125 results about "Traffic allocation" patented technology

The invention discloses a dominant path identification method and system in a multi-source scene based on a perturbation response model, and relates to the technical field of computers. According to the method, the influence of the link state change on the steady state of the system is dynamically analyzed based on a perturbation response mode instead of depending on a static index, the method is closer to a real interaction mechanism of the network, and the mechanism modeling precision is improved. By traversing the link state, the actual contribution of each link to the response of the target node is quantified, and the complex interaction of weak connection and multi-link coordination is prevented from being ignored. Through the process that the system is evolved to the steady state again after disturbance, flow distribution and competition at the position of a shared node are naturally modeled instead of depending on local optimal addressing, the global reasonability of dominant path recognition is improved, and the problem of multi-source target resource competition is solved. The method is suitable for various networks, and has a core support effect on construction of a propagation risk early warning model based on network science, implementation of a key node intervention strategy and optimization of an intelligent governance mechanism of a social information system.

The invention provides a network flow regulation and control system and method and a storage medium, and relates to the technical field of network communication. The network traffic regulation and control system comprises: an information collection unit, which is used for obtaining historical traffic data of all media plane network elements connected with a control plane network element and a topological relation of the media plane network elements; the AI model updating unit is used for updating the traffic regulation and control model of the control plane network element according to the historical traffic data and the topological relation, and the strategy generation unit is used for obtaining a traffic distribution strategy of the control plane network element; and the strategy execution unit is used for dynamically adjusting the media traffic of each media plane network element according to the traffic distribution strategy. According to the method, the network data is collected and analyzed in real time, and dynamic updating of the AI model is combined, so that dynamic regulation and control of the network traffic are realized, the method can quickly adapt to changes of network conditions, and the flexibility and efficiency of traffic regulation and control are improved.

The invention discloses a comprehensive space-time flexibility analysis method for an electric vehicle under a dynamic traffic flow, and the method comprises the steps: carrying out the flexible charging and discharging capability of the electric vehicle through the maximum potential of a price signal on the basis of a dynamic traffic distribution model, and depicting a comprehensive space-time flexible operation region of the electric vehicle; establishing a dynamic traffic distribution model considering V2G vehicle network interaction, and considering price guidance of electric vehicle V2G vehicle network interaction and charging and discharging coupons in the model; a second-order cone DistFlow optimal power flow model is established in the power distribution network, and a reasonable power distribution network power purchase and generation strategy is formulated; dual-network coupling of a power distribution network and a traffic network is realized through a charging station and a V2G station, a power distribution-traffic coupling system cost model considering vehicle-network interaction is constructed, a flexible operation domain of an electric vehicle bidirectional charging station is described through convex hull fitting, and a comprehensive space-time flexibility analysis method for an electric vehicle under dynamic traffic flow is obtained. And the flexible adjustment capability of charging and discharging of the electric vehicle under different subsidy quotas is described.

The invention discloses a track digital twinning real-time online deduction method and system, and belongs to the technical field of traffic simulation based on machine learning. The problem that in the prior art, a traditional traffic simulation and rail passenger flow dynamic allocation method is low in solving efficiency, and consequently the large-scale rail traffic network dynamic passenger flow allocation requirement is difficult to meet is solved. The method comprises the following steps: constructing a track road network model; generating road network passenger flow data and line shift data; further, simulation individuals of the train and the passengers are generated, path track matching based on time and space is carried out, and passenger-train dynamic traffic distribution and passenger-train interactive operation deduction are completed; according to the real-time detection data and the simulation result, dynamic line shift and passenger flow adjustment is carried out until a preset convergence condition is reached, and dynamic traffic checking is completed; and simulation is carried out to realize reduction and prediction of the passenger flow / flow direction of the whole line network. The method effectively improves the rail passenger flow dynamic distribution efficiency, and can be applied to large-scale traffic network simulation.

The invention belongs to the technical field of power system optimization scheduling, and discloses a mathematical model dual-drive-based port intelligent scheduling method, which comprises the following steps of inputting real-time operation data of a port logistics system and an energy system; on the basis of a deep reinforcement learning model, operation data is adopted for training, a state-action-reward mapping relation is established, and a data-driven preliminary scheduling strategy is generated; based on the operation data, constructing a model-driven traffic distribution-user balance optimization model, and obtaining an energy pricing strategy capable of minimizing the operation cost; constructing a multi-agent collaborative decision framework to coordinate a preliminary scheduling strategy and a traffic distribution-user equilibrium optimization model, and realizing iterative optimization of dual-drive strategy collaboration; dynamically selecting an optimal sub-heuristic strategy by adopting a dual deep Q network structure based on an iterative optimization result; the problems of insufficient strategy generalization ability and poor dynamic environment adaptability in the prior art are solved.

The invention discloses a self-adaptive telephone traffic distribution method and system based on customer service emotion. Comprising the following steps: acquiring a first emotional state data set of a plurality of first customer service staff in an idle state in a first time period and a first customer evaluation value after each first customer service staff answers a first incoming call in a second time period, and acquiring a call answering skill value of each first customer service staff; for each first customer service, analyzing the first emotional state data set and the first customer evaluation value of the first customer service by using a target emotional evaluation model to obtain a first emotional value of the first customer service in a first time period, and determining the call receiving priority of each first customer service for answering the second incoming call according to the call receiving skill value and the first emotional value; and in response to an answering request for the second incoming call, determining a target customer service answering the second incoming call according to the call answering priority of each first customer service. According to the invention, the technical problem that the telephone traffic distribution result cannot adapt to the actual working state of the customer service because the analysis of the emotional state of the customer service is neglected in the related telephone traffic distribution technology is solved.

The invention relates to the field of traffic engineering, and discloses an urban road network toughness management platform and evaluation method based on dynamic cascade failure, and the platform comprises a disturbance scene simulation and random capacity degradation module, a dynamic cascade failure process simulation module, and a multi-dimensional toughness index calculation and uncertainty evaluation module. A toughness three-dimensional vector is formed by integrating system robustness, restorability and performance accumulated loss, and a time-varying dynamic traffic distribution model considering road network structure change is used for depicting a cascade failure dynamic process; a random variable is introduced into a damaged road section capacity index, and a new evaluation method is provided for solving the defect that the existing toughness evaluation method is difficult to comprehensively quantify the robustness and the restorability of a road network. A failure diffusion mechanism in an abnormal scene is truly restored, and an effective method is provided for overcoming the double defects that a traditional model is insufficient in quantification of travel behavior dynamics and a system recovery process.

The invention discloses an expressway reconstruction and extension traffic diversion method, system and device and a medium, and the method comprises the steps: obtaining multi-source dynamic traffic data, and constructing a road network origin-destination matrix through data fusion and demand deduction; a traffic flow distribution result is obtained by constructing a system optimal traffic distribution model; identifying the first congestion time period, and calculating the traffic flow exceeding the residual traffic capacity in the congestion time period to obtain the traffic flow to be shunted; solving an optimal shunting path under the target of minimizing the total travel time of the system through a hybrid intelligent algorithm to obtain an optimal shunting path scheme; and verifying the optimal shunting path scheme by using microscopic traffic simulation software, updating traffic data based on a simulation result, and carrying out iterative optimization to obtain a differentiated traffic organization scheme. According to the invention, the traffic flow passing efficiency during the highway reconstruction and extension period is effectively improved.

The invention discloses a dynamic electric power-traffic coupling system optimal pricing method considering differentiation V2G, which fully considers electric vehicle user V2G differentiation factors on the background of traffic flow simulation of a dynamic traffic distribution model, and sets an optimal electricity price to realize optimal scheduling of an electric power-traffic coupling system. Firstly, a dynamic traffic distribution model considering traffic flow is established, and differentiated behaviors of users for V2G and changes of vehicle cost at any time and space movement are considered in the model. And then establishing a second-order cone DistFlow-based power distribution network optimal power flow model in the power distribution network to describe a power flow distribution condition, realizing coupling with a traffic network through a charging station and a V2G station, constructing a dynamic power-traffic coupling system optimal pricing method considering differentiated V2G, and guiding charging flow and V2G flow distribution through formulating an optimal charging electricity price and V2G reward so as to realize optimal pricing of the dynamic power-traffic coupling system. Load shedding loss caused by overload in the peak period of the power distribution network is reduced, and flexibility and reliability of the power distribution network are enhanced.

The invention discloses an urban circle traffic demand prediction method and system, and belongs to the technical field of traffic data processing, and the method comprises the steps: taking a four-stage theory as a basis, efficiently obtaining a travel demand OD matrix of urban circle global traffic middle area granularity in the future, and mastering the overall traffic demand pattern of an urban circle from a macroscopic level; on the basis of a trip chain theory, a city traffic cell granularity trip demand OD matrix with higher time-space precision in the future year is accurately obtained, and the method can adapt to more application scenes and reflect traffic prediction and evaluation analysis of traffic demand details; through a traffic distribution algorithm of motor vehicles and public traffic, traffic flow indexes borne by urban circle traffic supply facilities are obtained, and continuity and consistency of spatial and temporal distribution of the current situation and indexes such as traffic supply facilities, travel demands, road flow and bus passenger volume in the future are achieved. And therefore, the traffic demand prediction and evaluation index result of the urban circle in the future year can scientifically meet the needs of users.

The invention provides a flow distribution method and related equipment. The method comprises the following steps: in a constructed training environment, according to a preset reward function, training to obtain an intelligent agent based on a deep learning algorithm; deploying an actual network topology according to the training environment; in response to a service distribution demand, inputting a traffic matrix corresponding to the service into the trained agent to obtain a target action; the target action comprises a flow distribution proportion for each segment routing path; and determining a traffic distribution proportion of each segment routing path based on the target action, and performing traffic distribution processing on the service according to the traffic distribution proportion. According to the embodiment of the invention, the intelligent agent capable of quickly and autonomously making a decision is obtained through deep reinforcement learning training, and reasonable path selection and traffic distribution are performed on each traffic request, so that the global network link load is reduced.

The invention discloses a flow control method and device, a storage medium and electronic equipment, and relates to the technical field of network flow management, and the method comprises the steps: determining a plurality of feature vectors matched with input network flow based on a plurality of feature extraction modules; performing feature fusion processing on the plurality of feature vectors through a gating attention mechanism to obtain distribution strategy features, and determining a traffic distribution strategy matched with the input network traffic according to the distribution strategy features; determining network resources respectively allocated to the network traffic of the plurality of traffic categories in the input network traffic according to a traffic allocation strategy; updating a flow distribution strategy according to the network transmission performance information; the decision model updating strategy is adjusted in real time based on the strategy execution result, learning and optimization of the adaptive network state in the operation process are achieved, it is ensured that the long-term service quality index is kept at the optimal level, the technical problems that the flow distribution strategy is poor in performance and cannot meet the requirement are solved, and the technical effect of improving the network resource utilization rate is achieved.

The invention relates to a Java background service deployment method and system based on double-node dynamic routing, and the method comprises the steps: obtaining the health state of each node based on TCP port activity detection and / or UDP heartbeat packet detection; judging the nodes of which the detection failure times exceed the preset times as fault nodes, and setting the fault nodes to be in an offline state; determining a traffic allocation weight according to the real-time working state of the node; performing routing distribution on the client request based on the traffic distribution weight; route distribution is dynamically adjusted based on the traffic allocation weight, the resource utilization rate of the nodes is improved, and the situation that the load of a single node is too heavy is avoided; when a fault node occurs, the other node is automatically switched to respond to the request, so that the fault switching time is shortened; and the data consistency between the double nodes is adjusted based on the Redis cluster and the MySql cluster. Based on cooperation of the steps, the problems of failure switching delay, low resource utilization and low data consistency in a traditional scheme are solved.

The invention relates to the technical field of wireless communication, in particular to a WAPI stable transmission type wireless data management system, which is used for solving the problems that a WAPI-based ternary security architecture is adopted, an intelligent substation network is constructed, secure communication and service isolation are realized, the compatibility with the existing network is ensured, and the wireless data management efficiency is high. However, flow distribution cannot be dynamically adjusted according to transmission conditions and service requirements, network congestion and delay cannot be reduced through dynamic adjustment, and system stability and performance are reduced. Wireless transmission flow is monitored in real time through the flow management module, flow distribution is dynamically adjusted according to transmission conditions and service requirements, efficient utilization of network resources is guaranteed, an existing network structure is not affected through comprehensive evaluation, accurate calculation of the service requirements and optimization of bandwidth distribution, good compatibility is achieved, and the service quality is improved. Network congestion and delay are reduced through dynamic adjustment, and system stability and performance are improved.

The invention discloses a message issuing speed control method and system based on an AI large model. The method comprises the steps of collecting multi-source data in real time and constructing a multi-dimensional fusion feature vector; based on the BERT-CNN distillation architecture, detecting abnormity and executing hierarchical fusing; based on the fusion feature vector, using a reinforcement learning model to predict message issuing rates of a plurality of time windows in the future and dynamically adjusting priorities; in the offline stage, a mixed integer programming model is adopted to generate minimum cloud resource cost, and in the online stage, a deep reinforcement learning model is adopted to carry out real-time resource fine tuning; based on the node health degree, calculating a traffic allocation weight through a smooth weighted polling algorithm so as to carry out load balancing; different business scenes are adapted through domain adversarial training and multi-task learning, and different languages are adapted through multi-language BERT coding. The message rate is accurately controlled to improve the system stability and the resource utilization rate; low-cost scheduling fine tuning of cloud resources is realized; various business scenes and languages can be quickly adapted, and the development cost and time are reduced.

A virtualized cellular access node includes a control plane interface coupled to a physical cellular access node, a first virtualized network function that receives a first portion of data, a second virtualized network function that receives a second portion of data, and a third virtualized network function that receives a third portion of data. The control plane interface receives data related to a cellular network having cellular terminals. The first virtualized network function analyzes the first portion of data and generates a first instruction related to traffic allocation within the cellular network. The second virtualized network function analyzes the second portion of the data and generates a second instruction related to bandwidth allocation within the cellular network. The third virtualized network function analyzes a third portion of the data and generates a third instruction related to quality of service assignment to a first cellular terminal within the cellular network.

The invention belongs to the technical field of power systems, and relates to an RDMA protocol efficient analysis and forwarding method based on an RISC-V architecture, hardware acceleration of a protocol analysis and verification process is realized by introducing a hardware acceleration module and a customized RISC-V instruction set, so that the analysis speed is greatly improved, and the CPU load is reduced; in the protocol analysis process of a data packet, the flexibility and customizability of an RISC-V architecture are utilized, an instruction set is optimized according to the special requirements of an RDMA protocol, header information of the data packet can be efficiently extracted, CRC verification can be carried out, the load condition of each calculation unit can be monitored in real time through dynamic flow scheduling and load balancing and a hardware scheduling module, and the real-time performance of the data packet is improved. Flow distribution is intelligently adjusted, the overload problem of a single computing node is avoided, and efficient forwarding of data packets is ensured. Besides, based on the customized processing capability of the RISC-V architecture, the forwarding path of the data packet can be flexibly adjusted according to the real-time network topology and routing information, and the adaptability and the processing capability of the whole network are improved.

The invention provides an SDH / PDH payload real-time bandwidth analysis method based on time synchronization, and relates to the technical field of transmission networks, and the method comprises the steps: obtaining the network state information of each network working node in an optical transmission network; preprocessing the original data frame set to obtain an average effective load corresponding to each data frame in the data frame set, and calculating an effective load dynamic estimation value based on the average effective load and a historical average effective load; obtaining a network transmission resource allocation strategy of an optical link between any two adjacent network working nodes and a network transmission resource parameter corresponding to the network transmission resource allocation strategy according to a preset constraint condition and the effective load dynamic estimation value; and obtaining a comprehensive evaluation index of the current data frame according to the network transmission resource parameter and the load bandwidth performance function, and adjusting a flow distribution path of the optical transmission network according to the comprehensive evaluation index. According to the invention, the dynamic self-adaptive adjustment of the network flow can be realized.

The invention discloses a method and a system for optimizing a cargo flow transportation strategy. The method comprises the following steps of: establishing a full-flow simulation calculation super network model of containers from highway collection and distribution, railway collection and distribution, inland river port transfer and trunk line central bond port transportation to destination ports on the basis of three-dimensional traffic network transportation mode conditions; by calculating the transportation cost, the transportation time, the transfer cost and the transportation reliability of each transportation link in the super network model, establishing a generalized cost function for the cost, the time and the transportation volume of container freight; and according to the generalized cost function, container network traffic distribution is carried out, the path with the lowest generalized cost of all paths between the container starting point and the container ending point is calculated, and a cargo flow transportation strategy is formulated. According to the scheme, the total transportation volume and the transportation cost of the scheme under the conditions of large-scale networking and optimal transportation cost of a current situation and a planned port can be evaluated, and the transportation scheme is optimized and evaluated, so that the transportation economic benefit is improved.

The invention discloses a multi-satellite communication network dynamic beam scheduling and power control method, and belongs to the field of resource allocation in satellite communication. The implementation method comprises the following steps: constructing a multi-satellite communication network model, constructing a multi-satellite communication network data queue model based on the network model, and constructing a multi-satellite communication network energy queue model; constructing a queue control model based on a Lyapunov equation; constructing a joint optimization problem of hopping beam scheduling and power control based on a drift and penalty function; reconstructing and approximating the joint optimization problem of the hopping beam scheduling and the power control by using an SCA algorithm; decomposing an approximated joint optimization problem by adopting a Benders decomposition framework, wherein the joint optimization problem is divided into a power control sub-problem and a beam scheduling main problem; solving the power control sub-problem and the beam scheduling main problem to obtain an optimal solution; and iterative optimization is carried out, and dynamic beam scheduling and power control of the multi-satellite communication network are realized according to the optimal solution, so that a multi-satellite network dynamic system reaches long-term stability, and user fairness is realized on flow distribution.

This invention proposes a time-synchronized real-time bandwidth analysis method for SDH / PDH payloads, relating to the field of transmission network technology. The method includes: acquiring network status information of each network working node in the optical transmission network; preprocessing the original data frame set to obtain the average payload corresponding to each data frame, and calculating a dynamic estimate of the payload based on the average payload and historical average payloads; obtaining the network transmission resource allocation strategy for the optical link between any two adjacent network working nodes and the corresponding network transmission resource parameters according to preset constraints and the dynamic payload estimate; obtaining a comprehensive evaluation index for the current data frame based on the network transmission resource parameters and the payload bandwidth performance function, and adjusting the traffic allocation path of the optical transmission network according to the comprehensive evaluation index. This invention helps to achieve dynamic adaptive adjustment of network traffic.

The present invention relates to the field of satellite communication technology, and particularly to a satellite routing method based on dynamic celestial sphere region division. The method includes: dividing multiple nodes by using a clustering algorithm to obtain multiple virtual regions with load balance; optimizing the multiple virtual regions by using a local flooding optimization strategy to generate a preset propagation range of data packets; predicting the delay and congestion conditions of the links in the preset propagation range by using a recurrent neural network model according to historical link delay data, and dynamically adjusting the path selection and traffic allocation strategies based on the prediction results; calculating the additional delay of each path based on the delay and load conditions of different paths in the path selection and traffic allocation strategies, and calculating the traffic to be allocated for each path based on the additional delay. Thereby, the communication bottleneck problems such as network delay and increased packet loss rate caused by the dynamic changes of the network in low-earth orbit satellites and the Internet of Things are solved, and the efficient operation of the network in a dynamic environment is realized.

The invention discloses a multi-path traffic distribution method based on node parallel computing, and relates to the technical field of traffic flow distribution and computer application, and the method comprises the steps: modeling a traffic network into a computer directed graph composed of a node set and a segmental arc set, and loading a traffic origin-destination demand matrix; constructing an improved Logit multi-path random traffic distribution model to reduce the sensitivity of a path travel time unit and a network scale to a distribution result; a node-based multi-path flow distribution model is formed, and traffic flow iterative distribution is realized by updating the effective subsequent road section flow of the node; taking each terminal point as an independent unit, and executing a node-level multi-path traffic distribution calculation task; a parallel computing framework is designed, a global flow distribution problem is decomposed into node-level sub-problems, and distribution tasks are executed on a plurality of computing units at the same time. According to the method, efficient multi-path flow distribution of a large-scale traffic network is realized, and the calculation efficiency of traffic distribution is remarkably improved.

This invention provides a network adjustment method, apparatus, electronic device, and storage medium, relating to the field of data processing technology. The method includes: acquiring network performance information of each routing port at the current moment; wherein the network performance information includes priority flow control message information of the routing ports; inputting the network performance information of each routing port into a network congestion assessment model, and outputting first real-time network congestion level information of each routing port; and calculating network weight information of each routing port based on the first real-time network congestion level information of each routing port, so as to adjust the port traffic allocation of each routing port according to the network weight information.

The invention discloses a traffic network bottleneck identification method based on flow cascading in the technical field of traffic information control, and the method comprises the steps: obtaining road data and commuting behavior data in a target area, extracting the midpoint of each road in the road data, connecting the origin-destination space of the commuting behavior data to the midpoint of the nearest road, and obtaining the traffic network bottleneck identification result. And recording a corresponding index relationship between the origin-destination point and the midpoint of the road. The incremental traffic distribution algorithm is adopted to distribute the travel matrix of the spatial position information, the congestion effect generated by network flow cascade is simulated by iteratively updating the network edge weight, the network bottleneck under the network flow reconstruction is identified, the cascade conduction mechanism of the traffic network flow under the disturbance condition can be systematically described, and the traffic flow reconstruction efficiency is improved. Network bottlenecks having key influences on system stability are identified, and the response capability and structural toughness of urban risks are improved.

The present invention discloses a method for analyzing the total travel distance of multiple modes of transportation based on traffic distribution, which belongs to the technical field of calculation, estimation or counting. The method includes the following steps: clarifying the research area and time period; dividing traffic areas; constructing a road network and a bus line network; calculating the line network density and average station spacing of buses in the traffic area; conducting a questionnaire survey on residents' transportation travel; constructing a traffic distribution matrix and performing traffic distribution; calculating the non-linear coefficient of residents' transportation travel within the traffic area; constructing a calculation model for the distance from passengers to bus stops; and calculating the total travel distance of various transportation modes. The present invention comprehensively analyzes all aspects of the integrated transportation system, organically combining travel on the road network, travel within the traffic area, and travel by passengers to bus stops. It can systematically analyze the entire process of residents' transportation travel and accurately calculate the total travel distance of multiple transportation modes.

The invention discloses a traffic distribution method based on public transportation super network construction, which relates to the technical field of road traffic, and comprises the following steps: acquiring all bus station information, bus lines and traffic zone centroid point information in a target distribution area; generating real nodes and virtual nodes according to the bus station information and the bus route information; constructing a driving arc according to the virtual nodes; constructing a co-station transfer arc according to the real nodes and the virtual nodes; constructing a different-station transfer arc according to the real nodes; constructing an upper / lower network arc according to the real node and the centroid point of the traffic zone; according to the real node, the virtual node, the driving arc, the same-station transfer arc, the different-station transfer arc and the upper / lower network arc, constructing a bus super network; according to the method, the traffic flow is distributed to each arc section of the bus super network by adopting a multi-path-capacity limiting method, so that the bus distribution can comprehensively consider the influence of the transfer behavior, the distribution result of the traffic flow is closer to the reality, and the reasonability of the bus distribution is improved.

This application discloses a method, apparatus, computer device, and storage medium for allocating channel traffic, relating to the fields of computer and internet technology. The method includes: acquiring historical traffic records and constraints corresponding to at least two channels, where the constraints indicate the conditions that traffic allocated to the channel must meet; for a first channel among the at least two channels, determining a first predicted traffic volume for the first channel in the next prediction period based on the historical traffic records corresponding to the first channel; determining a first dynamic decision weight for the first channel in the next prediction period based on the first predicted traffic volume and the constraints corresponding to the first channel, where the first dynamic decision weight is used to adjust the weights of key parameters for traffic allocation in the next prediction period; and adjusting the traffic allocated to the first channel in the next prediction period based on the first dynamic decision weight. This application can effectively improve the efficiency of traffic allocation in multi-channel scenarios.

1. The name of the design product: test service configuration graphical user interface of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the graphical user interface displayed on the electronic device. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the present graphical user interface is used for test service configuration. The front view is the test service configuration home page. The user can jump to the interface change state diagram 1 by clicking the "traffic allocation mode" box of the topology diagram. The user can jump to the interface change state diagram 2 by clicking "next step" of the interface change state diagram 1 after setting the relevant parameters according to the interface prompt. The user can jump to the interface change state diagram 3 by clicking "submit" of the interface change state diagram 2 after setting the relevant parameters according to the interface prompt. 6. Other circumstances that need to be explained: "XX" in the interface represents replaceable text and / or numbers and / or letters and / or symbols.

The invention provides a micro-service component development method based on standard data analysis, a medium and a system, and belongs to the technical field of development methods.The micro-service component development method based on standard data analysis comprises the steps that a standard data analysis model is established for data hierarchical processing, a historical service request is processed by adopting a multi-dimensional Joseph ring algorithm to obtain an access calling sequence, service access parameters are calculated based on the access calling sequence, and an optimal communication flow distribution scheme is calculated by adopting a communication flow optimization equation set. The communication flow optimization equation set comprises a resource constraint equation, a flow balance equation, a time delay optimization equation and an overhead optimization equation, the resource constraint equation is used for limiting the total resource use amount, the flow balance equation is used for balancing the data flow, the time delay optimization equation is used for reducing the communication time delay, and the overhead optimization equation is used for reducing the total overhead of system operation; and constructing a service calling routing table and establishing a micro-service component registration center, and optimizing service resource allocation by adopting a multi-dimensional knapsack algorithm.