160 results about "Service load" patented technology

The invention discloses a micro-service dynamic weight load balancing method and related equipment. The method comprises the following steps: asynchronously acquiring a multi-dimensional real-time load index of a micro-service instance, obtaining a load prediction value by virtue of a model, fusing the real-time index, the prediction value and a service health degree, calculating a dynamic weight by depending on service load data, distributing a request according to the weight, and feeding back an adjustment coefficient. According to the method, by asynchronously collecting the multi-dimensional real-time indexes, an accurate basis is provided for weight calculation, so that the request allocates the actual load of the matched instance, and the situation that the response of a high-load instance is slow due to too many requests is avoided; by introducing a load prediction value, load change can be pre-judged in advance, a weight strategy is adjusted in advance, overload when an instance load suddenly increases is prevented, and the fluctuation resistance of the system is improved; the weight is calculated by fusing multi-dimensional data, so that the comprehensive load of the instance can be comprehensively reflected, and evaluation deviation caused by a single index is avoided; a feedback mechanism can enable weight calculation to continuously adapt to a system state, and load unevenness caused by weight fixing or adjustment lag is avoided.

The invention discloses a server temperature control method and system based on deep learning, and belongs to the technical field of server temperature control, and the method comprises the steps: firstly, synchronously collecting server hardware temperature, business load and environment parameters, capturing a heat conduction relation through combining a thermal imaging technology, and constructing a dynamic relation network through time-space fusion processing; a heat flow prediction model is constructed based on the network, model parameters are dynamically corrected in combination with thermal response characteristic attenuation coefficients generated by service load characteristic analysis, and temperature distribution changes are predicted; generating a candidate control strategy set, screening an optimal strategy through composite scene simulation, and generating a control instruction; and comparing the actual temperature after the control instruction is executed with the model prediction temperature in real time, switching to a safety control mode when the deviation exceeds a threshold value, and extracting an incremental sample to update model parameters after the deviation is recovered, thereby realizing accurate temperature control.

The invention relates to the technical field of communication, and discloses a sea area wireless network coverage method and device and a computer readable storage medium, and the method comprises the steps: obtaining the historical link performance, real-time marine environment data and business load information of a target sea area; constructing a sea surface electromagnetic wave propagation attenuation dynamic prediction model based on a gated circulation unit; and in combination with the prediction result and the service demand, jointly optimizing the base station transmitting power, the antenna beam pointing angle and the subcarrier resource allocation, and issuing a regulation and control instruction. The system comprises a data acquisition module, a propagation modeling module, a resource scheduling module and an instruction execution module. According to the invention, through deep fusion of marine environment physical field perception and wireless communication system control, a dynamic coverage regulation and control mechanism driven by a sea condition is established; the provided sea surface electromagnetic wave propagation attenuation dynamic prediction model can pre-judge the signal attenuation trend under the complex sea condition in advance, so that network resource scheduling has perspectiveness.

The invention discloses a dynamic base station dormancy / wake-up method based on a flow load and a channel state, which improves the accuracy and reliability of dormancy and wake-up judgment by comprehensively considering multi-dimensional factors such as a service load, a wireless channel state, user distribution, adjacent region bearing capacity and the like. By designing a multi-level dormancy and wake-up mechanism and combining flexible management of different functional modules, reasonable balance between energy consumption reduction and service continuity is realized; by introducing a neighbor cell cooperation mechanism and a pre-wake-up strategy, the wake-up time delay is shortened while the coverage and switching stability are maintained. Meanwhile, key indexes such as energy consumption, access time delay, offline rate and switching success rate are continuously monitored in the operation process, and the feedback information is used for dynamically optimizing parameters such as criterion weight, threshold value and residence time. Through a closed-loop adjustment mechanism, the system can keep stable and effective operation in different scenes, and long-term balance between energy-saving control and service performance is realized.

The invention relates to the technical field of intelligent power grid network security, in particular to an adaptive scanning concurrency number adjusting method under micro-grid isolation, which comprises the following steps: S1, respectively deploying load monitoring nodes in a control area, a non-control area and a management information area, collecting service load and network state data of each area in real time through the load monitoring node; and S2, based on the collected service load and network state data, constructing a concurrent number calculation formula, and through dynamic concurrent adjustment driven by the real-time load, the vulnerability scanning efficiency is ensured, and the service operation of each region of the micro-grid is prevented from being interfered.

The invention discloses a cellular module power control method based on a network state and a service load, and aims to solve the problems of low energy utilization rate, unstable communication quality and the like of a traditional power control scheme. According to the method, power control parameters including a dynamic power protection threshold, a hardware protection delay and a hardware protection release threshold are defined and issued through a standardized interface. The network state and the service load are monitored in real time, and multi-dimensional data are collected to support power calculation. A module physical layer is combined with monitoring data, and through logic of basic power reference calculation, service load correction, parameter boundary verification and the like, target power giving consideration to communication quality and energy consumption is obtained. Dynamic power adjustment is executed according to the target power, when the target power reaches the upper limit, the standby power supply and the main power supply are triggered to supply power cooperatively, and power smooth transition and hardware protection are achieved in combination with hardware protection delay. And if the closed-loop monitoring adjustment effect does not reach the standard, iterative optimization is carried out again. The energy utilization rate is improved, and the communication transmission success rate is improved.

The invention relates to the technical field of wireless communication, and particularly discloses a satellite link-based network outage emergency communication guarantee system, which is characterized in that each distributed communication node periodically acquires local state information such as channel quality, service load and self energy of adjacent nodes, and constructs a dynamically updated local network state matrix; the nodes generate connection decision parameters updated in real time through depth feature extraction and multi-target parallel evaluation calculation based on the matrix; each node autonomously executes the connection relationship adjustment with the adjacent node according to the parameters, and realizes the dynamic reconstruction of the network topology through distributed state synchronization; a reconfigured network forms a multi-hop forwarding path through distributed routing discovery taking a satellite gateway as a root, nodes perform aggregation scheduling and forwarding according to data priorities, and trigger local path re-optimization under continuous link quality monitoring, so that an emergency communication link leading to a satellite link is autonomously and reliably formed and maintained.

The invention relates to the technical field of subkeys and communication, discloses a quantum key distribution and wavelength division multiplexing cooperative scheduling method for a metropolitan optical network, and aims to solve the problems of insufficient key rate and classic service quality reduction caused by mutual interference of quantum signals and classic services in a shared optical fiber. The method comprises the following steps: modeling Raman scattering and crosstalk noise between quantum and classical signals; constructing a joint optimization model which aims at minimizing classic service degradation and ensures that the quantum key rate is not lower than a threshold; solving wavelength, power and routing allocation by combining mixed integer programming and an intelligent algorithm; the key generation window and the reconfiguration wavelength are dynamically scheduled based on the service load prediction; according to the technical scheme, dual optimization of safety performance and network resource utilization efficiency can be realized.

The invention provides a cache space management method and device, equipment, a storage medium and a program product, and relates to the field of cache management. Comprising the steps of initializing a to-be-managed cache space, and obtaining file data; calculating a first real-time utilization rate according to the keyword data, triggering and obtaining a collection data set according to the collection instruction, and obtaining a reading data set according to the reading instruction; according to the first real-time utilization rate, the collected data set and the read data set, performing three-source data verification to obtain a second real-time utilization rate, comparing the second real-time utilization rate with a preset trimming threshold set, determining a trimming state, and calculating to obtain a target reserved space and a space alignment release amount; therefore, the to-be-pruned task queue is pruned, and the pruned cache space is obtained. The technical problem that in the prior art, an existing cache management strategy lacks dynamic adaptability, cannot dynamically adapt to service loads and is difficult to meet complex scene requirements, so that cache space management efficiency is low is solved.

The invention provides a business load prediction method and device, equipment, a storage medium and a product, and relates to the field of financial science and technology or other related fields, and the method comprises the steps: obtaining historical business feature data and a historical business load value; converting the historical business feature data into an original sparse coefficient matrix of a sparse linear equation set; converting a first element value in the original sparse coefficient matrix into a semi-precision format for storage; generating an approximate inverse matrix of the original sparse coefficient matrix based on the first element values stored in the semi-precision format, and storing second element values in the approximate inverse matrix in the semi-precision format; converting the first element value and the second element value in the semi-precision format into a single-precision format; and based on the historical business load value, the first element value of the single-precision format and the second element value of the single-precision format, executing solving operation of the equation set, and determining a predicted value of the business load according to a solution vector obtained by solving. According to the method, the storage space occupied by the matrix data and the data transmission bandwidth pressure can be reduced.

The invention relates to the technical field of dynamic bandwidth allocation, in particular to an ONU intelligent differentiation bandwidth control method and device oriented to multiple terminals, and the method comprises the following steps: obtaining terminal access and disconnection time, extracting connection frequency and stability information, obtaining channel utilization rate peak and valley values, and extracting fluctuation characteristics; and performing statistics on data stream types and resource proportion adjustment priorities, identifying application resource level configuration granularity, extracting granularity difference, calculating an adjustment period, updating bandwidth parameters, and establishing an adjustment record. According to the method, accurate judgment of the stable state of the terminal and extraction of the peak-valley difference value and the fluctuation frequency of the channel utilization rate are realized through analysis of the access behavior of the terminal, the predictability of channel load change and the conjoint analysis of the data stream type and the resource proportion are improved, the distribution fairness of bandwidth resources in a concurrent environment is optimized, and the resource utilization rate is improved. And resource level mapping of the transmission rate, the trigger interval and the duration is applied, so that the resource matching capability under different service loads is enhanced.

The invention provides a traffic load monitoring management method and system for an electric power communication network, and the method comprises the steps: carrying out the initial multilayer analysis of a collected traffic data package based on a DPI probe, and obtaining the initial analysis data of the traffic; performing windowing processing on the flow initial analysis data based on the time sliding windows to obtain a flow load index and a service load index corresponding to each time sliding window, and associating the flow load indexes with the service load indexes to form structured flow feature data; inputting the structured traffic feature data into an anomaly detection model to obtain an anomaly recognition result output by the anomaly detection model; carrying out secondary analysis on an original abnormal data packet extracted from the traffic data packet based on an abnormal identification result, associating with the traffic primary analysis data, and constructing an abnormal traffic traceability chain; and determining a load regulation and control strategy based on the abnormal traffic traceability chain in combination with a pre-constructed traffic load regulation and control decision library. The fault recovery efficiency of the power communication network is improved.

The invention discloses a TDD window dynamic adjustment method based on a service load in a satellite communication network, and the method comprises the steps: collecting the multi-dimensional flow state data of an original network and a mirror image network in a current period in real time, including the bandwidth gap amount and resource redundancy in each service direction; determining a target adjustment direction and a window duration debit amount between the two networks by using a pre-configured cross-network resource evaluation mechanism on the basis of the multi-dimensional flow state data on the premise of meeting a preset constraint condition, and generating a new dynamic window planning scheme; corresponding time slot schedule signaling is generated based on the scheme, the signaling is issued to nodes of the whole network through a time sequence synchronization mechanism, and the system is triggered to execute window boundary switching at the target effective moment. According to the method, the problems of uncommon resource allocation and out-of-step switching in a satellite long-delay environment are effectively solved, and the utilization rate and the stability of system resources are improved.

The invention provides a data center operation and maintenance management method and system, and the method comprises the steps: collecting version information, deployment data and operation and maintenance logs corresponding to each level, and creating a corresponding incidence relation through a knowledge graph, so as to generate a version-operation state fusion portrait; the version difference of the data center is recognized based on a time sequence attention mechanism, a normal operation feature baseline is established with the version-operation state fusion portrait as input, and difference features between actual version data and the feature baseline are extracted through a dynamic window to locate difference points of key versions; determining a target difference level of the difference point, and outputting a target management and control strategy matched with the data center in combination with an actual service load of the data center; and performing version adjustment on the data center according to the target management and control strategy, synchronously collecting a correspondingly generated system response, and judging whether the adjustment of the data center is completed or not according to the system response. The version difference of the data center can be eliminated, and the management efficiency is improved.

The application relates to the fields of network communication anomaly detection and intelligent operation and maintenance, in particular to a behavior reasoning and AI intelligent disposal method and system for communication anomalies, which comprises the following steps: collecting communication interaction time sequence data and protocol stack resource state data; constructing an ideal communication state model based on interface contract analysis results, protocol specification analysis results and queuing rules, and generating an ideal communication track benchmark according to a service request sequence in a preset time window; respectively performing fault attack knowledge injection and service load fluctuation rule injection to generate abnormal scene simulation tracks and service tide simulation tracks; performing difference calculation on real observation features and the ideal communication track benchmark to obtain a real residual space, and generating an abnormal theoretical residual space and a service tide theoretical residual space; generating abnormal type results and root cause results based on the topological similarity between the residual spaces, and outputting corresponding intelligent disposal instructions; and the application can accurately identify high-concurrency legal tides and real attacks.

The invention relates to the field of unmanned aerial vehicle data link communication, in particular to a satellite and data link communication MAC (Media Access Control) layer resource scheduling method, which adopts the technical scheme that a plurality of master devices maintain a neighbor relation through heartbeat and mutually report the number of connected slave devices and congestion conditions, and the slave devices to which the master devices belong report signal quality in real time; when the service volume of a certain master device exceeds a threshold, service negotiation with a neighbor master device is carried out, and part of slave device services are redirected to other idle master devices; real-time information sharing and signal quality feedback are realized, so that the transparency of the overall operation state of the system is improved; service volume monitoring and response are also realized, and the expandability of the system is improved, so that balanced distribution of service loads is realized; and moreover, the fault handling capacity is improved, the single-point fault risk is reduced, and the reliability and stability of the system are enhanced.

The invention discloses a working mode adaptive switching method and device, equipment, a storage medium and a computer product. The method comprises the following steps: detecting whether a service load state and a trigger event occur or not in real time; according to the detected service load state and / or trigger event and the working mode capability supported by a second communication node, determining whether to perform working mode switching on a modem in the first communication node; and if yes, switching the working mode of the modem. Wherein the working mode switching comprises mutual switching between a power consumption reducing mode and a mobile bandwidth enhancing mode. According to the method, mutual switching is carried out between the power consumption reduction mode and the mobile bandwidth enhancement mode, so that the first communication node has the advantages of low power consumption and high service rate.

The invention provides a hybrid cloud architecture-based power business load balancing scheduling method and system, and the method comprises the steps: classifying power business operation data collected in real time based on the importance of power businesses, and obtaining a target power business category; determining a current load state of the target power business category by combining resource state information of the private cloud resource pool and the public cloud resource pool based on the target power business category and the corresponding power business operation data; and determining a load scheduling strategy based on the current load state for the target power business category. According to the method, the problems that in an existing method, the resource capacity of a local physical server cluster is fixed, sudden peak loads are difficult to deal with, and service response delay and data processing interruption are likely to be caused are effectively solved, and meanwhile stable and efficient operation of a power system is guaranteed.

The invention discloses a service management method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: receiving service configuration information; wherein the service configuration information comprises the minimum starting instance number of each service and a resource constraint condition; according to the service configuration information, service instances meeting the corresponding minimum starting instance number and the corresponding resource constraint condition are deployed for each service in an accelerator resource pool; and acquiring a service load index, calculating a target instance number of each service based on the service load index by using a proportional integral derivative controller, and performing elastic scaling scheduling on the service instance of each service according to the target instance number of each service. In the process of scheduling the accelerator resources, the resource utilization rate is improved, and the service stability is ensured.

The embodiment of the invention provides an application service capacity expansion method and device, and belongs to the technical field of computers. The method comprises the following steps: monitoring a service load of an application service, and determining a service load specification to which the service load belongs; and under the condition that the business load of the application service is improved from a first specification to a second specification, executing a service-uninterrupted capacity expansion operation on each application service module corresponding to the application service based on corresponding module configuration information so as to obtain a capacity-expanded application service matched with the second specification, and the application service is decomposed into a plurality of application service modules which can be independently expanded according to the functional composition.

This invention discloses a dynamic optimization method for network switch port WRR scheduling resources based on convex optimization modeling. Applied to the field of switching equipment scheduling and control, it addresses the problem that existing scheduling weight configurations cannot adapt to environmental changes, resulting in unstable forwarding performance of switching equipment. This invention establishes constraint functions based on port bandwidth, token resources, and queue number, collects the arrival probability distribution of data packets in each queue within the switch port to establish a distribution model, and combines the constraint functions and the collected model to construct a convex optimization problem for switch port queue resource allocation. The objective of the optimization problem is defined as minimizing the sum of queuing probabilities of the switch queues. The problem is solved using an existing convex optimization solver, and the results are configured as the weights of each port queue based on the Weighted Round Robin (WRR) scheduling algorithm. This invention solves the problem of adaptive resource allocation during dynamic network traffic exchange, enabling network switching equipment to provide stable network performance under different service loads.

The invention provides a file processing method and device and related equipment, and relates to the technical field of computers, and the method comprises the steps: extracting features corresponding to each to-be-processed file in a to-be-processed file set; determining a clustering result corresponding to the to-be-processed file set based on the feature corresponding to each to-be-processed file and a service load parameter, wherein the service load parameter is used for representing the occupation condition of a service corresponding to the file on system resources; inputting target data into a first model to obtain a file processing result corresponding to the to-be-processed file set output by the first model; the target data comprises at least one of the following items: the clustering result, a storage condition and a service performance index; the storage condition is used for representing the file storage condition of the system, and the business performance index is used for representing the performance condition of the system in the business processing process. Through the file processing method, human resources and operation and maintenance cost can be reduced, and file processing efficiency is improved.

The invention relates to a network element service recovery method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: simulating a current network element network state in a virtual isolation environment, deploying a network element network agent, simulating a service fault through the network element network agent, obtaining a candidate switching network element, obtaining an evaluation parameter of the candidate switching network element under the condition that the current network element network state does not meet an emergency risk condition, performing comprehensive calculation on the evaluation parameters through an entropy weight method to obtain a comprehensive evaluation value of the candidate switching network element, inputting the comprehensive evaluation value, the current network element network state, the network topology and the service grading label into a pre-trained AI model to obtain a grading switching strategy, and simulating the grading switching strategy through a network element network agent to obtain a network element network state. And under the condition that the simulation result meets the network state condition, executing a hierarchical switching strategy, and recovering the service of the current damaged network element. By adopting the method, the service load capacity can be improved.

The invention belongs to the technical field of network communication, and particularly relates to a cooperative adaptive routing method applied to a communication network. According to the method, an adaptive routing decision framework is constructed and comprises a protocol switching module, a threshold adaptive optimization module and a protocol parameter tuning module. And the protocol switching module realizes protocol switching through local network topology change and communication sensing information of a service load in combination with a periodic sensing and threshold control mechanism. The threshold adaptive optimization module uses a genetic algorithm to optimize a topology dynamic threshold, a load threshold and a sensing period, and searches an optimal threshold parameter combination adapted to different network topologies and service requirements in a parameter space. The protocol parameter tuning module is based on a Dirichlet distribution lightweight strategy, adopts a reinforcement learning algorithm to generate a multi-parameter joint adjustment weight vector, determines a parameter adjustment direction in combination with a rule, and updates each protocol parameter. According to the invention, the routing adaptivity is improved, and the service quality is optimized.

This invention relates to a smart device connectivity maintenance method for automatic switching of multimodal communication links, aiming to solve the problems of inconsistent state data, context drift, and limited real-time adaptability of end-side models in multi-source heterogeneous links. The technical solution uses a graph neural network model to perform multimodal standardization, dynamic topology mapping, and deep extraction of spatiotemporal features on link state data, including signal quality, service load, device movement trajectory, and environmental interference information, generating a multi-candidate link switching strategy distribution. On the end side, a lightweight temporal graph neural network is used, along with cloud-based knowledge distillation and single-step strategy alignment mechanisms, to calibrate local inference model parameters in real time, improving the accuracy and robustness of switching decisions. This solution significantly improves the real-time performance, stability, and service continuity of communication link switching, and can adaptively adjust the end-side knowledge synchronization frequency to achieve optimal communication experience under end-cloud collaboration.

The application relates to the technical field of big data analysis, and discloses an OT / IT heterogeneous data unified access and standardized conversion method, which comprises the following steps: acquiring a data stream and extracting service load data and metadata therefrom; converting the metadata into fixed-length hash features by using hash operation, stripping the metadata, and encapsulating the service load data and the hash features; dividing a plurality of continuous memory buffer areas corresponding to a bit mask base number of a memory space, and extracting feature offsets of the hash features by using the bit mask; sequentially appending and writing data into the buffer areas according to receiving time; and sequentially writing the data into a storage medium in batches when the memory occupation reaches a preset threshold. The application converts the device logical owner relationship into the continuity of the medium physical block by using the hash routing, suppresses write amplification, avoids system lagging caused by fragment consolidation, and guarantees the continuous and smooth data collection of a data surge.

The application relates to the technical field of wireless communication detection, in particular to a link state monitoring method of a radio frequency combiner. Based on the characteristics of radio frequency signals affected by the combined action of service load, thermal noise and abnormal interference, the downlink transmission power, uplink utilization rate and total received power are sampled in multiple time periods, the deviation and fluctuation of the received power and the expected load component are analyzed, the link environment stability is reflected, and then the residual power characteristics representing the link state complexity are obtained. The complexity is used to dynamically adjust the discrimination threshold or weight, so that the fault recognition fully considers the link dynamic characteristics, and the link state evaluation result is output through multiple rounds of correction and regression analysis. The method effectively avoids the interference of normal working conditions such as high load and temperature rise, and significantly improves the identification accuracy and reliability of nonlinear faults such as passive intermodulation (PIM) and external interference.

The invention belongs to the technical field of optical fiber communication line operation and maintenance, and discloses an optical fiber communication line intelligent operation and maintenance platform oriented to an operator. Wherein the equipment semantic database converts OTDR curve characteristics and alarm codes into description which can be directly understood by operation and maintenance personnel, such as attenuation abnormity, joint faults and the like; the environment semantic database is associated with soil settlement, temperature and humidity change and optical cable extrusion risk, and sheath aging acceleration; the service semantic library maps the bandwidth utilization rate, and the service interruption record is the bearing pressure level and the service influence degree; meanwhile, a weight model is trained in combination with historical operation and maintenance data, semantic association coefficients are dynamically adjusted in real-time business scenes such as the early peak of a government affair special line, edge-end computing power consumption is reduced in cooperation with an edge and cloud collaborative semantic processing architecture, a business load thermodynamic diagram is embedded through a digital twin module, a hotspot section is rapidly positioned, and the service load thermodynamic diagram is optimized. And the dispersed data is converted into effective information for supporting an operation and maintenance decision.

The invention relates to a method for identifying and authenticating a user profile, which makes it possible to use a connected service on a multimedia system loaded on a motor vehicle (2), the multimedia system comprising a memory (221) comprising a user profile for a portable device (5) in the memory, the vehicle comprising a first communication device for communicating with a remote server (3) comprising a memory (222) and a second communication system for communicating with the portable device, the portable device (5) comprising a memory, the method comprising a detection step of detecting the presence of a portable device (5), if a portable device (5) is detected, the method comprising a reception step of receiving authentication information, a transmission step of transmitting the authentication information to the remote server, a verification step of verifying the authentication information, and if the authentication information is compliant, a reception step of receiving, by the multimedia system, a use validation of the user profile.