1899 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.

Embodiments provide methods and systems for temporal graph representation learning based on node-level temporal point processes. Method performed by the server system includes accessing historical interaction data, generating temporal graph based on historical transaction data and predicting likelihoods of future interaction occurrences among entities based on a pre-trained TPP based graph neural network (GNN) model. Method includes determining edge embeddings of each node based on node features of each node and direct neighbor nodes of each node. Method includes generating edge-contextualized node embeddings of each node corresponding to the edge embeddings based on a neural network model and computing a likelihood of future interaction occurrences associated with the each node based on edge-contextualized node embeddings and a conditional intensity function. Method includes executing at least one of a plurality of graph context prediction tasks based on likelihoods of future interaction occurrences among entities.

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.

Embodiments of the disclosure discloses a service management system, a service management method, a device and a storage medium. The system includes a server, a plurality of devices, and a plurality of clients establishing a communication connection with the plurality of devices; the server is configured to receive a service execution request, determine a target client from the plurality of clients based on an identifier of a target client comprised in the service execution request, and forward the service execution request to the target client; and the target client is configured to parse service information comprised in the service execution request, determine a target device corresponding to the service information from the plurality of devices, generate a driving instruction for the target device by invoking a target device driving service of the target device, and drive the target device with the driving instruction to respond to the service information.

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 discloses a high-concurrency data cache sorting method and system, and the method comprises the steps: carrying out the time synchronization of a system server and a subsystem server, building a first-level cache and a second-level cache, and setting a double-buffer queue for the second-level cache; a plurality of threads receive high-concurrency data and distribute different thread groups for processing, a local timestamp and a serial number are set to be combined into a primary key, the primary key and a data value v are written into a first-level cache, and an index is established. A thread pool 1 is started to read data from a first-level cache and write the data into a second-level cache, and corresponding processing including discarding repeated data, writing the data into different buffer queues and the like is carried out by judging conditions such as a sequence number and a data value v. Meanwhile, a thread pool 2 is started to read the data from the second-level cache double-buffering queue in sequence and delete the cache, and if a specific situation is encountered, a threshold value is waited for or next data processing is continued. And the index and the cache queue content can be expanded to realize processing in a plurality of protocol modes, so that the data access efficiency is improved, the data completeness can be realized, and the conditions of data disorder and dirty data cannot occur.

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 invention provides a memory page exchange method and system for a microkernel operating system. The memory page exchange method comprises the following steps: step 1, running an exchange page management system service in a user mode of the microkernel operating system; step 2, providing data encapsulation and transmission for communication between user state system services; 3, generating an exchange page identifier, and registering a virtual address area used for transmitting data, a data buffer area and a thread for processing a missing page error to the kernel; 4, when the page is swapped out, the kernel modifies the service page table of the swap page management system, and the physical page needing to be swapped out is mapped; 5, when the page is swapped in, according to the swap page identifier obtained from the page table when the missing page error is triggered, the specified page data content is read from the swap area to the data buffer area; and step 6, packaging each interface of the exchange page management service. According to the invention, by utilizing the page table mapping, the memory copying times in the exchange process under the microkernel architecture are effectively reduced, and the operation efficiency of the exchange system is improved.

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 belongs to the technical field of solid fuel cells, and particularly relates to a hybrid-driven SOFC (Solid Oxide Fuel Cell) combined heat and power system service life prediction method, which comprises establishment of an SOFC system dynamic attenuation model and establishment of a hybrid-driven SOFC system service life prediction model. The service life of the system is predicted by simulating the dynamic attenuation of the SOFC combined heat and power system and performing machine learning, so that the performance of the whole SOFC combined heat and power system is predicted, and the influence of the interaction of each component on the service life of the system under the long-time operation of the system is analyzed. The method is short in test time and high in accuracy, the cost is saved, and the research and development progress is accelerated; an important reference basis is provided for long-life operation of the system, the influence of BOP parts on the whole life of the system can be clearly analyzed, and a direction is pointed out for the long-life operation of the system; and a machine learning method is utilized to avoid accidental results possibly existing in single simulation, so that the results have universality.

The invention discloses a mainboard, a mainboard system, a server, a node interconnection structure and a server system, and relates to the technical field of data transmission. The first connector is located at one end of the main board, so that a processor arranged on the main board transmits data to the first connector through a bus protocol in the main board to realize data transmission between the processor and the first connector. The data transmission is directly realized from the inside of the mainboard without cable routing, and if the data is used as a second node in the node interconnection structure, the interface space of the processor is also reduced. The first connector is connected with the connector assembly through the plugging part arranged at one end of the connector assembly, so that plugging connection between the processor and the connector of the connector assembly is realized, and subsequent data can be conveniently transmitted to other equipment. The plugging part is arranged at one end of the connector assembly, pluggable connection in a plugging mode is achieved between the connector assembly and the first connector, the whole mainboard does not need to be disassembled and assembled, the connector assembly is replaced only in the plugging mode, and operation steps are simplified.

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.

The invention relates to a structured extraction method and system for electric power overhaul data based on a large model. The method comprises the following steps: collecting and processing original electric power overhaul data; loading and analyzing the standardized naming mapping table of the power system equipment; configuring and calling a large language model, and performing feature extraction on the preprocessed to-be-analyzed text to obtain structured information of a target field; performing semantic similarity calculation based on vector embedding to obtain a corresponding preliminary matching result; further calculating the preliminary matching result according to a standardization algorithm, and establishing a standardization mapping index table of the current plant station and each level of equipment in the station; and the standardized mapping index table is integrated and packaged into a system service or offline file form to be output. According to the method, efficient and accurate structured extraction and standardized processing of electric power overhaul data are realized, complex unstructured text input can be processed, and extracted information is accurately corresponding to standardized equipment and station names through semantic understanding and a multi-stage matching mechanism. The process greatly improves the automation degree and accuracy of data processing.

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.

Aspects of the disclosure are directed to methods and systems for short form previews of long form media items. A server can provide, to an artificial intelligence (AI) model, a long form media item to be shared with users. The server can receive, from the AI model, one or more frames that are predicted to contain content that is of interest to the users. The server can extract a segment of the long form media item that corresponds to the one or more frames, where the extracted segment corresponds to a short form media item preview. The short form media item preview can be provided for presentation to the users.

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.

The invention discloses a telecommunication system service authorization method, and relates to the technical field of optical communication, and the system comprises the following components: S100, a user behavior data acquisition and analysis module, S200, an AI learning engine, S300, a personalized authorization strategy generation module, S400, a dynamic adjustment and feedback mechanism, and S500, a safety guarantee mechanism. According to the method, the diversified behavior data of the user is collected and analyzed in real time, the accurate user behavior portrait is constructed, and the prediction capability of the AI learning engine is combined, so that the future service demand of the user can be intelligently predicted, and a personalized service authorization strategy is generated according to the future service demand; according to the method and the system, telecommunication services which better meet the actual requirements of users can be provided for the users, the user experience is improved, the accuracy of service authorization can be ensured, unnecessary resource waste is reduced, and the service efficiency of operators and the customer satisfaction are improved.

According to the robust beam forming method for the AN enhanced RIS assisted physical layer security communication, the transmitting power of a base station is minimized on the premise that the system service quality requirement and the security rate outage probability constraint are met. The method comprises the following steps: firstly, constructing a security rate interruption constraint based on a base station-RIS-eavesdropper cascade channel transmitting end imperfect CSI model, and then approaching a security rate interruption probability constraint by using a Bernstein inequality, thereby reexpressing an original problem as a processable convex constraint. Under an alternating iterative optimization framework, positive semi-definite relaxation is utilized to convert a sub-problem into a convex problem, a sub-optimization problem of a given beam forming vector optimization RIS phase shift matrix is rewritten, a slack variable is introduced to re-express an original feasibility verification problem, and finally a base station transmitting beam forming vector is iteratively optimized. The AN beam forming vector and the RIS reflection beam forming matrix improve the system safety rate and the system robustness.