2), a mesoscale weather forecast module (3), a machine learning model (4) and a system server (5). The method comprises the following steps that: a system server performs data assimilation by combining real-time wind shear detection data measured by a laser wind measurement radar and forecast data of a current time point output by a mesoscale weather forecast module, processes the assimilated data by applying a CFD numerical simulation module, and calculates the real-time wind shear detection data by combining terrain and building parameters near an airport; according to the method, real-time sub-meter gridding three-dimensional wind field data is generated, and a sub-meter three-dimensional wind field structure is reconstructed, so that future wind shear of an airport is forecast and early warned, and then available runway prediction is carried out. The method is applied to the technical field of wind field prediction and judgment.

The present application belongs to the technical field of system service health level evaluation. Disclosed are a service health level evaluation method, an electronic device and a readable storage medium. The method comprises: in response to collected state monitoring data of a distributed system, acquiring target operation state information, which matches the state monitoring data, among multiple pieces of operation state information of a service health level evaluation model; on the basis of a causal relationship between the respective ones of the multiple pieces of operation state information, determining associated operation state information having a direct causal relationship or an indirect causal relationship with the target operation state information; and determining associated data, which matches the associated operation state information, in the state monitoring data, and determining a service health level of the distributed system on the basis of the associated data.

The invention discloses a power supply system, a server, a fault detection method, equipment and a storage medium, and relates to the technical field of servers, a first electronic switch and a fault processing circuit are arranged on a mainboard, and the reliability and complete fault record of the system can be ensured under the condition that a standby power supply fails. Specifically, when a first standby power supply provided by the power supply distribution board through the first electronic switch is abnormal, the first electronic switch is turned off, and the fault processing circuit can continue to work after the standby power supply breaks down, so that accurate and complete recording of fault information is realized, and data support is provided for subsequent fault reason analysis; therefore, the to-be-tested power supply can be effectively monitored.

Provided in the embodiments of the present application are a server system, a resource scheduling method for a server system, and a chip and a chiplet. The server system comprises: a multivariate computing resource pool, a data storage resource pool, a switching module and a control module, wherein the multivariate computing resource pool comprises a general computing resource pool and a heterogeneous computing resource pool, the general computing resource pool comprising a group of general computing units, and the heterogeneous computing resource pool comprising a group of heterogeneous computing units, and the multivariate computing resource pool is connected to the data storage resource pool via the switching module by means of a cache consistency bus inside the server system; the data storage resource pool comprises data storage resources allowed to be shared by multivariate computing resources in the multivariate computing resource pool; and the control module is configured to perform computing power scheduling on the multivariate computing resources in the multivariate computing resource pool, and dynamically allocate the data storage resources in the data storage resource pool to the multivariate computing resources in the multivariate computing resource pool.

A distributed task scheduling system based on RabbitMQ, Redis and MongoDB. The task scheduling system comprises a task system service, Redis, MongoDB, RabbitMQ and an SDK, wherein the task system service comprises a data and object storage management module, a message queue management module, a task management module, a timing task module and a workflow module. By means of the design of a task system service, Redis, MongoDB, RabbitMQ and an SDK, the functions of an asynchronous task, a timing task and a workflow in a distributed and micro-service environment are provided. By means of the technical solution of a message queue, trigger-based scheduling of a task is realized, and a reliable and unique task scheduling capability exists; moreover, a timing task trigger capability exists, and thus the present invention is suitable for a scenario in which the execution of a certain task is triggered in a timing or delayed manner; a workflow capability is provided, and thus serial and parallel execution of a plurality of tasks can be performed; and capabilities such as task rollback and interruption are provided, and thus a system which unifies the asynchronous task, the timing task and the workflow is achieved.

The invention relates to the technical field of ecological system service function evaluation. The invention relates to a frequency offset correction algorithm in HPLC (High Performance Liquid Chromatography) + HRF (High Radio Frequency) dual-mode communication. The method comprises the following steps: S1, collecting phase sequence data from an HPLC communication link, collecting frequency offset estimation data and corresponding confidence data from an HRF communication link, and adaptively adjusting a preset detection threshold value of the phase sequence data according to the confidence data; s2, performing pulse abnormal sample point detection and elimination on the phase sequence data according to the adjusted preset detection threshold value; according to the method, the detection threshold is dynamically adjusted through the confidence data, so that the anomaly detection process can be matched with the current interference environment in real time, the integrity of the phase sequence data is maintained, and the problem of insufficient adaptability of a fixed detection threshold in an electromagnetic interference dynamic change scene is solved; and a more reliable phase data basis is provided for subsequent interpolation compensation and frequency offset estimation, so that the frequency offset correction precision of the dual-mode communication system is improved.

The invention discloses a server configuration method and system, a server, equipment and a medium, and relates to the technical field of computers.The method comprises the steps that a configuration file sent by a front-end tool is received and analyzed through a unified configuration service interface, and a to-be-configured item and to-be-configured information corresponding to a current configuration event are obtained; obtaining an execution topological structure chart matched with the current configuration event; according to the execution topological structure diagram, sending a modification instruction carrying to-be-configured information to a to-be-configured module in a server; and according to a preset event atomization configuration rule, if any to-be-configured module runs abnormally, rolling back each to-be-configured module corresponding to the current configuration event to the previous configuration version. Centralized management of configuration is realized through a unified configuration service interface; and through the event atomization configuration rule, the consistency of the overall configuration state is ensured. The problem that the current configuration automation degree is low can be solved, and the effect of improving the configuration automation degree and the configuration efficiency is achieved.

Systems, devices, and methods are provided for cryptographic co-dependent across multiple roots of trust. A device may comprise two or more co-dependent roots of trust, such as a trusted execution environment (TEE) of a main application processor and a cryptographic subsystem comprising a cryptographic processor. A server may validate digital signatures generated by each co-dependent root of trust that is known for the device and then provide the device with cryptographic material that can be used to establish a shared secret. The shared secret may be used by the device to request the performance of a sensitive operation.

The invention discloses an architecture system applied to embedded system development, and relates to the field of embedded system development, and the architecture system comprises an application layer which is used for executing business logic in an embedded system and managing the configuration of the embedded system, and the application layer is developed by adopting a Lua script; the hardware abstraction layer provides a unified hardware access interface; and the virtualization interface layer is used for providing a uniform interface for the application layer, so that the application layer can access the hardware resources of the hardware abstraction layer and call the system service in the embedded system. According to the method and the device, the problem that cross-platform transplantation is difficult due to the fact that a C language direct programming mode is adopted in an embedded system in the related technology is solved.

The invention discloses a system, a server, a method, a medium and a program product for sharing a memory resource pool, and relates to the field of artificial intelligence, a plurality of switching components of a switch are connected with processors of a plurality of computer devices and the memory resource pool, and the plurality of computer devices share memory resources of the memory resource pool through the switch, different memory capacities are allocated according to the requirements of the computer equipment, dynamic allocation and efficient sharing of memory resources are achieved, the memory utilization rate of a whole machine system is improved, the memory access delay of the computer equipment is reduced, the memory sharing consistency of multiple pieces of computer equipment is ensured, and the requirements of multiple computing scenes are met. Therefore, the technical problems that in the prior art, a server cooperative computing method based on the remote direct memory access (RDMA) technology is large in transmission delay, the requirements of various computing scenes cannot be met, the consistency of shared memories of multiple computer devices cannot be guaranteed, and the resource utilization rate is low are solved.

The invention provides a liquid cooling leakage detection system and a liquid cooling cabinet, and relates to the technical field of data center cooling. The system comprises a cabinet liquid leakage detection system, a server liquid leakage detection system and a liquid cooling control system, the cabinet liquid leakage detection system comprises a cabinet bottom plate detection sensor array arranged at the bottom of the liquid cooling cabinet and used for monitoring the liquid accumulation state in the liquid cooling cabinet in real time and generating a liquid accumulation signal; the server liquid leakage detection system comprises a cold plate detection unit of a cold plate arranged in the liquid cooling server and used for monitoring the cooling liquid leakage state of the cold plate in real time and generating a leakage signal of the cold plate; and the liquid cooling control system is in communication connection with the cabinet liquid leakage detection system and the server liquid leakage detection system, and is used for receiving and responding to the liquid accumulation signal and the leakage signal of the cold plate, generating alarm information and triggering a control instruction of corresponding control processing. According to the invention, the accuracy of liquid leakage detection is improved, so that the probability of missed detection is reduced.

The invention relates to a parallel computing framework based on software definition and an implementation method thereof, the parallel computing framework comprises an operating system domain, a system service domain and a unified interface domain, and the operating system domain comprises equipment drive, task scheduling, signal management, memory management and various protocol stacks; the system service domain comprises a data plane, a control plane and a capability plane, and the data plane is responsible for loading, forwarding, mapping and exporting all data; the control plane is responsible for calculation task preprocessing, load separation, scheduling distribution, dynamic reconstruction, calculation scheduling and task estimation functions and supports expansion customization; the capability plane is mainly responsible for computing node capability registration, capability reconstruction, operator management, capability management and failure detection functions in the system; the unified interface domain has the functions of distributed calculation, model training, model reasoning and resource management. The problem of parallel computing efficiency under a resource-limited embedded heterogeneous system platform is solved, so that computing resources have dynamic self-organizing reconstruction capability according to computing requirements.

The invention belongs to the technical field of radio wave propagation, and particularly discloses a three-dimensional FDTD complex path ASF prediction method based on multiple GPUs. According to the method, the three-dimensional FDTD algorithm is realized through multiple GPUs, and the method is used for predicting the ASF on a complex path. The method comprises the following steps: firstly, preprocessing parameters, and copying the parameters to a device end, namely a GPU end; secondly, updating an electric field component in the whole calculation area; then updating the field source, and exchanging the electric field components # imgabs0 # and # imgabs1 # on the adjacent GPUs; updating the magnetic field component in the whole calculation area; and finally, circulating and judging an end condition, and outputting the ASF when the calculation is finished. The method solves the problem of poor ASF prediction precision caused by the fact that a two-dimensional time delay prediction method cannot consider the transverse effect, overcomes the defect that a traditional three-dimensional FDTD method is difficult to simulate large-area low-frequency ground wave propagation, and provides a theoretical basis and technical support for improving the service precision of a low-frequency radio navigation time service system.

According to embodiments of the present disclosure, a system includes: a microkernel having a low-level application programming interface (API) and providing memory protection domains to user-level processes; and an abstraction layer running on top of the microkernel and comprising a plurality of service extensions to the microkernel and configured to provide a high-level operating system (OS) API for use by one or more application processes running in user space, wherein different ones of the service extensions are configured to run within different ones of the memory protection domains provided by the microkernel.

The invention relates to the technical field of computer information, in particular to a joint combat target system data service system based on a large model. The system comprises a target system data processing module, a combat target feature fusion module, a combat relation knowledge graph construction module and a combat system service early warning module, and can obtain joint combat target system data and perform format classification division and target cleaning processing to obtain joint combat target system standard data; performing feature fusion mapping on the standard data of the joint combat target system to obtain combat target system fusion feature vector representation; and performing entity identification and relation extraction on the combat target system fusion feature vector representation, performing relation combination weight graph construction and combat service query and situation early warning analysis, generating combat situation early warning information, and providing a corresponding joint combat coping strategy suggestion scheme. According to the invention, the data processing and combat service mode of the joint combat target system can be innovated by using a large model technology.

Embodiments provide artificial intelligence methods and systems for evaluating vulnerability risks of issuer authorization system. Method performed by a server system includes accessing a set of payment transaction data including subset of fraudulent transaction data. Method includes generating via a machine learning model, set of synthetic transaction data based on the subset of fraudulent transaction data. Method includes accessing set of historical card velocity features and collating the set of synthetic transaction data and the set of historical card velocity features to generate set of enriched synthetic transaction data. Method includes extracting via a classifier, subset of feasible fraudulent transaction data from the set of enriched synthetic transaction data. Method includes generating simulated authorization model based on the set of payment transaction data. Method includes classifying via simulated authorization model, each enriched synthetic transaction from the subset of feasible fraudulent transaction data as one of fraudulent transaction and non-fraudulent transaction.

The invention discloses a multi-unmanned aerial vehicle cooperative auxiliary mobile edge computing task scheduling method and system, and belongs to the technical field of edge computing and intelligent scheduling, and the mobile edge computing task scheduling method comprises the following steps: obtaining the position information and computing task characteristics of a ground mobile terminal in a current time slot, performing preliminary task shunting according to the task data size and a preset threshold value; constructing a joint optimization model, and performing joint optimization on a two-dimensional track, a computing resource allocation strategy and a task migration decision of the unmanned aerial vehicle by taking minimization of total processing time delay of system tasks as a target; the optimization problem is solved by adopting a mixed action multi-agent deep reinforcement learning algorithm, the problem of complexity of multi-unmanned aerial vehicle cooperative scheduling in a dynamic environment is effectively solved, the task processing time delay is remarkably reduced, and the edge resource utilization rate and the system service continuity are improved.