An access method based on a distributed core network

Abstract

The application provides an access method based on a distributed core network, and relates to the fields of telecommunications and networks.The access method based on the distributed core network comprises the following steps: network topology analysis, using a graph theory algorithm to analyze the physical and logical topology structure of the distributed core network, and identifying the nodes and links in the network; edge computing node selection, selecting the most suitable edge computing node based on the network topology graph and using a shortest path algorithm and edge node resource information; and intelligent routing configuration, configuring intelligent routing rules for each access device using a routing algorithm based on the network topology and edge computing node selection.Through the design of the edge computing node, the method integrates the edge computing node into the core network, so that the access device can be closer to the computing resources.This can reduce the time delay, improve the response speed, and support more edge computing applications, such as the Internet of Things and real-time video analysis.

Description

Technical Field

[0001] This invention relates to the field of telecommunications and network technology, specifically to an access method based on a distributed core network. Background Technology

[0002] Distributed core networks are an emerging network architecture designed to address the limitations and problems of traditional access methods. By distributing functionality and control to the network edge and access points, they offer higher performance, reliability, and flexibility. Distributed core networks utilize existing technologies such as Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and edge computing to achieve scalable network access. The access methods of distributed core networks draw upon and apply various existing technologies. SDN technology allows network administrators to centrally manage and program access devices for dynamic configuration and optimization. NFV technology provides flexible network function deployment methods by virtualizing network functions into software instances.

[0003] Existing technologies have many advantages in distributed core network access methods, but they still have some limitations, such as high latency, low response speed, high risk of network congestion after a certain number of users, and the inability to allow different types of applications and services to coexist on the same infrastructure. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an access method based on a distributed core network, which solves the problems of high latency, low response speed, high risk of network congestion, and the inability to allow different types of applications and services to coexist on the same infrastructure.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an access method based on a distributed core network, comprising the following steps:

[0006] S1: Network topology analysis, using graph theory algorithms, analyzes the physical and logical topology of the distributed core network, identifies nodes and links in the network, and generates a network topology graph, including the connection relationships between nodes;

[0007] S2: Edge computing node selection, based on the network topology map, using the shortest path algorithm and edge node resource information, selects the most suitable edge computing node to determine which edge computing node each access device should connect to;

[0008] S3: Intelligent routing configuration, based on network topology and edge computing node selection, uses routing algorithms to configure intelligent routing rules for each access device to generate an intelligent routing table, specifying the best path for data flow;

[0009] S4: Network slice allocation. Based on business needs, a network slice allocation algorithm is used to allocate network resources to different applications and services to create different network slices. Each slice has independent resource allocation.

[0010] S5: Security policy settings, using access control lists (ACLs) and encryption algorithms, set security policies for each access device and network slice to ensure the confidentiality and integrity of data and restrict unauthorized access;

[0011] S6: Load balancing configuration utilizes load balancing algorithms to dynamically allocate traffic to different core network nodes to avoid congestion, thereby ensuring balanced utilization of network resources and improving performance and availability.

[0012] S7: Resource optimization and adjustment. Using resource management algorithms, it monitors the usage of network resources and adjusts resources according to demand to maximize the utilization of network resources and ensure efficient operation.

[0013] S8: Data flow monitoring and analysis, implements data flow monitoring, uses data analysis algorithms to monitor network performance and data traffic to generate performance indicators and analysis reports for network optimization and troubleshooting;

[0014] S9: Dynamic adaptive adjustment. Based on the monitoring results of data flow monitoring and analysis, an adaptive algorithm is used to dynamically adjust network parameters and strategies to ensure that the network maintains high performance and stability in a constantly changing environment.

[0015] Preferably, network topology analysis, employing graph theory algorithms, analyzes the physical and logical topology of the distributed core network, identifying the nodes and links within the network. The specific steps include:

[0016] S101: Collect network topology data. Obtain relevant data on network topology from network devices, configuration files, or network management systems, including connections between devices, topology structure, and node attribute information. This is accomplished through network scanning or using APIs, thereby collecting network topology data.

[0017] S102: Establish a network topology model. Based on the collected network topology data, construct a network topology model. Use graph theory methods to represent network devices and connections as nodes and edges of a graph to form a network topology model.

[0018] S103: Analyze network topology characteristics, analyze the established network topology model, and extract some key features of the network topology;

[0019] S104: Detect network topology problems. Use network topology models and topology feature analysis results to detect potential network topology problems.

[0020] S105: Optimize network topology. Based on the list of detected network topology problems, optimize and improve the network topology.

[0021] Preferably, the edge computing node selection, based on the network topology graph, uses the shortest path algorithm and edge node resource information to select the most suitable edge computing node. The specific steps include:

[0022] S201: Requirements and Objectives Analysis, collecting and analyzing system requirements, including objectives for reducing latency, increasing network throughput, and enhancing data privacy and security, defining clear requirements and objectives;

[0023] S202: Node performance evaluation, which assesses the performance of available edge computing nodes, including computing power, storage capacity, network bandwidth, and latency, and assigns a performance score to each node;

[0024] S203: Network connectivity assessment, which evaluates the network connectivity between edge computing nodes and other nodes, including latency, bandwidth, and reliability, and assigns a network connectivity score to each node;

[0025] S204: Data privacy and security assessment, which evaluates the data privacy and security performance of edge computing nodes, including data protection mechanisms, authentication and access control, and assigns a data security score to each node;

[0026] S205: Cost and resource assessment, which comprehensively considers the cost and resource consumption of each edge computing node, including purchase or lease costs, energy consumption, maintenance and management costs, and assigns a cost score to each node.

[0027] Preferably, the intelligent routing configuration, based on network topology and edge computing node selection, involves configuring intelligent routing rules for each access device using routing algorithms. The specific steps include:

[0028] S301: Network topology analysis, which uses collected network topology information to analyze the connection relationships and topology between network devices, thereby generating a data structure that describes the network topology;

[0029] S302: Performance Measurement and Analysis. Run network performance measurement tools to collect performance data of network devices, including latency and bandwidth utilization. Generate a performance analysis report based on the collected data, providing performance metrics for each network device.

[0030] S303: Path calculation and selection. Based on network topology analysis and performance measurement and analysis, it uses routing algorithms to calculate the best path between different source and destination nodes and generates a path selection table containing the best path information from each source node to the destination node.

[0031] S304: Configuration generation and distribution. Based on the path selection table, configure the routing tables of routers and switches, distribute the best path information to network devices, generate a routing configuration file, and distribute it to network devices.

[0032] S305: Fault monitoring and automatic recovery. Implements a fault monitoring mechanism to monitor the status and connectivity of network devices. When a fault occurs, it automatically triggers a recovery mechanism to restore the network, thereby achieving automatic fault detection and recovery functions and ensuring high availability and stability of the network.

[0033] Preferably, network slice allocation, based on business needs, employs a network slice allocation algorithm to allocate network resources to different applications and services. The specific steps include:

[0034] S401: Business requirements analysis, analyzes the network resource requirements of different applications and services, including bandwidth, latency, and QoS requirements, and generates a business requirements table containing network resource requirements information for each application and service;

[0035] S402: Resource assessment and partitioning. Based on existing network resources, considering resource availability and characteristics, a resource assessment algorithm is used to partition resources and generate a resource partitioning table containing information on available network resources after partitioning.

[0036] S403: Network slice allocation algorithm design. Based on the service requirements table and resource allocation table, design a slice allocation algorithm, taking into account priority settings, bandwidth allocation, and traffic control factors, to generate a network slice allocation strategy, including slice priority and bandwidth allocation rule information.

[0037] S404: Slice allocation execution. Based on the network slice allocation strategy, the slice allocation algorithm is executed to allocate network resources to each application and service, and the slice allocation results are generated, including the amount of resources allocated to each slice and related configuration information.

[0038] S405: Resource monitoring and optimization. Monitors the resource usage and performance of slices. Based on the monitoring results, uses resource optimization algorithms to make dynamic adjustments and generate optimization and update strategies, including resource adjustment suggestions and related configuration update information.

[0039] Preferably, the security policy settings, employing Access Control Lists (ACLs) and encryption algorithms, include the following specific steps for setting security policies for each access device and network slice:

[0040] S501: Device and network slice identification. Collect and identify relevant information of all access devices and network slices, including name, IP address, MAC address and unique identifier. Analyze the functional and security requirements of each device and network slice to understand the data or services that need to be protected.

[0041] S502: Security policy objectives are defined, including the security objectives of each access device and network slice, such as confidentiality, integrity, and availability requirements, and the resources that require access control and encryption protection.

[0042] S503: ACL rule creation. Based on the device and network slice list, create ACL rules to control the flow of data packets. Determine the content of the ACL rule, including source IP address, destination IP address, and port number information. According to the security policy objectives, set the ACL rule to allow or deny specific types of traffic.

[0043] S504: Encryption algorithm configuration, identifying communication channels or data streams that need encryption protection, selecting appropriate encryption algorithms, using TLS / SSL for encrypted data transmission, configuring encryption algorithms, including key management and certificate management, thereby encrypting data;

[0044] S505: Security policy implementation and related processing. Deploy ACL rules to network devices to ensure that only authorized traffic can pass through. Enable encryption on the communication link to protect the confidentiality of data. In subsequent steps, obtain the device and network slice list, security policy target list, ACL rule set and encryption configuration results to ensure the correlation between steps.

[0045] Preferably, the load balancing configuration utilizes a load balancing algorithm to dynamically distribute traffic to different core network nodes to avoid congestion. Specific steps include:

[0046] S601: Core network node identification, collects and identifies relevant information of all core network nodes, including node performance indicators and network topology, analyzes the availability and load of each core network node, understands the differences between nodes and the current load status, and collects a list of core network nodes.

[0047] S602: Load balancing algorithm selection. Research feasible load balancing algorithms and select an appropriate load balancing algorithm based on the performance indicators and target requirements of core network nodes.

[0048] S603: Load balancing rule creation. Based on the core network node list and load balancing algorithm, create load balancing rules, determine the content of the load balancing rules, including source IP address, destination IP address, and port number information, and set rules according to the load balancing algorithm to dynamically distribute traffic to different core network nodes.

[0049] S604: Load detection and node monitoring monitors traffic load and detects the load status of each core network node in real time. Based on the load status, it dynamically updates node load information and records relevant node metrics.

[0050] S605: Load balancing implementation and optimization. Configure load balancing rules on load balancing devices or software to achieve dynamic traffic distribution, monitor traffic distribution and node load, and optimize and adjust based on load balancing algorithms and load status monitoring information. Perform regular load balancing strategy evaluation and adjustment based on actual needs and network topology changes.

[0051] Preferably, resource optimization and adjustment, using resource management algorithms, monitors network resource usage and adjusts resources according to demand. Specific steps include:

[0052] S701: Resource monitoring and data collection. Deploy a monitoring system to monitor network resource usage in real time, including CPU utilization, memory usage, network bandwidth, and disk space metrics. Collect and store the monitored resource usage data for subsequent analysis and decision-making.

[0053] S702: Performance evaluation and analysis. Based on the collected resource usage data, perform performance evaluation and analysis, analyze resource usage trends, peak periods, key resource bottleneck indicators, and identify potential performance problems and bottlenecks.

[0054] S703: Resource demand assessment and planning. Based on user needs and business requirements, assess the current resource demand and scale, determine resource quotas and priorities, and plan resource allocation strategies based on business importance and resource availability.

[0055] S704: Resource adjustment strategy selection. Research feasible resource adjustment algorithms and strategies, and select appropriate resource adjustment strategies based on performance evaluation and resource demand evaluation results to meet business needs and optimize resource utilization.

[0056] S705: Resource adjustment implementation and monitoring. Based on the selected resource adjustment strategy, implement resource adjustment operations, evaluate resource utilization, performance improvement and the degree to which business needs are met, and make necessary adjustments and optimizations based on the monitoring results.

[0057] Preferably, data flow monitoring and analysis, implementing data flow monitoring, and using data analysis algorithms to monitor network performance and data traffic, includes the following specific steps:

[0058] S801: Data Acquisition. Deploy appropriate network monitors or traffic collectors in the network to capture network data traffic, collect network traffic data using these devices, and store it in a designated data storage system.

[0059] S802: Preprocessing data. This involves preprocessing the collected raw data, including data cleaning, noise reduction, and format conversion. Data cleaning algorithms, anomaly detection algorithms, and interpolation algorithms are used to ensure the accuracy and consistency of the data, generating a clean and usable preprocessed dataset.

[0060] S803: Network performance analysis. It uses time series analysis algorithms to analyze preprocessed data, identify key indicators such as bottlenecks, latency, packet loss rate, and bandwidth utilization in the network, and thus analyze the network performance analysis results, including bottleneck location, latency, packet loss rate, and bandwidth utilization indicators.

[0061] S804: Data traffic analysis. Based on network performance analysis results, it uses traffic pattern recognition and anomaly detection algorithms to analyze preprocessed data, identify abnormal traffic, DDoS attacks, traffic fluctuations, and discover potential security risks.

[0062] S805: Performance and Traffic Visualization, which displays the results of network performance analysis and data traffic analysis through visualization tools.

[0063] Preferably, the dynamic adaptive adjustment, based on the monitoring results of data flow monitoring and analysis, employs an adaptive algorithm to dynamically adjust network parameters and strategies. The specific steps include:

[0064] S901: Data stream monitoring and acquisition, which periodically collects system performance data, user demand information and system load data by using sensors or monitoring equipment;

[0065] S902: Real-time data analysis and prediction. Using machine learning algorithms, time series analysis or neural networks, it performs real-time analysis and prediction on data obtained from data stream monitoring and acquisition to identify the current state of the system, performance trends and potential problems.

[0066] S903: Optimize target setting and strategy selection. Based on the analysis results in real-time data analysis and prediction, set optimization targets and select appropriate adjustment strategies.

[0067] S904: Real-time data analysis and prediction, using adaptive algorithms to dynamically adjust system parameters and strategies based on performance prediction and optimization objectives in real-time data analysis and prediction, as well as optimization objectives in strategy selection.

[0068] S905: System performance monitoring and feedback. Continuously monitor system performance, including real-time performance indicators, user satisfaction, and resource utilization. If the performance does not meet the target or an anomaly occurs, return to real-time data analysis and prediction to re-analyze the data, or make emergency adjustments according to predefined rules.

[0069] This invention provides an access method based on a distributed core network. It has the following advantages:

[0070] This invention integrates edge computing nodes into the core network through edge computing node design, allowing access devices to be closer to computing resources. This reduces latency, improves response speed, and supports more edge computing applications. Through intelligent routing configuration, the access method leverages the intelligent routing and load balancing capabilities of the distributed core network to dynamically select the optimal path based on traffic and network conditions, optimizing data transmission efficiency and reducing congestion risks. Furthermore, the network slicing allocation design provides network slicing functionality, allowing different types of applications and services to coexist on the same infrastructure and allocating and isolating resources as needed. This supports diverse business scenarios and improves network flexibility. Attached Figure Description

[0071] Figure 1 This is a schematic diagram of the main steps of the present invention;

[0072] Figure 2 This is a detailed schematic diagram of S1 of the present invention;

[0073] Figure 3 This is a detailed schematic diagram of S2 of the present invention;

[0074] Figure 4 This is a detailed schematic diagram of S3 of the present invention;

[0075] Figure 5 This is a detailed schematic diagram of S4 of the present invention;

[0076] Figure 6 This is a detailed schematic diagram of S5 of the present invention;

[0077] Figure 7 This is a detailed schematic diagram of S6 of the present invention;

[0078] Figure 8 This is a detailed schematic diagram of S7 of the present invention;

[0079] Figure 9 This is a detailed schematic diagram of S8 of the present invention;

[0080] Figure 10 This is a detailed schematic diagram of S9 of the present invention. Detailed Implementation

[0081] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0082] Example:

[0083] like Figure 1-10 As shown, this embodiment of the invention provides an access method based on a distributed core network, including the following steps:

[0084] S1: Network topology analysis, using graph theory algorithms, analyzes the physical and logical topology of the distributed core network, identifies nodes and links in the network, and generates a network topology graph, including the connection relationships between nodes;

[0085] S2: Edge computing node selection, based on the network topology map, using the shortest path algorithm and edge node resource information, selects the most suitable edge computing node to determine which edge computing node each access device should connect to;

[0086] S3: Intelligent routing configuration, based on network topology and edge computing node selection, uses routing algorithms to configure intelligent routing rules for each access device to generate an intelligent routing table, specifying the best path for data flow;

[0087] S4: Network slice allocation. Based on business needs, a network slice allocation algorithm is used to allocate network resources to different applications and services to create different network slices. Each slice has independent resource allocation.

[0088] S5: Security policy settings, using access control lists (ACLs) and encryption algorithms, set security policies for each access device and network slice to ensure the confidentiality and integrity of data and restrict unauthorized access;

[0089] S6: Load balancing configuration utilizes load balancing algorithms to dynamically allocate traffic to different core network nodes to avoid congestion, thereby ensuring balanced utilization of network resources and improving performance and availability.

[0090] S7: Resource optimization and adjustment. Using resource management algorithms, it monitors the usage of network resources and adjusts resources according to demand to maximize the utilization of network resources and ensure efficient operation.

[0091] S8: Data flow monitoring and analysis, implements data flow monitoring, uses data analysis algorithms to monitor network performance and data traffic to generate performance indicators and analysis reports for network optimization and troubleshooting;

[0092] S9: Dynamic adaptive adjustment. Based on the monitoring results of data flow monitoring and analysis, an adaptive algorithm is used to dynamically adjust network parameters and strategies to ensure that the network maintains high performance and stability in a constantly changing environment.

[0093] Network topology analysis, employing graph theory algorithms, analyzes the physical and logical topology of the distributed core network, identifying nodes and links to generate a network topology map, including connections between nodes. Edge computing node selection, based on the network topology map and using shortest path algorithms and edge node resource information, selects the most suitable edge computing node to determine which edge computing node each access device should connect to. Intelligent routing configuration, based on the network topology and edge computing node selection, uses routing algorithms to configure intelligent routing rules for each access device, generating intelligent routing tables that specify the optimal path for data flows. Network slice allocation, based on business needs, uses network slice allocation algorithms to allocate network resources for different applications and services, creating different network slices, each with independent resource allocation. Security policy settings, employing access control lists (ACLs) and encryption algorithms, set security policies for each access device and network slice to ensure data confidentiality and integrity, restricting unauthorized access. Load balancing configuration utilizes load balancing algorithms to dynamically allocate traffic to different core network nodes to avoid congestion. This design ensures balanced utilization of network resources, improving performance and availability. Resource optimization and adjustment uses resource management algorithms to monitor network resource usage and adjust resources according to demand. This design maximizes network resource utilization and ensures efficient operation. Data flow monitoring and analysis implements data flow monitoring and uses data analysis algorithms to monitor network performance and data traffic. This design generates performance indicators and analysis reports for network optimization and troubleshooting. Dynamic adaptive adjustment uses adaptive algorithms to dynamically adjust network parameters and strategies based on the monitoring results of data flow monitoring and analysis. This design ensures the network maintains high performance and stability in a constantly changing environment. These steps form a complete distributed core network access method. Each step depends on the result of the previous step to ensure the correlation and sequential execution between steps. Through this method, efficient, secure, and scalable distributed core network access can be achieved.

[0094] Network topology analysis, employing graph theory algorithms, analyzes the physical and logical topology of a distributed core network, identifying nodes and links within the network. The specific steps include:

[0095] S101: Collect network topology data. Obtain relevant data on network topology from network devices, configuration files, or network management systems, including connections between devices, topology structure, and node attribute information. This can be done through network scanning or by using APIs to collect network topology data.

[0096] S102: Establish a network topology model. Based on the collected network topology data, construct a network topology model. Graph theory methods can be used to represent network devices and connections as nodes and edges of a graph to form a network topology model.

[0097] S103: Analyze network topology characteristics, analyze the established network topology model, extract some key features of the network topology, such as calculating the degree centrality, betweenness centrality and compact centrality of nodes in the network to evaluate the importance of nodes and the centrality of the network, and conduct analysis.

[0098] S104: Detect network topology problems. Using network topology models and topology feature analysis results, detect potential network topology problems such as loops, isolated nodes, and redundant paths. Graph traversal algorithms and loop detection algorithms can be used for detection.

[0099] S105: Optimize network topology. Based on the list of detected network topology problems, optimize and improve the network topology. For example, improve network performance and reliability by adjusting connectivity, removing isolated nodes, or adding redundant paths, thereby optimizing the network topology.

[0100] First, a network topology model is established by collecting network topology data. Then, the characteristics of the network topology model are analyzed to determine the list of network topology problems. Finally, the network topology is optimized.

[0101] Edge computing node selection, based on the network topology graph, employs the shortest path algorithm and edge node resource information. The specific steps for selecting the most suitable edge computing node include:

[0102] S202: Node performance evaluation. Evaluate the performance of available edge computing nodes, including computing power, storage capacity, network bandwidth, latency, etc., and assign a performance score to each node, such as "Node A's computing power score is 90%".

[0103] S203: Network connectivity assessment, which evaluates the network connectivity between edge computing nodes and other nodes, including latency, bandwidth, reliability, etc., and assigns a network connectivity score to each node, such as "the network latency score of node B is 5 milliseconds".

[0104] S204: Data privacy and security assessment, which evaluates the data privacy and security performance of edge computing nodes, including data protection mechanisms, authentication and access control, and assigns a data security score to each node, such as "Node C's data encryption score is 95%";

[0105] S205: Cost and resource assessment, which comprehensively considers the cost and resource consumption of each edge computing node, including purchase or lease costs, energy consumption, maintenance and management costs, etc., and assigns a cost score to each node, such as "the cost score of node D is 80%".

[0106] First, by collecting and analyzing system requirements, clear needs and objectives are defined, such as "low latency requirements" or "high data security." Then, a performance score is assigned to each node, such as "Node A's computing power score is 90%." A network connectivity score is assigned to each node, such as "Node B's network latency score is 5 milliseconds." A data security score is assigned to each node, such as "Node C's data encryption score is 95%." The performance score obtained in step S202 may affect the network connectivity score in step 3, because a node with poor performance may lead to higher latency. Similarly, the data privacy and security score in step 4 may affect the cost score in step S205, because implementing more advanced security measures may increase costs.

[0107] Intelligent routing configuration, based on network topology and edge computing node selection, involves configuring intelligent routing rules for each access device using routing algorithms. The specific steps include:

[0108] S301: Network topology analysis. Utilizes collected network topology information and analyzes the connection relationships and topology between network devices to generate a data structure describing the network topology, such as a figure or chart.

[0109] S302: Performance Measurement and Analysis. Run network performance measurement tools to collect performance data of network devices, including latency, bandwidth utilization, etc., and generate a performance analysis report based on the collected data, providing performance indicators for each network device.

[0110] S303: Path calculation and selection. Based on network topology analysis and performance measurement and analysis, it uses routing algorithms to calculate the best path between different source and destination nodes and generates a path selection table containing the best path information from each source node to the destination node.

[0111] S304: Configuration generation and distribution. Based on the path selection table, configure the routing tables of routers and switches, distribute the best path information to network devices, generate a routing configuration file, and distribute it to network devices.

[0112] S305: Fault monitoring and automatic recovery. Implements a fault monitoring mechanism to monitor the status and connectivity of network devices. When a fault occurs, it automatically triggers a recovery mechanism to restore the network, thereby achieving automatic fault detection and recovery functions and ensuring high availability and stability of the network.

[0113] First, a data structure describing the network topology is generated, such as a diagram or chart. Then, a performance analysis report is generated, providing performance metrics for each network device. Finally, a path selection table is generated, containing the optimal path information from each source node to the target node. A routing configuration file is generated and distributed to the network devices. When a network failure occurs, fault monitoring and automatic recovery can realize the automatic fault detection and recovery function of the network, ensuring the high availability and stability of the network.

[0114] Network slicing allocation, based on business needs, employs a network slicing allocation algorithm to allocate network resources to different applications and services. The specific steps include:

[0115] S401: Business requirements analysis, analyzes the network resource requirements of different applications and services, including bandwidth, latency, QoS requirements, etc., and generates a business requirements table containing network resource requirements information for each application and service.

[0116] S402: Resource assessment and partitioning. Based on existing network resources, considering resource availability and characteristics, a resource assessment algorithm is used to partition resources and generate a resource partitioning table containing information on available network resources after partitioning.

[0117] S403: Network slice allocation algorithm design. Based on the service requirements table and resource allocation table, design a slice allocation algorithm, taking into account factors such as priority settings, bandwidth allocation, and flow control, to generate a network slice allocation strategy, including information such as slice priority and bandwidth allocation rules.

[0118] S404: Slice allocation execution. Based on the network slice allocation strategy, the slice allocation algorithm is executed to allocate network resources to each application and service, and the slice allocation results are generated, including the amount of resources allocated to each slice and related configuration information.

[0119] S405: Resource monitoring and optimization. Monitors the resource usage and performance of slices. Based on the monitoring results, uses resource optimization algorithms to make dynamic adjustments and generate optimization and update strategies, including resource adjustment suggestions and related configuration update information.

[0120] Security policy settings, employing Access Control Lists (ACLs) and encryption algorithms, include the following specific steps for configuring security policies for each access device and network slice:

[0121] S501: Device and network slice identification, collects and identifies relevant information of all access devices and network slices, including unique identifiers such as name, IP address, and MAC address;

[0122] S502: Security policy objectives are defined, including the security objectives of each access device and network slice, such as confidentiality, integrity, availability, etc., and the resources that need to be access controlled and encrypted are defined.

[0123] S503: ACL rule creation. Based on the device and network slice list, create ACL rules to control the flow of data packets. Determine the content of the ACL rule, including information such as source IP address, destination IP address, and port number. According to the security policy objectives, set the ACL rule to allow or deny specific types of traffic.

[0124] S504: Encryption algorithm configuration, identifying communication channels or data streams that need encryption protection, selecting appropriate encryption algorithms, such as TLS / SSL, for encrypting data transmission, and configuring encryption algorithms, including key management and certificate management;

[0125] S505: Security policy implementation and related processing. Deploy ACL rules to network devices to ensure that only authorized traffic can pass through. Enable encryption on the communication link to protect the confidentiality of data. In subsequent steps, obtain the device and network slice list, security policy target list, ACL rule set and encryption configuration results to ensure the correlation between steps.

[0126] This method, through specific execution steps and associated processing, enables the setting of security policies for each access device and network slice. Please customize it according to your specific needs.

[0127] Load balancing configuration, which uses load balancing algorithms to dynamically distribute traffic to different core network nodes to avoid congestion, includes the following specific steps:

[0128] S601: Core network node identification. Collect and identify relevant information of all core network nodes, including node performance indicators (such as processing capacity, load status, etc.) and network topology, analyze the availability and load status of each core network node, and understand the differences between nodes and their current load status.

[0129] S602: Load balancing algorithm selection. Research feasible load balancing algorithms, such as round-robin, least connections, weighted round-robin, etc., and select an appropriate load balancing algorithm based on the performance indicators and target requirements of the core network nodes.

[0130] S603: Load balancing rule creation. Based on the core network node list and load balancing algorithm, create load balancing rules, determine the content of the load balancing rules, including source IP address, destination IP address, port number and other information, and set rules according to the load balancing algorithm to dynamically distribute traffic to different core network nodes.

[0131] S604: Load Detection and Node Monitoring. Monitors traffic load and detects the load status of each core network node in real time. Based on the load situation, it dynamically updates node load information and records relevant node metrics such as load ratio and response time.

[0132] S605: Load balancing implementation and optimization. Configure load balancing rules on load balancing devices or software to achieve dynamic traffic distribution, monitor traffic distribution and node load, and optimize and adjust based on load balancing algorithms and load status monitoring information. Perform regular load balancing strategy evaluation and adjustment based on actual needs and network topology changes.

[0133] This method achieves the goal of dynamically allocating traffic to avoid congestion through steps such as identifying core network nodes, selecting load balancing algorithms, creating load balancing rules, performing load detection and node monitoring, and implementation and optimization. Please configure and optimize accordingly based on your specific situation.

[0134] Resource optimization and adjustment, using resource management algorithms, monitors network resource usage and adjusts resources according to demand. Specific steps include:

[0135] S701: Resource monitoring and data collection. Deploy a monitoring system to monitor network resource usage in real time, including indicators such as CPU utilization, memory usage, network bandwidth, and disk space. Collect and store the monitored resource usage data for subsequent analysis and decision-making.

[0136] S702: Performance evaluation and analysis. Based on the collected resource usage data, performance evaluation and analysis are performed to analyze key indicators such as resource usage trends, peak periods, and resource bottlenecks, and to identify potential performance problems and bottlenecks.

[0137] S703: Resource demand assessment and planning. Based on user needs and business requirements, assess the current resource demand and scale, determine resource quotas and priorities, and plan resource allocation strategies based on business importance and resource availability.

[0138] S704: Resource adjustment strategy selection. Research feasible resource adjustment algorithms and strategies, such as load balancing, dynamic allocation, and resource optimization. Based on performance evaluation and resource demand evaluation results, select appropriate resource adjustment strategies to meet business needs and optimize resource utilization.

[0139] S705: Resource adjustment implementation and monitoring. Based on the selected resource adjustment strategy, implement resource adjustment operations, such as adding or reducing computing nodes, adjusting bandwidth limits, etc., monitor the effect of resource adjustment, evaluate resource utilization, performance improvement and the degree to which business needs are met, and make necessary adjustments and optimizations based on the monitoring results.

[0140] This method achieves the goal of adjusting resources according to demand through steps such as resource monitoring and data collection, performance evaluation and analysis, resource demand assessment and planning, selection of resource adjustment strategies, and implementation and monitoring of resource adjustments. Please select appropriate resource management algorithms and optimization strategies based on your specific circumstances, and make appropriate configurations and adjustments.

[0141] First, a business requirements table is generated, containing network resource requirements for each application and service. Then, a resource allocation table is generated, containing available network resources after allocation. Next, a network slice allocation strategy is generated, including slice priority, bandwidth allocation rules, and other information. Finally, slice allocation results are generated, containing the amount of resources allocated to each slice and related configuration information.

[0142] Data flow monitoring and analysis, specifically the steps involved in implementing data flow monitoring and using data analysis algorithms to monitor network performance and data traffic, include:

[0143] S801: Data acquisition, using network monitoring equipment or traffic collectors to capture and record network data traffic in real time;

[0144] S802: Preprocessing data, which involves preprocessing the collected raw data, including data cleaning, noise reduction, and format conversion.

[0145] S803: Network performance analysis, which uses time series analysis algorithms to analyze preprocessed data and identify key indicators such as network bottlenecks, latency, packet loss rate, and bandwidth utilization.

[0146] S804: Data traffic analysis. Based on network performance analysis results, it uses traffic pattern recognition and anomaly detection algorithms to analyze preprocessed data, identify abnormal traffic, DDoS attacks, traffic fluctuations, and other issues, and discover potential security risks.

[0147] S805: Performance and Traffic Visualization. It displays the results of network performance analysis and data traffic analysis through visualization tools, such as charts and dashboards, so that network administrators or maintenance personnel can more intuitively understand and monitor network performance and traffic.

[0148] By following the steps above, data flow monitoring can be implemented, and data analysis algorithms can be used to monitor network performance and data traffic. This approach can help identify potential problems early, optimize network performance, and respond to security threats promptly.

[0149] Dynamic adaptive adjustment, based on the monitoring results of data flow monitoring and analysis, employs adaptive algorithms to dynamically adjust network parameters and strategies. The specific steps include:

[0150] S901: Data stream monitoring and acquisition, which periodically collects system performance data, user demand information and system load data by using sensors or monitoring equipment;

[0151] S902: Real-time data analysis and prediction. Utilizing machine learning algorithms, such as time series analysis or neural networks, to perform real-time analysis and prediction on data obtained from data stream monitoring and acquisition in order to identify the current state of the system, performance trends, and potential problems.

[0152] S903: Optimize target setting and strategy selection. Based on the analysis results from real-time data analysis and forecasting, set optimization targets, such as minimizing latency, maximizing throughput, or optimal energy consumption. Select appropriate adjustment strategies, such as parameter tuning, load balancing, or path optimization.

[0153] S904: Real-time data analysis and prediction, using adaptive algorithms such as reinforcement learning, genetic algorithms or fuzzy control, dynamically adjusts system parameters and strategies based on performance prediction and optimization objectives in real-time data analysis and prediction, and optimization objectives in strategy selection.

[0154] S905: System performance monitoring and feedback. Continuously monitor system performance, including real-time performance indicators, user satisfaction, and resource utilization. If the performance does not meet the target or an anomaly occurs, return to real-time data analysis and prediction to re-analyze the data, or make emergency adjustments according to predefined rules.

[0155] In step S902, the preprocessing process generates cleaned, uniformly formatted data results, which are used as input to the network performance analysis algorithm in step S903. The result of step S903, i.e., the network performance analysis result, serves as input to the data traffic analysis algorithm in step S904, enabling more accurate identification and analysis of abnormal traffic and security risks. Finally, the results of steps S904 and S905 are combined and presented in a visual format to network administrators or operations personnel, enabling monitoring and analysis of network performance and data traffic.

[0156] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An access method based on a distributed core network, characterized in that, Includes the following steps: Network topology analysis employs graph theory algorithms to analyze the physical and logical topology of a distributed core network and identify nodes and links within the network. Edge computing node selection is based on the network topology map, using the shortest path algorithm and edge node resource information to select the most suitable edge computing node; Intelligent routing configuration, based on network topology and edge computing node selection, uses routing algorithms to configure intelligent routing rules for each access device to generate an intelligent routing table, specifying the best path for data flow; Network slice allocation: Based on business needs, a network slice allocation algorithm is used to allocate network resources to different applications and services to create different network slices, each slice having independent resource allocation; Security policy settings employ access control lists (ACLs) and encryption algorithms to set security policies for each access device and network slice, thereby ensuring the confidentiality and integrity of data and restricting unauthorized access; Load balancing configuration utilizes load balancing algorithms to dynamically distribute traffic to different core network nodes to avoid congestion, thereby ensuring balanced utilization of network resources and improving performance and availability. Resource optimization and adjustment: Using resource management algorithms, monitoring network resource usage, and adjusting resources according to demand to maximize network resource utilization and ensure efficient operation; Data flow monitoring and analysis: Implement data flow monitoring, use data analysis algorithms to monitor network performance and data traffic to generate performance indicators and analysis reports for network optimization and troubleshooting. Dynamic adaptive adjustment: Based on the monitoring results of data flow monitoring and analysis, adaptive algorithms are used to dynamically adjust network parameters and strategies to ensure that the network maintains high performance and stability in a constantly changing environment. Edge computing node selection, based on the network topology graph, employs the shortest path algorithm and edge node resource information. The specific steps for selecting the most suitable edge computing node include: Requirements and objectives analysis: Collect and analyze system requirements, including objectives for reducing latency, increasing network throughput, and enhancing data privacy and security; define clear requirements and objectives. Node performance evaluation assesses the performance of available edge computing nodes, including computing power, storage capacity, network bandwidth, and latency, and assigns a performance score to each node. Network connectivity assessment evaluates the network connectivity between edge computing nodes and other nodes, including latency, bandwidth, and reliability, and assigns a network connectivity score to each node; Data privacy and security assessment evaluates the data privacy and security performance of edge computing nodes, including data protection mechanisms, authentication and access control, and assigns a data security score to each node; Cost and resource assessment comprehensively considers the cost and resource consumption of each edge computing node, including purchase or lease costs, energy consumption, maintenance and management costs, and assigns a cost score to each node.

2. The access method based on a distributed core network according to claim 1, characterized in that: Network topology analysis, employing graph theory algorithms, analyzes the physical and logical topology of a distributed core network, identifying nodes and links within the network. The specific steps include: Collect network topology data by obtaining relevant data on network topology from network devices, configuration files, or network management systems, including connections between devices, topology structure, and node attribute information. This can be done through network scanning or by using APIs. Establish a network topology model. Based on the collected network topology data, construct a network topology model and use graph theory methods to represent network devices and connections as nodes and edges of a graph to form a network topology model. Analyze network topology characteristics, analyze the established network topology model, and extract some key features of the network topology; Detect network topology problems by using network topology models and topology feature analysis results to identify potential network topology issues; Optimize network topology: Based on the list of detected network topology issues, optimize and improve the network topology.

3. The access method based on a distributed core network according to claim 1, characterized in that: Intelligent routing configuration, based on network topology and edge computing node selection, involves configuring intelligent routing rules for each access device using routing algorithms. The specific steps include: Network topology analysis utilizes collected network topology information and analyzes the connection relationships and topology between network devices to generate a data structure describing the network topology. Performance measurement and analysis: Run network performance measurement tools to collect performance data of network devices, including latency and bandwidth utilization. Generate a performance analysis report based on the collected data, providing performance metrics for each network device. Path calculation and selection, based on network topology analysis and performance measurement and analysis, uses routing algorithms to calculate the best path between different source and target nodes, and generates a path selection table containing the best path information from each source node to the target node; Configuration generation and distribution: Based on the path selection table, configure the routing tables of routers and switches, distribute the best path information to network devices, generate a routing configuration file, and distribute it to the network devices; Fault monitoring and automatic recovery: Implement a fault monitoring mechanism to monitor the status and connectivity of network devices. When a fault occurs, automatically trigger the recovery mechanism to restore the network, thereby achieving automatic fault detection and recovery functions and ensuring high availability and stability of the network.

4. The access method based on a distributed core network according to claim 1, characterized in that: Network slicing allocation, based on business needs, employs a network slicing allocation algorithm to allocate network resources to different applications and services. The specific steps include: Business requirements analysis involves analyzing the network resource requirements of different applications and services, including bandwidth, latency, and QoS requirements, and generating a business requirements table containing network resource requirements information for each application and service. Resource assessment and allocation: Based on existing network resources, considering resource availability and characteristics, a resource assessment algorithm is used to allocate resources and generate a resource allocation table containing information on available network resources after allocation. The network slice allocation algorithm is designed based on the business requirements table and resource allocation table. It takes into account factors such as priority settings, bandwidth allocation, and traffic control to generate a network slice allocation strategy, including slice priority and bandwidth allocation rule information. Slice allocation execution: Based on the network slice allocation strategy, the slice allocation algorithm is executed to allocate network resources to each application and service, and slice allocation results are generated, including the amount of resources allocated to each slice and related configuration information; Resource monitoring and optimization involves monitoring the resource usage and performance of slices. Based on the monitoring results, resource optimization algorithms are used for dynamic adjustments to generate optimization and update strategies, including resource adjustment suggestions and related configuration update information.

5. The access method based on a distributed core network according to claim 1, characterized in that: Security policy settings, employing Access Control Lists (ACLs) and encryption algorithms, involve the following specific steps for configuring security policies for each access device and network slice: Device and network slice identification: Collect and identify relevant information of all access devices and network slices, including name, IP address, MAC address and unique identifier; analyze the functional and security requirements of each device and network slice; and understand the data or services that need to be protected. Security policy objectives are defined, including the security objectives for each access device and network slice, such as confidentiality, integrity, and availability requirements, and the resources that require access control and encryption protection are defined. ACL rule creation: Based on the device and network slice list, ACL rules are created to control the flow of data packets. The content of the ACL rule is determined, including source IP address, destination IP address, and port number information. According to the security policy objectives, ACL rules are set to allow or deny specific types of traffic. Encryption algorithm configuration involves identifying communication channels or data streams that require encryption protection, selecting appropriate encryption algorithms, using TLS / SSL for encrypted data transmission, and configuring encryption algorithms, including key management and certificate management, to encrypt data. Security policy implementation and related processing: Deploy ACL rules to network devices to ensure that only authorized traffic can pass through; enable encryption on communication links to protect data confidentiality; and obtain the results of device and network slice lists, security policy target lists, ACL rule sets, and encryption configurations in subsequent steps to ensure the correlation between steps.

6. The access method based on a distributed core network according to claim 1, characterized in that: Load balancing configuration, which uses load balancing algorithms to dynamically distribute traffic to different core network nodes to avoid congestion, includes the following specific steps: Core network node identification involves collecting and identifying relevant information about all core network nodes, including node performance metrics and network topology, analyzing the availability and load of each core network node, understanding the differences between nodes and their current load status, and collecting a list of core network nodes. Load balancing algorithm selection involves researching feasible load balancing algorithms and selecting an appropriate one based on the performance indicators and target requirements of core network nodes. Load balancing rule creation is based on the core network node list and load balancing algorithm. It creates load balancing rules, determines the content of the load balancing rules, including source IP address, destination IP address, and port number information, and sets rules according to the load balancing algorithm to dynamically distribute traffic to different core network nodes. Load detection and node monitoring monitor traffic load and detect the load status of each core network node in real time; based on the load status, dynamically update the node load information and record the relevant node indicators. Load balancing implementation and optimization involves configuring load balancing rules onto load balancing devices or software to achieve dynamic traffic distribution, monitor traffic distribution and node load, and optimize and adjust based on load balancing algorithms and load status monitoring information. Regular load balancing strategies should also be evaluated and adjusted according to actual needs and network topology changes.

7. The access method based on a distributed core network according to claim 1, characterized in that: Resource optimization and adjustment, using resource management algorithms, monitors network resource usage and adjusts resources according to demand. Specific steps include: Resource monitoring and data collection: Deploy a monitoring system to monitor network resource usage in real time, including CPU utilization, memory usage, network bandwidth, and disk space metrics. Collect and store the monitored resource usage data for subsequent analysis and decision-making. Performance evaluation and analysis: Based on the collected resource usage data, we conduct performance evaluation and analysis, analyze resource usage trends, peak periods, key indicators of resource bottlenecks, and identify potential performance problems and bottlenecks. Resource demand assessment and planning: Based on user needs and business requirements, assess the current resource demand and scale, determine resource quotas and priorities, and plan resource allocation strategies based on business importance and resource availability. Resource adjustment strategy selection involves researching feasible resource adjustment algorithms and strategies, and selecting appropriate resource adjustment strategies based on performance evaluation and resource demand evaluation results to meet business needs and optimize resource utilization. Implement and monitor resource adjustments. Based on the selected resource adjustment strategy, implement resource adjustment operations, evaluate resource utilization, performance improvement, and the degree to which business needs are met, and make necessary adjustments and optimizations based on the monitoring results.

8. The access method based on a distributed core network according to claim 1, characterized in that: Data flow monitoring and analysis, specifically the steps involved in implementing data flow monitoring and using data analysis algorithms to monitor network performance and data traffic, include: Data acquisition involves deploying appropriate network monitors or traffic collectors in the network to capture network data traffic, using these devices to collect network traffic data, and storing it in a designated data storage system. Data preprocessing involves preprocessing the collected raw data, including data cleaning, noise reduction, and format conversion. Data cleaning algorithms, anomaly detection algorithms, and interpolation algorithms are used to ensure the accuracy and consistency of the data, generating a clean and usable preprocessed dataset. Network performance analysis uses time series analysis algorithms to analyze preprocessed data, identify key indicators such as bottlenecks, latency, packet loss rate, and bandwidth utilization in the network, and thus analyze the network performance analysis results, including bottleneck location, latency, packet loss rate, and bandwidth utilization indicators. Data traffic analysis, based on network performance analysis results, uses traffic pattern recognition and anomaly detection algorithms to analyze preprocessed data, identify abnormal traffic, DDoS attacks, traffic fluctuations, and discover potential security risks; Performance and traffic visualization: The results of network performance analysis and data traffic analysis are displayed using visualization tools.

9. The access method based on a distributed core network according to claim 1, characterized in that: Dynamic adaptive adjustment, based on the monitoring results of data flow monitoring and analysis, employs adaptive algorithms to dynamically adjust network parameters and strategies. The specific steps include: Data stream monitoring and acquisition involves periodically collecting system performance data, user demand information, and system load data using sensors or monitoring equipment. Real-time data analysis and prediction utilizes machine learning algorithms, employing time series analysis or neural networks, to perform real-time analysis and prediction on data obtained from data stream monitoring and acquisition, in order to identify the current state of the system, performance trends, and potential problems. Optimize target setting and strategy selection by setting optimization targets and selecting appropriate adjustment strategies based on the analysis results of real-time data analysis and prediction. Real-time data analysis and prediction uses adaptive algorithms to dynamically adjust system parameters and strategies based on performance prediction and optimization objectives in real-time data analysis and prediction, as well as optimization objectives in strategy selection. System performance monitoring and feedback: Continuously monitor system performance, including real-time performance indicators, user satisfaction, and resource utilization. If performance fails to meet targets or anomalies occur, return to real-time data analysis and prediction to re-analyze the data, or make emergency adjustments according to predefined rules.

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