Electric power communication resource topological optimization method and system based on graph database

Abstract

The invention relates to the technical field of electric power communication, in particular to an electric power communication resource topological optimization method and system based on a graph database. The specific implementation process comprises the following steps: constructing an electric power communication resource topological graph comprising communication exchange nodes, data transmission links and attribute information through a graph database; analyzing and quantifying the received business type into a routing constraint condition according to a business service level protocol; performing dynamic weighting calculation on each candidate communication path meeting the routing constraint condition, evaluating comprehensive performance indexes and outputting an optimal communication path; and converting the optimal communication path into a topology configuration instruction capable of guiding network equipment to carry out data deployment, and carrying out dynamic optimization on the power communication resource topology. According to the method, the service quality requirements of different services are quantified into dynamically adjusted routing constraints and weights, so that reasonable allocation of power communication resources and effective optimization of network topology are realized, and the working efficiency of a power communication resource network is improved.

Description

Technical Field

[0001] The present invention relates to the field of power communication technology, and in particular to a method and system for optimizing power communication resource topology based on a graph database. Background Art

[0002] In the field of power communication technology, the use of graph databases for topological analysis of resource networks, which carry large amounts of data and exchange traffic, has become a cutting-edge technology. By abstracting data exchange devices such as switches and routers in power communication resource networks as network nodes and transmission media such as optical fibers and cables as communication links, graph databases can establish network topology models that accurately reflect the interconnections and transmission properties between network elements. Compared to traditional technologies, the use of graph databases can effectively improve the real-time perception of power communication resource network topology and the efficiency of routing calculations under multi-dimensional constraints.

[0003] However, when faced with conflicting scenarios such as transmission latency and bandwidth bottlenecks, graph databases often fail to proactively optimize network topology based on the quality of service requirements of different services, such as relay protection and data collection. This results in the inability to optimally allocate power communication resources during critical situations such as traffic bursts, limiting the efficiency of the entire power communication network.

[0004] To this end, a power communication resource topology optimization method and system based on graph database is proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for optimizing the topology of power communication resources based on a graph database, and to realize topological analysis and optimization of the power communication resource network by introducing a service level agreement into the graph database.

[0006] To achieve the above object, the present invention provides the following technical solutions: The power communication resource topology optimization method based on graph database includes: A graph database is used to construct a topological map of power communication resources, including information on communication exchange nodes, data transmission links, and attributes. The received service types are automatically parsed and quantified into routing constraints based on the performance indicators preset in the built-in service level agreement. Performing dynamic weighted calculation on each candidate communication path that meets the routing constraint condition to obtain a comprehensive performance index; outputting an optimal communication path by evaluating the comprehensive performance index of each candidate communication path; The optimal communication path is automatically converted into a topology configuration instruction that can guide network devices to perform data deployment, and the power communication resource topology is dynamically optimized.

[0007] Preferably, the specific implementation process of constructing a power communication resource topology map including communication exchange nodes, data transmission links and attribute information through a graph database includes: Establishing communication exchange nodes based on the power communication devices used in the power communication resource network; establishing data transmission links connecting the communication exchange nodes based on the connection relationships between the power communication devices; Configuring attribute information for the communication exchange node and the data transmission link according to the device information of the power communication device, wherein the attribute information includes device type, geographical location, link bandwidth, transmission delay, and reliability; Based on the communication exchange nodes, data transmission links and attribute information, a power communication resource topology diagram including physical connections and logical relationships between power communication devices is constructed.

[0008] Preferably, the specific implementation process of automatically parsing and quantifying the received service type into routing constraints according to the performance indicators preset in the built-in service level agreement includes: Preset service levels based on the criticality and communication requirements of the power communication service type, and set performance indicators for each service level; the performance indicators include bandwidth requirements, latency limits, and reliability; Establish a correspondence between the power communication service type and the service level. When receiving a request to activate the power communication service, parse the received power communication service type according to the service level agreement, automatically query and match the service level corresponding to the power communication service type, and obtain the performance indicator; map the performance indicator to each communication exchange node and data transmission link of the power communication resource topology diagram, and construct a logical judgment expression based on the corresponding attribute information; cross-combine multiple logical judgment expressions to obtain routing constraints.

[0009] Preferably, the specific implementation process of performing dynamic weighted calculation on each candidate communication path that meets the routing constraint condition to obtain the comprehensive performance index includes: According to the emphasis of the power communication service type on the performance indicator, the weight coefficient corresponding to the service type is pre-quantified and stored; when a request for activation of the power communication service is received, the corresponding service type is automatically identified and the weight coefficient matching the service type is retrieved; For a single candidate communication path, the raw data of each performance indicator thereof is mapped into a dimensionless numerical range and normalized to obtain normalized performance indicator data of the path; each normalized performance indicator of the candidate communication path is multiplied by a weight coefficient determined by the service type to obtain a weighted score for each performance indicator; The weighted scores of the various performance indicators are accumulated and summed to obtain the comprehensive performance indicator of the candidate communication path under the current service type.

[0010] Preferably, the specific implementation process of outputting the optimal communication path by evaluating the comprehensive performance indicators of each candidate communication path includes: Taking all candidate communication paths and their corresponding comprehensive performance indicators as a set, comparing the numerical values ​​of all comprehensive performance indicators in the set, and sorting the corresponding candidate communication paths in descending order according to the comparison results; The candidate communication path that ranks first after sorting is determined and output as the optimal communication path.

[0011] Preferably, the specific implementation process of automatically converting the optimal communication path into a topology configuration instruction that can guide network devices to perform data deployment and dynamically optimizing the power communication resource topology includes: Preset different command syntax templates according to the power communication equipment model and operating system; Traversing each communication switching node and data transmission link included in the optimal communication path, and extracting attribute information of each communication switching node and data transmission link in turn; Retrieving an instruction syntax template corresponding to the device model and operating system of the communication switching node, inputting the attribute information as a parameter into the retrieved instruction syntax template, and generating a topology configuration instruction; The topology configuration instructions are sent to the power communication equipment through the network management protocol to execute data deployment, and the attribute information of the nodes and data transmission links in the graph database is updated to dynamically optimize the power communication resource topology.

[0012] The power communication resource topology optimization system based on graph database includes: The routing topology constraint construction module uses a graph database to construct a power communication resource topology map containing communication exchange nodes, data transmission links, and attribute information. Based on the performance indicators preset in the built-in service level agreement, it automatically parses the received business types and quantifies them into routing constraints. A service path calculation and selection module performs dynamic weighted calculation on each candidate communication path that meets the routing constraints to obtain a comprehensive performance index; and outputs an optimal communication path by evaluating the comprehensive performance index of each candidate communication path; The configuration instruction dynamic optimization module automatically converts the optimal communication path into a topology configuration instruction that can guide network devices to perform data deployment, and dynamically optimizes the power communication resource topology.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention improves the inefficiency, error-proneness and inaccuracy problems caused by the traditional network's reliance on manual interpretation of business requirements and manual configuration of routing strategies through a built-in business service level agreement. After receiving a service activation request, the system does not wait for manual intervention, but automatically maps and quantifies these high-level business intentions into a set of precise technical indicators such as latency, bandwidth and reliability based on the preset business service level agreement. This method directly translates the abstract "business language" into the "technical language" that the algorithm can execute, thereby providing standardized input for subsequent path optimization. It realizes the automated connection between business requirements and network resource optimization, and improves the response speed and accuracy of the power communication resource network to business needs.

[0014] 2. This invention addresses the shortcomings of traditional routing algorithms, which fail to meet the diverse quality of service requirements of different services and only optimize for a single metric, such as minimum cost, by constructing dynamic, weighted routing constraints tailored to service types. This invention presets different weight coefficients for core performance metrics (such as latency, bandwidth, and reliability) for different service types. During path calculation, the normalized performance data of each candidate communication path is dynamically weighted and summed, and the optimal communication path is selected based on the overall performance metrics. This ensures that the output path is the "comprehensive optimal solution" that is most beneficial to a specific service across multiple dimensions, rather than a "local optimal solution" based on a single dimension, thus achieving adaptive communication path planning for quality of service.

[0015] 3. This invention improves the disconnect between optimization results and actual network deployment by implementing automated conversion technology from optimal paths to deployable configuration instructions. After calculating the optimal communication path, the system traverses all nodes and links along the path, retrieves the corresponding template from a preset instruction syntax template library based on the device model and operating system, and automatically generates topology configuration instructions that can be directly recognized and executed by network devices. This creates an end-to-end automated closed loop from service provisioning to topology optimization, effectively enhancing the automated operation and maintenance capabilities of the power communication resource network. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of the method for optimizing the topology of power communication resources based on a graph database proposed in the present invention; Figure 2 This is a structural diagram of the power communication resource topology optimization system based on graph database proposed in the present invention; Figure 3 This is a schematic diagram of the power communication resource routing planning based on the service level agreement proposed in the present invention application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be described in detail below with reference to the accompanying drawings and in combination with specific embodiments. It must be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to constitute any form of limitation on the scope of protection of the present invention. Therefore, all equivalent changes or modifications conceived by ordinary technicians in this field based on the content disclosed by the present invention without paying creative work should fall within the scope of protection requested by the present invention.

[0018] Reference Figures 1 to 3 The present invention provides a method and system for optimizing the topology of power communication resources based on a graph database. The technical solution is as follows:

[0019] Example 1 Reference Figure 1 This embodiment proposes a method for optimizing power communication resource topology based on a graph database, including: A graph database is used to construct a topological map of power communication resources, including information on communication exchange nodes, data transmission links, and attributes. The received service types are automatically parsed and quantified into routing constraints based on the performance indicators preset in the built-in service level agreement. Performing dynamic weighted calculation on each candidate communication path that meets the routing constraint condition to obtain a comprehensive performance index; outputting an optimal communication path by evaluating the comprehensive performance index of each candidate communication path; The optimal communication path is automatically converted into a topology configuration instruction that can guide network devices to perform data deployment, and the power communication resource topology is dynamically optimized.

[0020] Furthermore, the specific implementation process of constructing a power communication resource topology map including communication exchange nodes, data transmission links and attribute information through a graph database includes: Establishing communication exchange nodes based on the power communication devices used in the power communication resource network; establishing data transmission links connecting the communication exchange nodes based on the connection relationships between the power communication devices; Configuring attribute information for the communication exchange node and the data transmission link according to the device information of the power communication device, wherein the attribute information includes device type, geographical location, link bandwidth, transmission delay, and reliability; Based on the communication exchange nodes, data transmission links and attribute information, a power communication resource topology diagram including physical connections and logical relationships between power communication devices is constructed.

[0021] Graph database technology is used to construct a topological map of power communication resources that comprehensively reflects the current state of the network. Every physical device deployed in the power communication network, such as a running router A or a transmission network device B deployed at a main network communication hub, is abstracted and instantiated as an independent "communication exchange node" in the graph database.

[0022] To accurately represent communication switching nodes, detailed attribute information must be configured. For example, for example, router A, its attribute information can be configured as follows: the device type is recorded as "core router," its geographic location can be precisely marked using GPS coordinates, and static information such as its management IP address, device model, and firmware version can be recorded. Real-time performance data such as its current CPU load and memory usage can also be dynamically linked.

[0023] Subsequently, based on the established communication exchange nodes, data transmission links are constructed according to the actual physical connection relationships between devices. For example, router A is physically connected to transmission network device B at the main network communication hub via a G.652.D single-mode optical fiber. This physical connection is abstracted in the graph database as a "data transmission link" connecting two corresponding nodes, or an "edge" in the graph database. Similar to nodes, this link is also assigned a series of key quantitative attributes to describe its transmission characteristics. Specifically, the bandwidth attribute of the link can be configured as "10Gbps" based on its port rate; its transmission delay attribute is precisely calculated and assigned a value of "1.5 milliseconds" by comprehensively considering the physical length of the optical fiber, the propagation speed of the optical signal, and the processing and forwarding time of the devices at both ends; and its reliability attribute can be evaluated and quantified into a specific value, such as "99.999%", based on the link's historical operating data, with the average failure-free operation time over the past year.

[0024] This embodiment forms a complete network topology within a graph database by performing node and link abstraction and attribute configuration for all devices and physical connections in the power communication resource network. This network topology not only clearly displays the physical connection relationships between network devices in the form of nodes and edges, but also intuitively reflects the network's logical relationships and real-time dynamic resources, providing a solid and detailed data foundation for subsequent resource queries and intelligent topology optimization.

[0025] Furthermore, the specific implementation process of automatically parsing and quantifying the received service type into routing constraints based on the performance indicators preset in the built-in service level agreement includes: Preset service levels based on the criticality and communication requirements of the power communication service type, and set performance indicators for each service level; the performance indicators include bandwidth requirements, latency limits, and reliability; Establish a correspondence between the power communication service type and the service level. When receiving a request to activate the power communication service, parse the received power communication service type according to the service level agreement, automatically query and match the service level corresponding to the power communication service type, and obtain the performance indicator; map the performance indicator to each communication exchange node and data transmission link of the power communication resource topology diagram, and construct a logical judgment expression based on the corresponding attribute information; cross-combine multiple logical judgment expressions to obtain routing constraints.

[0026] Multiple tiers of service levels are pre-defined based on the criticality of power communications services to grid operations and their specific communication requirements. Each tier is assigned a set of clear performance thresholds. For example, the system can have three pre-defined service levels: Level 1 corresponds to millisecond-level hard real-time services, such as "relay protection," with strict performance requirements: a minimum bandwidth of at least 10 Mbps, a transmission latency limit of 2 milliseconds, and a path reliability requirement exceeding 99.9999%. Level 2 corresponds to near-real-time control services, such as "data collection," with performance requirements of greater than 2 Mbps, a latency limit of 20 milliseconds, and a reliability requirement of at least 99.999%. Level 3 corresponds to non-real-time management information services, such as "office automation system access," with less stringent latency and reliability requirements, such as a 200 millisecond latency limit and a reliability requirement exceeding 99.999%.

[0027] The specific implementation process of the quantified routing constraint condition includes: Establish a correspondence table between power communication business types and preset business service levels; When a data collection service activation request is received, the service type identifier "data collection" carried in the request is automatically parsed according to the built-in service level agreement; by querying the corresponding relationship table, the service type is matched to the service level "second level", and a specific performance indicator set including bandwidth greater than 2Mbps, latency limit of 20 milliseconds, and reliability of not less than 99.999% is automatically obtained; The obtained performance indicators are mapped one by one onto the constructed power communication resource topology map and converted into logical judgment expressions for the node and link attributes in the map; the delay upper limit requires that the sum of the "transmission delay" attribute values ​​of all data transmission links on the candidate communication path and the sum of the "processing delay" attribute values ​​of all communication exchange nodes on the path must be less than 20; the reliability requirement requires that the product of the "reliability" attribute values ​​of all links and nodes on the path must be greater than or equal to 0.99999; the bandwidth requirement stipulates that the bandwidth bottleneck of all nodes on the path must be greater than 2Mbps; All logical judgment expressions generated for a single performance indicator are combined into a set containing multiple "and" logical conditions to form a complete constraint on the candidate path.

[0028] These logical judgment expressions will be applied as core filtering conditions in the query process of the graph database, ensuring that only those communication paths that strictly meet the "second-level" service level requirements of the data collection business in all dimensions such as bandwidth, latency, and reliability will be considered valid candidate communication paths, thereby completing the precise and automated conversion of business intentions into specific routing constraints.

[0029] This embodiment improves the ambiguity and inconsistency brought about by the traditional network's reliance on manual interpretation of business requirements through a standardized service level agreement, realizes the automated analysis and precise quantification of business intent, provides an executable constraint basis for implementing service quality-oriented adaptive path planning, and effectively improves the accuracy of network resource allocation and the level of automation of business response.

[0030] Furthermore, a specific implementation process of performing dynamic weighted calculation on each candidate communication path that meets the routing constraint condition to obtain a comprehensive performance index includes: According to the emphasis of the power communication service type on the performance indicator, the weight coefficient corresponding to the service type is pre-quantified and stored; when a request for activation of the power communication service is received, the corresponding service type is automatically identified and the weight coefficient matching the service type is retrieved; For a single candidate communication path, the raw data of each performance indicator thereof is mapped into a dimensionless numerical range and normalized to obtain normalized performance indicator data of the path; each normalized performance indicator of the candidate communication path is multiplied by a weight coefficient determined by the service type to obtain a weighted score for each performance indicator; The weighted scores of the various performance indicators are accumulated and summed to obtain the comprehensive performance indicator of the candidate communication path under the current service type.

[0031] Based on the inherent properties of different power communication services, the emphasis on various performance indicators is pre-quantified and a set of weight coefficients is formed for storage and record. For example, for the "relay protection" service type, which has strict requirements on delay and reliability, its weight coefficients can be pre-set as follows: delay weight is assigned to 0.5, reliability weight is assigned to 0.4, and bandwidth weight is only assigned to 0.1. For the "data acquisition" service, where the primary requirement is large bandwidth, its weight coefficients can be set as follows: bandwidth weight is assigned to 0.5, delay weight is assigned to 0.3, and reliability weight is assigned to 0.2. When a relay protection service is received, the service type is automatically identified and the matching weight coefficient set is retrieved from the stored records, namely delay 0.5, reliability 0.4, and bandwidth 0.1, to prepare for subsequent calculations.

[0032] The specific implementation process of calculating the comprehensive performance index includes: There are two candidate communication paths that meet the basic constraints of the relay protection service: path X and path Y. Path X has a total latency of 1 millisecond, end-to-end reliability of 99.99998%, and an available bandwidth of 50 Mbps. Path Y has a total latency of 1.5 milliseconds, a reliability of 99.99991%, and an available bandwidth of 200 Mbps. The original performance indicators are mapped to a unified dimensionless numerical range (between 0 and 1) and normalized. For negative indicators such as latency (smaller values ​​are better), the path with the lowest latency is assigned a score of 1.0, while the path with the highest latency is assigned a score of 0.0. For positive indicators such as bandwidth and reliability (larger values ​​are better), the path with the best performance is assigned a score of 1.0. After normalization, the normalized performance indicator data of each candidate communication path is multiplied by the weight coefficient determined by the service type to obtain the weighted score of each performance indicator. The weighted scores of various performance indicators under a single path are accumulated and summed to obtain the comprehensive performance indicator of the candidate communication path under the current service type.

[0033] Through normalization, the performance indicators of latency, reliability, and bandwidth are mapped to a unified dimensionless scoring range, resulting in a comprehensive performance score that fully reflects the path-service match. This transforms complex network optimization decisions from fuzzy judgments based on subjective experience to precise, quantifiable mathematical principles. Path evaluation is no longer limited to a single optimal metric, but can now intelligently balance multiple performance dimensions such as latency, bandwidth, and reliability based on actual service needs.

[0034] For path X, the normalized scores for delay, reliability, and bandwidth are 1.0, 1.0, and 0.0, respectively. Multiplying these scores by the weight coefficients for the relay protection service (0.5, 0.4, and 0.1) yields a weighted score of 0.5 for delay, 0.4 for reliability, and 0.0 for bandwidth. For path Y, the normalized scores are 0.0, 0.0, and 1.0, respectively. Multiplying these scores by the same weights yields a weighted score of 0.0 for delay, 0.0 for reliability, and 0.1 for bandwidth.

[0035] For path X, its comprehensive performance index is the sum of the weighted scores of each item, 0.9. For path Y, its comprehensive performance index is 0.1. By comparing these two comprehensive performance indicators, it is clear that although path B has a significant bandwidth advantage, path A is a far superior choice for relay protection services with stricter latency and reliability requirements.

[0036] This embodiment improves the traditional routing algorithm's difficulty in making decisions when faced with multi-dimensional optimization objectives by introducing dynamic weight coefficients tied to service types. This allows it to calculate a comprehensive utility value that fully reflects the path-service match. This ensures the rational allocation of network resources and effectively implements adaptive communication path planning for quality of service.

[0037] Furthermore, by evaluating the comprehensive performance indicators of each candidate communication path, the specific implementation process of outputting the optimal communication path includes: Taking all candidate communication paths and their corresponding comprehensive performance indicators as a set, comparing the numerical values ​​of all comprehensive performance indicators in the set, and sorting the corresponding candidate communication paths in descending order according to the comparison results; The candidate communication path that ranks first after sorting is determined and output as the optimal communication path.

[0038] The optimal communication path for the "office automation system access" service needs to be selected from multiple candidate communication paths. The weighted calculation above yields three candidate communication paths and their corresponding comprehensive performance indicators. Specifically, candidate communication path A has a comprehensive performance indicator of 0.92; candidate communication path B has a comprehensive performance indicator of 0.88; and candidate communication path C has a comprehensive performance indicator of 0.95. These three candidate communication paths and their associated comprehensive performance indicators are combined into a processing set, which can be represented in a data structure as (path A, 0.92), (path B, 0.88), and (path C, 0.95).

[0039] Next, a direct mathematical comparison is performed on the numerical values ​​of all comprehensive performance indicators in the set. Specifically, the three floating-point numbers 0.92, 0.88, and 0.95 are compared. Based on this comparison, the candidate communication paths in the set are sorted in descending order. Since 0.95 is greater than 0.92, which in turn is greater than 0.88, the sorted list becomes (Path C, Path A, Path B).

[0040] After the sorting is complete, the program logic automatically determines and selects the candidate communication path that ranks first in the descending sorted list and outputs it as the final calculation result. The top candidate is communication path C, so path C is officially output as the optimal communication path for carrying the "Office Automation System Access" service. This output result is directly submitted to the subsequent configuration instruction generation module to complete the actual allocation of network resources.

[0041] This embodiment reduces the ambiguity in selecting between multiple candidate communication paths by converging multi-dimensional performance evaluation results into a single comprehensive metric and using this as the basis for ranking. This makes the entire path optimization process deterministic and repeatable, avoiding the errors and inefficiencies that may be introduced by manual judgment.

[0042] Furthermore, the specific implementation process of automatically converting the optimal communication path into a topology configuration instruction that can guide network devices to perform data deployment and dynamically optimizing the power communication resource topology includes: Preset different command syntax templates according to the power communication equipment model and operating system; Traversing each communication switching node and data transmission link included in the optimal communication path, and extracting attribute information of each communication switching node and data transmission link in turn; Retrieving an instruction syntax template corresponding to the device model and operating system of the communication switching node, inputting the attribute information as a parameter into the retrieved instruction syntax template, and generating a topology configuration instruction; The topology configuration instructions are sent to the power communication equipment through the network management protocol to execute data deployment, and the attribute information of the nodes and data transmission links in the graph database is updated to dynamically optimize the power communication resource topology.

[0043] A pre-built and maintained library of command syntax templates provides standardized configuration command formats for common device models and their operating systems in power communication networks. For example, for switches running the Cisco IOS operating system, the system has pre-built templates for creating VLANs and applying them to specific interfaces. For routers running the VRP operating system, a corresponding set of templates with different syntax structures is pre-built. These templates contain information such as interface names and VLAN IDs.

[0044] The specific implementation process of the conversion topology configuration instruction includes: After determining the optimal communication path, traverse each communication switching node and data transmission link included in the path; the optimal path must pass through a Cisco Catalyst 3850 switch deployed in computer room M and connected to computer room N through its Gigabit Ethernet 1 / 0 / 5 port; when traversing this Cisco switch node, immediately extract its attribute information, including the device model "Cisco Catalyst 3850", the operating system "IOS-XE", the interface to be configured is Gigabit Ethernet 1 / 0 / 5, and the VLAN ID "120" required by the service; According to the extracted device model and operating system information, the corresponding instruction template is accurately retrieved from the instruction syntax template library, and the extracted attribute information is filled into the corresponding placeholder of the template as a parameter to generate a topology configuration instruction that can be directly executed on the device.

[0045] This process eliminates the tedious steps of manually logging into each device and entering configuration commands one by one. For paths involving multiple network nodes, this effectively shortens configuration time and improves data deployment efficiency. The pre-set command syntax template library ensures standardized configuration across all devices in environments with multiple brands and models, greatly facilitating subsequent business processing.

[0046] This generated topology configuration command is automatically distributed to the target Cisco switch in computer room M via standard network management protocols for data deployment. After successfully executing the command, the device returns a confirmation message. Upon receiving the confirmation, the graph database is immediately synchronized and updated. For example, on the "edge" object representing the link between computer rooms M and N, its "Used Bandwidth" attribute is increased by 2 Mbps to meet the data collection service requirements, and a new "Bearer Service ID" attribute is added.

[0047] This embodiment improves the inefficiency and error-proneness inherent in traditional operations and maintenance processes, resulting from manual translation and configuration, through seamless, automated integration from optimization decision-making to network execution. By utilizing templated and automated command delivery, it shortens service provisioning and network adjustment cycles, ensures configuration standardization and accuracy, and effectively enhances the automated management capabilities of the power communication resource network.

[0048] The graph database-based power communication resource topology optimization method proposed in this embodiment constructs a power communication resource topology graph and combines it with the business service level agreement to accurately quantify abstract business requirements into computable routing constraints. This improves the inefficiency of traditional power communication networks caused by inaccurate topology information and manual interpretation of business requirements, and effectively enhances the ability to automatically and accurately perceive business intent.

[0049] A dynamic, weighted path calculation method based on service type intelligently balances and comprehensively evaluates performance metrics such as latency, bandwidth, and reliability based on the differentiated emphasis of different services (such as relay protection and data acquisition). This overcomes the limitation of traditional routing algorithms, which can only optimize based on a single metric, and enables adaptive communication path planning for quality of service.

[0050] Example 2 This embodiment provides a power communication resource topology optimization system based on a graph database and applied to a power communication network. Figure 2 ,The system includes a routing topology constraint building module, a ,service path calculation and selection module, and a ,configuration instruction dynamic optimization module.

[0051] The routing topology constraint construction module uses a graph database to construct a power communication resource topology map containing communication exchange nodes, data transmission links, and attribute information. Based on the performance indicators preset in the built-in service level agreement, it automatically parses the received business types and quantifies them into routing constraints. A service path calculation and selection module performs dynamic weighted calculation on each candidate communication path that meets the routing constraints to obtain a comprehensive performance index; and outputs an optimal communication path by evaluating the comprehensive performance index of each candidate communication path; The configuration instruction dynamic optimization module automatically converts the optimal communication path into a topology configuration instruction that can guide network devices to perform data deployment, and dynamically optimizes the power communication resource topology.

[0052] Furthermore, the routing topology constraint construction module constructs a graph database for each communication device and the connection relationships between devices within the power communication network. Each key network unit within the network, such as routers and connecting optical fibers, is modeled as a "communication exchange node" and "data transmission link" in the graph database. Each modeled unit has detailed attributes, such as device model, geographic location, link bandwidth of 100Gbps, transmission latency of 0.5 milliseconds, and reliability of 99.999%. The core function of this module is to convert high-level business requirements into machine-readable constraints based on preset business service level agreements. When a new service activation request, such as "data collection," is received, the system automatically parses its service type, matches it to the preset business service level, and quantifies its performance indicators (such as a latency limit of 50 milliseconds) into a set of precise logical judgment expressions, which serve as hard filtering conditions for subsequent path calculations.

[0053] Furthermore, after the routing topology constraint construction module has screened multiple candidate communication paths, the service path calculation and selection module performs a quantitative evaluation of each candidate communication path to select the optimal solution. First, based on the service type, for example, "relay protection," it retrieves a preset weighting factor. This factor assigns higher weights to key indicators such as latency and reliability, such as a latency weight of 0.6. The module then normalizes each candidate communication path's performance metrics (e.g., 2 milliseconds latency, 99.9999% reliability), multiplies them by the weighting factor, and sums the results. This results in a single "comprehensive performance index" for each candidate communication path. Finally, the module sorts all candidate communication paths in descending order by their comprehensive performance index and automatically selects the top-ranked path, such as path U with a comprehensive index of 0.91, as the final optimal communication path output.

[0054] Furthermore, the routing topology constraint construction module is responsible for automatically converting the logical path into configuration instructions that can be executed by network devices after the optimal communication path is determined. The module has preset instruction syntax templates for different device models and operating systems, such as Cisco IOS QoS policy templates, VRP routing configuration templates, etc. When deployment begins, the module traverses each network node on the optimal path, such as a Cisco Catalyst 9300 switch, and calls the corresponding template according to its device model. Then, it fills in the specific parameters required for the business, such as interface name Gigabit Ethernet 1 / 1 / 1, VLAN ID: 120, etc., into the template to generate a complete configuration instruction. Finally, the instruction is automatically sent to the target device for execution through network management protocols such as NETCONF. After successful execution, the system will synchronously update the resource occupancy information in the graph database, thereby completing a closed-loop dynamic optimization from decision-making to deployment to state synchronization.

[0055] Example 3 This embodiment deploys the above-mentioned graph database-based power communication resource topology optimization method and system in the power communication network of P enterprise. Figure 3 , to achieve topology optimization of power communication resources.

[0056] The system constructs a comprehensive graph database of the physical devices and inter-device connections in Enterprise P's power communication network. For example, an H3CS5820V2 series switch deployed in the central computer room and an NE40E router deployed in the conference room are each instantiated as an independent communication exchange node in the graph database. The system also configures detailed attribute information for each node. For example, the node attributes of the "H3C switch in the central computer room" are configured as follows: Device ID: SCS-SW-01, Device Model: H3CS5820V2, Operating System: Comware V7, Management IP: 10.1.2.5, CPU Utilization: 15%, Memory Utilization: 22%. Data transmission links are constructed based on inter-device connections. For example, the central computer room and the conference room are physically connected via a G.652.D single-mode optical fiber. This connection is abstracted in the graph database as an "edge" connecting the two corresponding nodes. The properties of the link are set as follows: Link ID: LNK-CNS-01, Link type: Fiber, Bandwidth capacity: 10 Gbps, Available bandwidth: 8.2 Gbps, Transmission delay: 1.5 milliseconds, Reliability: 99.999%.

[0057] The system has a built-in business service level agreement in the form of structured data (such as database tables). The specific example is as follows: The first level corresponds to millisecond-level real-time services, such as relay protection. Its performance indicators are set as follows: minimum bandwidth of no less than 10 Mbps, upper limit of transmission delay of 2 milliseconds, and comprehensive path reliability requirement greater than 99.9999%. Delay weighting is 0.5, reliability weighting is 0.4, and bandwidth weighting is 0.1. The second level corresponds to quasi-real-time control services, such as data acquisition. Its performance indicators can be set as follows: bandwidth requirement greater than 2 Mbps, upper limit of delay of 20 milliseconds, and reliability of no less than 99.999%. Delay weighting is 0.3, reliability weighting is 0.2, and bandwidth weighting is 0.5. The third level corresponds to non-real-time management information services, such as office automation systems. Its latency and reliability requirements are relatively relaxed, with an upper limit of delay of 200 milliseconds and reliability greater than 99.9%. Delay weighting is 0.2, reliability weighting is 0.4, and bandwidth weighting is 0.4.

[0058] When the system receives a request to activate a data collection service for a central computer room, it automatically performs the following actions: It identifies the service type as data collection. It automatically queries the service's service level agreement, identifies it as Level 2, and obtains its performance requirements: bandwidth must be greater than 2 Mbps, latency must be less than 20 milliseconds, and reliability must be greater than 99.999%. It then converts these performance requirements into structured logical conditions for selecting candidate paths in the graph database. It then generates clauses in a graph database query language (such as Cypher) that specify: the available bandwidth of all links along the path must be greater than 2 Mbps, the sum of the path's total transmission latency and node processing latency must be less than 20 milliseconds, and the reliability of all nodes and links along the path must be greater than 0.99999.

[0059] The graph database is queried for all candidate communication paths from the source node to the central computer room that meet all the above conditions, and two candidate paths are selected. Path A: Passing through two intermediate nodes, with a total latency of 18 milliseconds, a path bandwidth of 50 Mbps, and an overall reliability of 99.9998%. Path B: Passing through three intermediate nodes, with a total latency of 15 milliseconds, a path bandwidth of 120 Mbps, and an overall reliability of 99.9996%. The system maps the raw data of each performance indicator to a unified dimensionless numerical range (0 to 1). For latency (a negative indicator, lower values ​​are preferred), the system assigns the highest score of 1.0 to the minimum value (15 milliseconds) among the candidate paths, and the lowest score to the maximum value (18 milliseconds). Using linear mapping, the normalized latency score for Path A is 0.0, and the score for Path B is 1.0. For bandwidth (a positive indicator, higher values ​​are preferred), the system assigns the highest score of 1.0 to the maximum value (120 Mbps), and the lowest score of 0.0 to the minimum value (50 Mbps). The bandwidth normalized score for path B is 1.0, and the score for path A is 0.0. For reliability (a positive indicator), path A has a score of 1.0 and path B has a score of 0.0.

[0060] The weight coefficients for the data collection service are retrieved from the service level agreement: latency weight 0.3, reliability weight 0.2, and bandwidth weight 0.5. The comprehensive performance index for path A is calculated by multiplying each normalized score of path A by its corresponding weight coefficient and summing the results. The calculation process is: (latency score 0.0 multiplied by weight 0.3) plus (reliability score 1.0 multiplied by weight 0.2) plus (bandwidth score 0.0 multiplied by weight 0.5). The final comprehensive performance index for path A is 0.2. The comprehensive performance index for path B is calculated as: (latency score 1.0 multiplied by weight 0.3) plus (reliability score 0.0 multiplied by weight 0.2) plus (bandwidth score 1.0 multiplied by weight 0.5). The final comprehensive performance index for path B is 0.8. By comparison, path B's comprehensive performance index (0.8) is much higher than path A's (0.2), so path B is determined to be the optimal communication path for carrying this data collection service.

[0061] The system traverses each node along optimal path B. When it reaches the "Central Computer Room H3C Switch" node, it extracts the device model (H3CS5820V2) and operating system (Comware V7) from its attributes. The system then retrieves the VLAN configuration template corresponding to this model and system from a pre-set command syntax template library. Specific service parameters, such as the VLAN ID assigned to this data collection service (101) and the port on the switch (Gigabit Ethernet 1 / 0 / 23) traversed by path B, are added as variables to the template's placeholders. This ultimately generates a complete, executable topology configuration command. Using standard network management protocols (such as NETCONF), the generated configuration command is sent to the "Central Computer Room H3C Switch" to activate the power communication service. Upon successful service activation, the system receives a confirmation message. Finally, the system automatically updates the attributes of the links and nodes involved in path B in the graph database, for example, reducing the available bandwidth of LNK-CNS-01 by 5 Mbps.

[0062] This embodiment not only improves the inefficiencies and configuration errors caused by manual operations, but also utilizes a service-oriented dynamic weighted evaluation mechanism to address the limitations of traditional routing algorithms, which struggle to intelligently balance multiple performance dimensions. This automated closed-loop approach to route selection and topology execution effectively improves the utilization efficiency of power communication resources.

[0063] It should be understood that the embodiments described above are merely illustrative and are intended to facilitate understanding of the present invention, rather than to limit the present invention. Those skilled in the art may make various changes and improvements upon understanding the core concepts of the present invention. Therefore, the scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing power communication resource topology based on a graph database, characterized in that: include: Construct a power communication resource topology map containing communication exchange nodes, data transmission links, and attribute information through a graph database; Automatically parse and quantify received service types into routing constraints based on the performance indicators preset in the built-in service level agreement. Performing dynamic weighted calculation on each candidate communication path that meets the routing constraint condition to obtain a comprehensive performance index; outputting an optimal communication path by evaluating the comprehensive performance index of each candidate communication path; The optimal communication path is automatically converted into a topology configuration instruction that can guide network devices to perform data deployment, and the power communication resource topology is dynamically optimized.

2. The method for optimizing power communication resource topology based on graph database according to claim 1, characterized in that: The specific implementation process of constructing a power communication resource topology map containing communication exchange nodes, data transmission links and attribute information through a graph database includes: Establishing communication exchange nodes based on the power communication devices used in the power communication resource network; establishing data transmission links connecting the communication exchange nodes based on the connection relationships between the power communication devices; Configuring attribute information for the communication exchange node and the data transmission link based on the device information of the power communication device, wherein the attribute information includes device type, geographical location, link bandwidth, transmission delay, and reliability; Based on the communication exchange nodes, data transmission links and attribute information, a power communication resource topology diagram including physical connections and logical relationships between power communication devices is constructed.

3. The method for optimizing power communication resource topology based on graph database according to claim 1, characterized in that: The specific implementation process of automatically parsing and quantifying the received service type into routing constraints based on the performance indicators preset in the built-in service level agreement includes: Preset service levels based on the criticality and communication requirements of the power communication service type, and set performance indicators for each service level; the performance indicators include bandwidth requirements, latency limits, and reliability; Establish a correspondence between the power communication service type and the service level. When receiving a request to activate the power communication service, parse the received power communication service type according to the service level agreement, automatically query and match the service level corresponding to the power communication service type, and obtain the performance indicator; map the performance indicator to each communication exchange node and data transmission link of the power communication resource topology diagram, and construct a logical judgment expression based on the corresponding attribute information; cross-combine multiple logical judgment expressions to obtain routing constraints.

4. The method for optimizing power communication resource topology based on graph database according to claim 1, characterized in that: The specific implementation process of performing dynamic weighted calculation on each candidate communication path that meets the routing constraints to obtain a comprehensive performance index includes: According to the emphasis of the power communication service type on the performance indicator, the weight coefficient corresponding to the service type is pre-quantified and stored; when a request for activation of the power communication service is received, the corresponding service type is automatically identified and the weight coefficient matching the service type is retrieved; For a single candidate communication path, the raw data of each performance indicator thereof is mapped into a dimensionless numerical range and normalized to obtain normalized performance indicator data of the path; each normalized performance indicator of the candidate communication path is multiplied by a weight coefficient determined by the service type to obtain a weighted score for each performance indicator; The weighted scores of the various performance indicators are accumulated and summed to obtain the comprehensive performance indicator of the candidate communication path under the current service type.

5. The method for optimizing power communication resource topology based on graph database according to claim 1, characterized in that: The specific implementation process of outputting the optimal communication path by evaluating the comprehensive performance indicators of each candidate communication path includes: Taking all candidate communication paths and their corresponding comprehensive performance indicators as a set, comparing the numerical values ​​of all comprehensive performance indicators in the set, and sorting the corresponding candidate communication paths in descending order according to the comparison results; The candidate communication path that ranks first after sorting is determined and output as the optimal communication path.

6. The method for optimizing power communication resource topology based on graph database according to claim 1, characterized in that: The specific implementation process of automatically converting the optimal communication path into a topology configuration instruction that can guide network devices to perform data deployment and dynamically optimizing the power communication resource topology includes: Preset different command syntax templates according to the power communication equipment model and operating system; Traversing each communication switching node and data transmission link included in the optimal communication path, and extracting attribute information of each communication switching node and data transmission link in turn; Retrieving an instruction syntax template corresponding to the device model and operating system of the communication switching node, inputting the attribute information as a parameter into the retrieved instruction syntax template, and generating a topology configuration instruction; The topology configuration instructions are sent to the power communication equipment through the network management protocol to execute data deployment, and the attribute information of the nodes and data transmission links in the graph database is updated to dynamically optimize the power communication resource topology.

7. The power communication resource topology optimization system based on graph database is characterized by: include: The routing topology constraint construction module uses a graph database to construct a power communication resource topology map containing communication exchange nodes, data transmission links, and attribute information; Automatically parse and quantify received service types into routing constraints based on the performance indicators preset in the built-in service level agreement. A service path calculation and selection module performs dynamic weighted calculation on each candidate communication path that meets the routing constraints to obtain a comprehensive performance index; and outputs an optimal communication path by evaluating the comprehensive performance index of each candidate communication path; The configuration instruction dynamic optimization module automatically converts the optimal communication path into a topology configuration instruction that can guide network devices to perform data deployment, and dynamically optimizes the power communication resource topology.

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