18 results about "Network performance optimization" patented technology

The invention discloses a power grid hybrid network performance optimization model considering construction cost, and belongs to the technical field of intelligent power grid communication. According to the model, a parameter system including communication equipment, terrain and a global system is defined, a function with the purpose of minimizing the total cost of a life cycle and multivariate constraint conditions of transmission distance, retransmission times, delay, reliability and flow velocity are constructed, and optimal equipment and transfer device configuration is solved by adopting a node traversal and iterative optimization algorithm. Cost and performance collaborative optimization of a honeycomb, Wi-Fi and ZigBee heterogeneous hybrid communication network under a complex terrain is realized, planning accuracy and reliability are remarkably improved, and construction, operation and maintenance cost is reduced.

The application belongs to the technical field of communication, and particularly relates to a network performance testing method, a network performance testing device, a computer readable medium, an electronic device and a computer program product. The method comprises the following steps: establishing a network performance testing channel for communication connection with a specified network element, wherein the specified network element is a functional network element specified in a core network of a communication system; and performing data communication with the specified network element based on the network performance testing channel, so as to obtain network performance parameters of communication traffic. The application can improve the accuracy of network performance optimization.

The invention particularly relates to a machine room network performance optimization system based on big data, and relates to the technical field of network performance optimization. A phase difference module which reflects and controls the path difference; a total phase in-phase implementation module; a reflection amplitude control module; and a dynamic monitoring and optimizing module. According to the invention, a full-link optimization system from signal characteristic analysis to phase and amplitude fine control is constructed, a reflection and control path difference module is combined with a machine room space to flexibly adjust a path difference, an active compensation phase is introduced by a total phase in-phase implementation module, and phase deviation of metal reflection and dielectric loss is accurately counteracted; the incident wave and the reflected wave are strictly superposed in the same phase at the receiving end, a phase foundation is built for signal gain, the superposition enhancement effect is theoretically developed into stable engineering practice, the problems that the signal enhancement effect is unstable and is easily counteracted by interference in traditional optimization are solved, and high reliability of data transmission is guaranteed.

The invention discloses a pulse time-driven network performance optimization system and method, and the system comprises a sparse scrambling coding module which is used for carrying out the sparse scrambling coding of input data, so as to convert the input data into a pulse sequence with the determined time distribution in the coding time, and obtain a coded pulse sequence; the decoding module is used for inputting the coded pulse sequence into the pulse neural network for reasoning, and continuously monitoring pulse activity of each category of channel of an output layer of the pulse neural network in the reasoning process; when the first pulse of any category of channel is detected, generating category prediction based on the pulse time, the pulse count or the combination thereof of the first pulse; and the coding and decoding driving training module is used for carrying out combined optimization of weights and thresholds on the network or carrying out conversion from an artificial neural network and carrying out threshold calibration on the network based on category prediction. Therefore, by adopting the embodiment of the invention, the recognition robustness of the network on the data set can be obviously improved.

This invention discloses a group-connected BD-RIS-assisted uplink communication system and a method for maximizing transmission rate, relating to the field of wireless communication technology. The method first establishes a channel model between the user, base station, and BD-RIS, derives the decoded signal expression for the user at the base station, and calculates the user's signal-to-interference-plus-noise ratio (SNR) and achievable rate. Then, it constructs an optimization problem with the goal of maximizing the system's sum and rate, with the optimization variables being the equalizer, user transmit power, and BD-RIS phase shift matrix. Finally, it employs an alternating optimization strategy, sequentially optimizing the equalizer based on the minimum mean square error criterion, transforming the non-convex problem into a convex problem to solve for the transmit power, and optimizing the phase shift matrix using the BFGS quasi-Newton method, iterating until the system performance converges. This invention overcomes the design limitations of traditional reconfigurable smart reflectors, fully leverages the control advantages of BD-RIS, effectively improves the sum and rate of the uplink communication system, and provides a new solution for future wireless network performance optimization.

The invention discloses a parameter adjustment method and device, a storage medium and electronic equipment, and relates to the technical field of communication, and the method comprises the steps: obtaining an operation parameter of target access network equipment in an area where network performance optimization needs to be carried out; determining network parameters and state information of at least one cell covered by the target access network equipment; performing global optimal analysis on the target access network equipment according to the network parameters and the state information to obtain target operation parameters corresponding to the target access network equipment; and adjusting the operation parameter of the target access network equipment to the target operation parameter so as to optimize the network performance of a target area where at least one cell in the area is located. According to the invention, the global optimal analysis is carried out on the target access network equipment according to the network parameters and the state information to obtain the corresponding target operation parameters, so that the accuracy of parameter adjustment is improved; by adjusting the operation parameter of the target access network device to the target operation parameter, the network performance optimization effect of the target area is improved.

The invention discloses a directed ring causal structure discrimination and estimation method for network intelligent operation and maintenance, relates to the technical field of network intelligent operation and maintenance, and provides a solution based on high-order cumulant matrix analysis for causal discovery and effect estimation requirements of a feedback loop in a network system. A unified cumulant matrix construction principle is established, so that cumulant total orders of main diagonal elements and auxiliary diagonal elements of the matrix are the same; on the basis, the system firstly utilizes rank conditions of a forward three-order cumulant matrix and a reverse three-order cumulant matrix to realize loop detection; and after the existence of the feedback loop is confirmed, constructing a mixed third-order cumulant matrix, constructing a solvable equation about a causal coefficient by utilizing determinant properties, directly completing loop effect estimation, and realizing integration of loop discrimination and effect estimation. According to the method, a complex intra-ring causal effect estimation problem is converted into an algebraic problem which can be solved directly, and accurate causal support is provided for network performance optimization, resource scheduling and safety protection.

The application discloses a kind of time synchronization network performance optimization method, device, equipment and medium, the method is applied to synchronous network probe monitoring system, comprising the following steps: when time synchronization network performance appears deterioration fault, probe equipment reports time synchronization network performance deterioration fault information to probe network management equipment;Probe network management equipment prompts operation and maintenance personnel to carry out fault maintenance to fault position, and issues first switching instruction to probe equipment, and probe equipment is switched from measurement mode to time source mode according to first switching instruction;Probe network management equipment receives fault solution receipt, then issues second switching instruction to probe equipment, and probe equipment is switched from time source mode to measurement mode according to second switching instruction;Probe equipment continues to measure and obtains the time synchronization network performance of access equipment, to complete the optimization of time synchronization network performance.The method can realize the automation and reliability of synchronous network fault root location process.

A method for wireless communications comprising: transmitting, by a network node to a wireless device, a handover configuration information to facilitate reporting of successful handovers associated with the wireless device; receiving, at the network node, information reporting a successful handover associated with the wireless device, wherein the information reporting the successful handover is in accordance with the handover configuration information; and performing network optimization based on the information reporting the successful handover.

The invention discloses a performance optimization method based on a supporting cache millimeter wave cellular network, which relates to the technical field of wireless communication, and comprises the following steps: (1) constructing a hybrid millimeter wave small cellular network; (2) modeling the network, and establishing a path loss model containing a line-of-sight (LoS) link and a non-line-of-sight (NLoS) link; (3) designing an optimal caching strategy, and storing the most popular content MPC under Zipf request distribution to maximize the regional spectrum efficiency; (4) establishing a user dynamic association mechanism, and preferentially accessing a base station in which the requested content is cached; (5) deriving a closed solution expression of the regional spectral efficiency ASE under the condition that the backhaul capacity is limited, quantifying the network throughput performance, and reducing the calculation complexity by adopting a Gauss-Laguerre integral method; and (6) network performance optimization is carried out based on Zipf request distribution, and cache coverage gain and content reuse efficiency are balanced through joint optimization of cache node density and single-point cache capacity. The method effectively reduces backhaul resource consumption, and is suitable for 5G / 6G millimeter wave high-density small cellular network deployment.

The invention provides a communication method and device, and the method comprises the steps: receiving first data which comprises the traffic statistic data of one or more cells within the range of a base station; acquiring a first model based on the first data; reasoning the network performance of one or more cells within the range of the base station based on a first model to obtain communication parameters; and sending the communication parameters. Through the method provided by the invention, the transmission delay of the network performance optimization command can be reduced.

The application provides a method for improving controllability of a symmetric network by time segmentation, and relates to the technical field of network performance optimization. The method adopts a time segmentation method to divide a symmetric network into a symmetric time-varying network composed of multiple snapshots, and realizes the structural controllability of the whole network through the control of each snapshot. Given a symmetric network, the black and white coloring is performed through a breadth-first search algorithm for classification; the maximum matching of edges in the symmetric network is found; the undirected cactus is constructed according to the unmatched nodes and the matched edges; the network graph composed of each undirected cactus is used to construct a snapshot, and the number of snapshots is the same as the number of undirected cacti. When a symmetric network is divided into a symmetric time-varying network composed of multiple snapshots, the time segmentation method can effectively reduce the number of drive nodes in the symmetric network and improve the network controllability.

The application provides a HTTP request performance diagnosis method and system based on a dynamic Agent mechanism and a storage medium, relates to the technical field of computer network performance optimization, and the diagnosis method comprises the following steps: S1, a dynamic Agent program is connected to a target server through the Attach mechanism of a JVM tool script; S2, the Agent program proxies the service method of javax.servlet.http.HttpServlet, intercepts specific HTTP requests, and starts a background monitoring thread to perform the following operations: setting an execution time threshold, marking HTTP requests exceeding the time threshold as STUCK states; performing thread stack sampling on the STUCK state requests at a set frequency; collecting method execution completion events and constructing flame graph data; S3, two result files are generated: head.txt, which records the total time consumption of the request and a unique identifier UUID; and uuid.txt, which stores the flame graph data obtained by sampling; S4, a flame graph generation tool is called to generate an SVG format flame graph; and S5, the performance bottleneck is located by analyzing the stack width and the number of samples of the flame graph; the flame graph width is positively correlated with the execution time consumption, and the widest stack is preferentially optimized.

Embodiments of the present disclosure relate to network performance optimization, and more particularly to gNB performance optimization based on reinforcement learning (RL) operations. The method includes obtaining current state information of a network environment and a reward, the reward being associated with a reinforcement learning operation and pertaining to performance of the network environment; determining a predicted future state of the network environment based on the current state information; and generating a target set of configuration parameters of the network environment based on at least the predicted future state of the network environment by using the reinforcement learning operation; and configuring the network environment using the target set of configuration parameters.

The present disclosure provides a system for optimizing network performance based on correlated multi-source experiential feedback. The system includes a data pipeline comprising a telemetry ingestion module configured to collect structured system data and a natural language parser configured to extract sentiment-weighted indicators from unstructured user feedback data. An analytical artificial intelligence (AI) module identifies patterns and anomalies in the data. A correlation AI engine generates time-aligned embeddings and computes relationships between network events and user dissatisfaction. A generative AI module produces system modification recommendations based on correlation engine outputs. An action operator automatically deploys configuration changes to infrastructure nodes, monitors outcomes, and triggers rollback operations in response to performance regressions, without human intervention.

The invention discloses a network performance optimization system and method based on data analysis, and the system comprises the steps: integrating multi-modal network data collection, multi-modal network knowledge graph construction, adaptive business intention analysis, an intention-driven graph attention time sequence prediction model (IGATP) and a multi-target intelligent arrangement and feedback module; the deep understanding of the network service intention, the accurate prediction of the network performance, the anticipation of the intention violation risk and the intelligent active arrangement of the network resources are realized. According to the system, the business intention, the knowledge graph, deep learning and reinforcement learning are creatively combined, the problems of insufficient intention perception, lack of association analysis, prediction lag and passive optimization decision in an existing network optimization scheme are solved, the reliability, efficiency and user experience of network services are remarkably improved, and the network is promoted to advance towards high-level autonomy.

The invention discloses a fault simulation and network performance improvement method and device based on a digital twinning model, and belongs to the technical field of network communication and digital twinning. The method comprises the following steps: collecting and preprocessing real network physical entity data, and constructing a network digital twin model for realizing three-dimensional mapping; establishing a fault scene library based on the model, and injecting fault parameters for simulation to obtain a fault simulation result; setting an evaluation index system, quantitatively evaluating network performance and identifying a bottleneck; and formulating a performance improvement strategy, issuing the performance improvement strategy to a real network after simulation verification, and establishing a closed-loop feedback mechanism for continuous optimization. The device comprises a data acquisition module, a model construction module, a fault simulation module, a performance evaluation module, a strategy making and implementation module and a data interaction module, and can be additionally provided with a model updating module. According to the method, accurate fault simulation and efficient network performance optimization are realized, the network operation stability and the intelligent management level are improved, and the method adapts to a dynamic network environment and has good adaptability and expansibility.

Provided in the present application are a communication method and apparatus. The method comprises: receiving first data, wherein the first data comprises traffic statistics data of one or more cells within the range of a base station; on the basis of the first data, acquiring a first model; on the basis of the first model, performing inference on the network performance of the one or more cells within the range of the base station, so as to acquire a communication parameter; and sending the communication parameter. By means of the method provided in the present application, the transmission delay of a network performance optimization command can be reduced.