Method and apparatus for deploying optical line terminal, readable storage medium, program product

Abstract

The application discloses a deployment method and device of an optical line terminal, a readable storage medium and a program product, and comprises the following steps: determining a preliminary selection area of an optical line terminal to be deployed based on the service radius of the optical line terminal and a service demand area requiring network service provided by the optical line terminal; determining a candidate area with a user density greater than a preset density threshold in the preliminary selection area based on the positions and quantities of users in the preliminary selection area; evaluating whether the network service provided when the optical line terminal is deployed in the candidate area meets a preset network service standard; and deploying the optical line terminal in a target area in the candidate area that meets the preset network service standard.

Description

Technical Field

[0001] This application relates to the field of optical fiber technology, and in particular to a method and apparatus for deploying an optical line terminal, a readable storage medium, and a program product. Background Technology

[0002] With the rapid development of fiber optic access networks, Fiber to the Home (FTTH) has become the mainstream technology for current optical network construction. As the core equipment of FTTH networks, the rational deployment of the Optical Line Terminal (OLT) has a significant impact on the performance and efficiency of the entire network. How to optimize the deployment location of the OLT has become one of the key technical issues that need to be addressed in optical network construction.

[0003] Traditional OLT deployment methods often rely on empirical analysis and manual judgment, which have certain limitations and can easily lead to uneven resource allocation or excessive waste. Selecting OLT deployment locations solely based on pipeline distribution may not fully meet user needs. Conversely, deploying solely based on cost factors may not guarantee network performance. Therefore, a more scientific and systematic method is needed to optimize OLT deployment locations and achieve more efficient OLT deployment. Summary of the Invention

[0004] The purpose of this application is to provide a deployment method and apparatus for optical line terminals, a readable storage medium, and a program product to solve the problem of low deployment efficiency of existing optical line terminals.

[0005] To solve the above-mentioned technical problems, this specification is implemented as follows: Firstly, a method for deploying an optical line terminal is provided, comprising: Based on the service radius of the optical line terminal and the service demand area that requires the optical line terminal to provide network services, the initial selection area for deploying the optical line terminal is determined. Based on the location and number of users in the initial selection area, candidate areas with user density greater than a preset density threshold are determined. Evaluate whether the network services provided when deploying optical line terminals in candidate areas meet the preset network service standards. The optical line terminal is deployed in the target area of ​​the candidate area that meets the preset network service standard.

[0006] Optionally, determining candidate regions where the user density in the initially selected region is greater than a preset density threshold includes: Based on the location distribution map corresponding to the location of each user in the initial selection area, the initial selection area is divided into multiple grids; Calculate the user density of each grid based on its area and the number of users it contains; The user density corresponding to each grid is mapped to different density levels, and two adjacent grids with the same user density level are merged into one grid; A heat map is generated based on each fused grid and its corresponding density level, and then overlaid onto the map of the initially selected area using geographic information system software to obtain a heat map. The heat map uses different colors to represent the density level of grids at different locations. Based on the heat map, grids with a density level greater than a preset density level are selected and identified as candidate regions.

[0007] Optionally, based on the service radius of the optical line terminal and the service demand area requiring the network service of the optical line terminal, a preliminary selection area for the deployment of the optical line terminal is determined, including: Geographic Information System (GIS) software is used to map and mark the service demand areas; Using any point in the service demand area as the center and the maximum service radius of the optical line terminal as the radius, draw a circle to obtain the corresponding circle to simulate multiple coverage areas of the optical line terminal. The intersection of all the circular areas whose coverage completely covers the service demand area is determined as the initial selection area for the deployment of optical line terminals.

[0008] Optionally, after obtaining the heatmap, the process may also include: Obtain user density data and the multiple density levels defined in the heatmap; Statistical analysis is performed on each density level based on the user density data to determine the data variation of each density level. The statistical analysis includes calculating the average user density, user density standard deviation, minimum user density, and maximum user density for each density level. Normalize the user density data in the density level where the data variation is greater than the preset edge threshold; Based on the user density data of the normalized density levels, multiple density levels are clustered using a preset clustering algorithm to obtain the clustered density levels and the corresponding range of user density data. The step of selecting grids with a density level greater than a preset density level based on the heat map and determining them as candidate regions includes: selecting grids with a density level greater than a preset density level after clustering based on the heat map and determining them as candidate regions.

[0009] Optionally, the evaluation assesses whether the network services provided when deploying optical line terminals in candidate areas meet preset network service standards, including: The center of the candidate area is used as the location for deploying optical line terminals; The network architecture for deploying optical line terminals at the specified locations is simulated using a preset network simulation tool, and the simulated network parameters for the optical line terminals are set. Based on the network architecture and the simulated network parameters, the network services provided when the optical line terminal is deployed at the location are evaluated to ensure that they meet the preset network service standards, including broadband performance and quality of service.

[0010] Optionally, the candidate regions include multiple regions, and before evaluating whether the network service provided by the deployment of optical line terminals in the candidate regions meets the preset network service standards, the following further steps are taken: Determine the standardized values ​​of the evaluation indicators for each candidate region, wherein the evaluation indicators include at least one of the following: total user demand, pipeline coverage, and population growth rate. Sort the candidate regions in descending order according to the standardized values, and select a predetermined number of candidate regions that rank first from each candidate region for the evaluation. The total user demand is related to the statistical population and average user density of each candidate region.

[0011] Optionally, the evaluation indicators include population growth rate, and the standardized values ​​of the evaluation indicators for each candidate region are determined, including: Obtain current and historical population data for the target candidate region; The fluctuations in the historical population data are analyzed to determine whether the fluctuation trend of the historical population data is stationary or non-stationary. If the fluctuation is stationary, a linear regression model is used to predict the future population of the target candidate region; If the fluctuation is non-stationary, a pre-trained time series prediction model is used to predict the future population of the target candidate region; Based on the current and future population, a standardized value for the population growth rate of the target candidate region is determined.

[0012] In a second aspect, an optical line terminal deployment apparatus is provided, comprising a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method described in the first aspect.

[0013] Thirdly, a readable storage medium is provided that stores a program or instructions which, when executed by a processor, implement the steps of the method described in the first aspect.

[0014] Fourthly, a computer program product is provided, comprising a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform the steps of the method described in the first aspect.

[0015] In this embodiment, a preliminary area for deploying an optical line terminal (OLT) is determined based on the service radius of the OLT and the service demand area requiring network services from the OLT. Based on the location and number of users within the preliminary area, a candidate area with a user density exceeding a preset density threshold is determined. The network services provided by deploying the OLT in the candidate area are evaluated to ensure they meet preset network service standards. The OLT is then deployed in a target area within the candidate area that meets the preset network service standards. This fully utilizes key information about user distribution and, combined with network service standards, selects a suitable OLT deployment location, achieving scientific management and optimized decision-making for OLT deployment. This improves network coverage and resource utilization efficiency, increases user satisfaction, reduces operating costs and risks, and adapts to the needs of modern network services. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating the deployment method of an optical line terminal according to an embodiment of this application.

[0017] Figure 2 This is a schematic diagram of the overall process of deploying an optical line terminal according to an embodiment of this application.

[0018] Figure 3 This is a structural block diagram of the deployment device for an optical line terminal according to an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. The drawing numbers in this application are only used to distinguish the various steps in the solution and are not used to limit the execution order of the various steps. The specific execution order is subject to the description in the specification.

[0020] To address the problems existing in the prior art, embodiments of this application provide a method for deploying an optical line terminal, such as... Figure 1 As shown, the process includes steps 102 to 106.

[0021] Step 102: Based on the service radius of the optical line terminal and the service demand area that requires the optical line terminal to provide network services, determine the initial selection area for the deployment of the optical line terminal.

[0022] The service radius of an optical line terminal (OLT) is related to the terminal type and is a known parameter. The size of the service radius determines the area of ​​service coverage that an OLT can provide. A larger service radius allows for a wider service coverage area. The service demand area is the area where an OLT needs to be deployed and network services provided, such as residential communities, office buildings, and commercial areas. In this step, based on the service coverage area corresponding to the OLT's service radius and the service demand area, the area to be initially determined for deployment of the OLT can be identified; this is the initial selection area.

[0023] Based on the solution provided in the above embodiments, optionally, in step 102 above, determining the initial selection area for deploying the optical line terminal based on the service radius of the optical line terminal and the service demand area requiring the network service of the optical line terminal includes: mapping and marking the service demand area on a map using geographic information system software; drawing circles with any point in the service demand area as the center and the maximum service radius of the optical line terminal as the radius to obtain corresponding circles for simulating multiple coverage areas of the optical line terminal; and determining the intersection area of ​​all circles whose coverage areas completely cover the service demand area as the initial selection area for deploying the optical line terminal.

[0024] Specifically, in this step, Geographic Information System (GIS) software is used to map the service demand area onto a map, and the service demand area is marked in the GIS software. Then, using a circle tool, the center of the circle is placed at different points in the service demand area, and the radius of the circle is the maximum service radius of the OLT device, simulating the coverage area of ​​the OLT device. The intersection area of ​​all circles that can completely cover the service demand area is found, and the intersection area is the deployment area of ​​the OLT device.

[0025] In this embodiment of the application, by using GIS software and simulating circular tools, it can be ensured that the selected deployment points of the OLT devices cover all service demand areas, reducing the risk of uncovered areas and ensuring that all users can enjoy the service, thereby improving user satisfaction and service fairness.

[0026] Step 104: Based on the location and number of users in the initial selection area, determine the candidate area in the initial selection area where the user density is greater than a preset density threshold.

[0027] The initial selection area is a relatively large region. To provide better network quality services to most users, candidate areas with user density exceeding a preset density threshold can be further selected from the initial selection area. The range of candidate areas is smaller than the initial selection area, and multiple candidate areas may be selected through the above method.

[0028] Based on the solution provided in the above embodiments, optionally, in step 104, determining candidate areas where the user density in the initial selection area is greater than a preset density threshold includes: dividing the initial selection area into multiple grids based on the location distribution map corresponding to the location of each user in the initial selection area; calculating the user density of each grid based on the area of ​​each grid and the number of users included therein; mapping the user density corresponding to each grid to different density levels, and merging two adjacent grids with the same user density level into one grid; generating a heat map based on the merged grids and their corresponding density levels, and overlaying it onto the map of the initial selection area using geographic information system software to obtain a heat map, wherein the heat map uses different colors to represent the density levels of grids at different locations; and filtering out grids with a density level greater than a preset density level based on the heat map and determining them as candidate areas.

[0029] In this step, user location data is collected in the initially selected area where OLT devices will be deployed, and a location distribution map is generated based on the user location data. The location distribution map is divided into grids, and the user density is calculated based on the area of ​​each grid and the number of users. The calculated user density is mapped to different density levels. Different user densities may be mapped to the same density level, depending on the data range of user density defined for each density level (the boundary of the density level).

[0030] The process iterates through all grids, merging adjacent grids with the same density level into a single grid. A heatmap is then generated based on the grid and its corresponding density level. Finally, GIS software is used to overlay the heatmap onto a map including the initially selected area to obtain a heat map.

[0031] The heatmap displays the geographic area of ​​each grid and the density level of the geographic area where the grid is located in a special color highlighting. The shade of color reflects the density level, for example, red represents a high density level and blue represents a low density level.

[0032] Therefore, by collecting user locations, user density, and pipeline wiring diagrams in the initial selection areas where OLT equipment is to be deployed, the user locations and user density are mapped onto a map using GIS software to generate a heat map. The heat map allows for easy filtering of multiple densely populated user areas, which are then prioritized as initial OLT deployment areas.

[0033] Furthermore, to accurately assess user needs and optimize the resource allocation of OLT devices, in one specific embodiment, the heatmap generated above can also be optimized.

[0034] Specifically, after obtaining the heatmap, the process further includes: acquiring user density data and multiple density levels from the heatmap; performing statistical analysis on each density level based on the user density data to determine the data variation for each density level; the statistical analysis includes calculating the average user density, standard deviation of user density, minimum user density, and maximum user density for each density level; normalizing the user density data in density levels where the data variation exceeds a preset threshold; clustering multiple density levels based on the normalized density level user density data using a preset clustering algorithm to obtain the clustered density levels and the corresponding range of user density data; and selecting grids with density levels greater than a preset density level from the heatmap and determining them as candidate regions, which includes: selecting grids with clustered density levels greater than a preset density level from the heatmap and determining them as candidate regions.

[0035] First, obtain the user density data from the heatmap and the current density level division. The user density data refers to the user density data within the corresponding division range for each density level; the data range for user density varies for different density levels.

[0036] Then, descriptive statistical analysis is performed on each density level, including calculating the average user density, standard deviation of user density, minimum user density, and maximum user density based on the user density data corresponding to each density level.

[0037] Statistical analysis is used to determine whether the data variation of user density at each density level exceeds a preset variation threshold. If it does, the user density data at that density level is normalized. Based on the normalized user density data at each density level, clustering optimization is performed on the density levels currently defined in the heatmap.

[0038] The formula for density-level clustering optimization is shown below: ; in, This represents the optimal number of clusters. Let represent the sum of variances within the i-th cluster, and k represent the total number of clusters.

[0039] The formula for clustering is as follows: ; in, This represents the i-th cluster; This represents data points, indicating the user density in each region. This represents the center point of the i-th cluster; This indicates the center point of other clusters.

[0040] Based on the clustering results, the data range for each cluster is obtained, which represents a new density level. The above clustering process is repeated to determine the density level and the corresponding user density data range for each cluster.

[0041] Correspondingly, based on the density level of the clustered data mapped by the optimized heatmap, grids with a density level greater than the preset density level can be selected and identified as candidate regions.

[0042] The above embodiments optimize GIS heat maps, including statistical analysis, data variation judgment, and cluster analysis, thereby accurately assessing user needs, determining the optimal user density level division and boundaries, optimizing the deployment area of ​​OLT devices, optimizing resource allocation, improving resource utilization efficiency and user satisfaction, and reducing operating costs and risks.

[0043] Step 106: Evaluate whether the network services provided when deploying optical line terminals in the candidate area meet the preset network service standards.

[0044] After selecting candidate regions, it is necessary to evaluate whether the network services provided by the optical line terminals (OLTs) deployed in the candidate regions can meet the preset network service standards. If not, the corresponding candidate regions are removed.

[0045] In one specific embodiment, evaluating whether the network service provided when deploying an optical line terminal in a candidate area meets a preset network service standard includes: using the center of the candidate area as the location for deploying the optical line terminal; using a preset network simulation tool to simulate the network architecture of the optical line terminal at the location and setting the simulated network parameters of the optical line terminal; and based on the network architecture and the simulated network parameters, evaluating whether the network service provided when deploying the optical line terminal at the location meets the preset network service standard, wherein the network service includes broadband performance and quality of service.

[0046] Specifically, the center of each candidate region is used as a potential OLT deployment point. Network simulation tools are used to evaluate the network services covered by the OLT at each potential OLT deployment point, including bandwidth performance and quality of service. The evaluated bandwidth performance and quality of service are compared with the expected network service standards to determine whether each deployment point meets the standards. If not, the corresponding deployment point is eliminated, resulting in optimized deployment points.

[0047] Network simulation tools such as OPNET, GNS3, or Cisco Packet Trace can be used to simulate the network architecture of OLT devices deployed at different locations. Simulation parameters for the OLT devices are set, including the number of users, data requirements, service types (such as VoIP, streaming media, data download, etc.), and other network conditions.

[0048] Then, based on the simulated OLT device network architecture and corresponding simulated parameters, bandwidth performance metrics are evaluated, such as throughput (to measure the amount of data the network can handle under high load conditions), network latency (to measure the transmission time of data from source to destination), and packet loss rate (to measure the proportion of packets lost under high traffic conditions). These metrics can help evaluate the network performance of OLT devices deployed at corresponding locations under different user densities and data traffic volumes.

[0049] It can also evaluate service quality metrics, such as QoS parameters, to assess service quality standards including latency, jitter (latency variation), and packet loss rate. It can also evaluate priority and policy tests, i.e., assess whether the network of OLT devices deployed at corresponding locations can correctly prioritize important data flows according to service type.

[0050] These evaluation tests ensure that the deployed OLT devices can provide stable and reliable services under various conditions, meeting the specific needs of different businesses. By evaluating the bandwidth performance and service quality at different deployment locations using network simulation tools and comparing them with expected standards, potential bottlenecks in the network can be effectively identified and optimized in a timely manner.

[0051] In addition, to further improve the sustainable and stable provision of high-quality network services by deployed OLT devices, when there are multiple candidate regions, a better region can be selected from multiple candidate regions for subsequent network service evaluation.

[0052] In one specific embodiment, optionally, the candidate regions include multiple regions. Before evaluating whether the network service provided by the deployment of optical line terminals in the candidate regions meets the preset network service standards, the method further includes: determining the standardized values ​​of the evaluation indicators for each candidate region, wherein the evaluation indicators include at least one of total user demand, network coverage, and population growth rate; sorting the candidates in descending order according to the standardized values, and selecting a predetermined number of candidate regions ranked first from each candidate region for the evaluation; wherein the total user demand is related to the statistical population and average user density of each candidate region.

[0053] The total user demand in a candidate region is related to the parameters of the currently registered network users in that region, including the statistical population and average user density of the candidate region, which limits the minimum network services that the OLT device must provide.

[0054] The quantitative formula for evaluating the total user demand is as follows: ; in, This represents the total user demand for the i-th candidate region. This represents the statistical population of the i-th candidate region. This represents the average user density of the i-th candidate region.

[0055] Pipeline network is a general term for communication pipelines and optical cable lines. In the context of OLT deployment, it specifically refers to the infrastructure system that carries the physical transmission of optical fibers, consisting of pipelines, manholes, optical cable junction boxes, splice boxes, and various optical cables. By analyzing the pipeline network coverage in each candidate area using GIS tools, the higher the pipeline network coverage, the more significantly the failure rate and maintenance costs can be reduced after OLT deployment.

[0056] The quantitative formula for assessing population growth rate is as follows: ; in, This represents the population growth rate of the i-th candidate region. This represents the predicted future population of the i-th candidate region. This represents the current population of the i-th candidate region.

[0057] Specifically, the evaluation indicators include the population growth rate. Determining the standardized values ​​of the evaluation indicators for each candidate region includes: obtaining current and historical population data for the target candidate region; analyzing the fluctuations in the historical population data to determine whether the fluctuation trend is stationary or non-stationary; if it is stationary, using a linear regression model to predict the future population of the target candidate region; if it is non-stationary, using a pre-trained time series prediction model to predict the future population of the target candidate region.

[0058] The predicted future population for each candidate region is determined as follows: historical population data is obtained, and the fluctuations in the historical population data are analyzed to determine whether the fluctuation trend is stationary or non-stationary. If it is stationary, a linear regression model is used to predict the future population. If it is non-stationary, a time series prediction model, such as the Autoregressive Integrated Moving Average (ARIMA) model, is used to predict the future population.

[0059] When analyzing fluctuations in historical population data, the augmented Dickey-Fowler (ADF) test is used to examine whether the time series is non-stationary. ; in, This represents the sequence after difference; Represents a constant term; Indicates a time trend; A coefficient representing the delay value; This indicates the value from the previous period; This represents the difference in the previous p periods; Indicates the error term; This represents the lag coefficient of the difference sequence.

[0060] Parameters in the time series were examined by running the ADF test. Whether the value is 0 determines whether the time series is stationary. If a unit root exists, the time series is non-stationary; if If the t-statistic is less than the critical value or the p-value is less than 0.05, then the time series is stationary.

[0061] When calculating the t value, the parameters are first estimated using the least squares method. The estimated value Estimates based on estimations The value of t is calculated as follows: ; in, Indicates the estimated value The standard deviation.

[0062] The p-value represents the probability of the observed statistic or a more extreme value occurring under the null hypothesis; where the null hypothesis is... In the ADF test, the null hypothesis is... This indicates the existence of a unit root, meaning the time series is not stationary.

[0063] In one embodiment of this application, the standardized values ​​of any one of the total user demand, network coverage, and population growth rate can be sorted in descending order from largest to smallest, and a predetermined number of candidate regions ranked first can be selected from each candidate region for subsequent network service evaluation.

[0064] Alternatively, the standardized values ​​of any two or three of the total user demand, pipeline coverage, and population growth rate can be summed, and all candidate areas can be sorted in descending order based on the summed values. A predetermined number of candidate areas can be selected and ranked first, such as the top five candidate areas.

[0065] By considering user demand and pipeline coverage, the selected candidate areas not only meet the requirement of high user demand but also ensure high pipeline infrastructure support for OLT equipment, thus reducing the failure rate and maintenance costs after OLT equipment deployment. By considering population growth rates, OLT deployment locations can be adjusted in a timely manner to dynamically adapt to changes in regional demand, improve service quality, and lay a solid foundation for future expansion and upgrades of OLT equipment.

[0066] By integrating multi-dimensional data such as user location, pipeline wiring, and population growth rate, cross-departmental data collaboration can be achieved, thereby enabling more efficient OLT planning and optimization.

[0067] Step 108: Deploy the optical line terminal in the target area of ​​the candidate area that meets the preset network service standard.

[0068] In this embodiment, the candidate regions that meet the preset network service standards selected from multiple candidate regions in the above steps are used as the final deployment regions for the OLT devices, and the corresponding OLT devices are deployed.

[0069] By considering candidate areas that meet user density requirements and network service standards as deployment areas for OLT equipment, scientific management and optimized decision-making for OLT equipment deployment have been achieved, significantly improving resource utilization efficiency and user satisfaction, reducing operating costs and risks, and adapting to the needs of modern network services.

[0070] Below, in conjunction with Figure 2 The overall example flow of the deployment method of the optical line terminal according to the embodiments of this application is described.

[0071] like Figure 2 As shown, it includes the following steps: Step 202: Determine the area where the OLT device is to be deployed based on the service radius of the OLT device and the area that needs the service of the OLT device; Step 204: Collect user locations, user density, and pipeline wiring diagrams for the area where OLT equipment is to be deployed. Map the user locations and user density onto the map using GIS software to generate a heat map. Step 206: Select multiple densely populated user areas based on the heat map, and use these areas as the initial OLT deployment areas; Step 208: Based on the total user demand, the network support for OLT equipment, and population growth trends in each OLT deployment area, select OLT deployment areas to obtain multiple determined OLT deployment areas; Step 210: Use the center of each determined OLT deployment area as a potential OLT deployment point; use network simulation tools to evaluate the bandwidth performance and quality of service covered by different deployment points for each potential OLT deployment point; compare the evaluated bandwidth performance and quality of service with the expected network service standards to determine whether each deployment point meets the standards. If it does not meet the standards, the corresponding deployment point is removed to obtain the optimized deployment points.

[0072] This embodiment deploys OLT devices based on user distribution. It identifies densely populated user areas by generating heat maps and prioritizes these areas for deployment. Furthermore, by considering user demand and the official network's support for OLT devices, it ensures that deployment locations not only have high user demand but also strong network infrastructure support, reducing post-deployment failure rates and maintenance costs. Finally, network simulation tools are used to evaluate the bandwidth performance and service quality of different deployment locations, ensuring that each location meets or exceeds predetermined network service standards. Therefore, starting from service requirements and combining GIS (Geographic Information System) technology and network simulation tools, it achieves scientific management and optimized decision-making for OLT device deployment, significantly improving resource utilization efficiency and user satisfaction, reducing operating costs and risks. This not only meets the needs of modern network services but also lays a solid foundation for future expansion and upgrades.

[0073] In this embodiment, a preliminary area for deploying an optical line terminal (OLT) is determined based on the service radius of the OLT and the service demand area requiring network services from the OLT. Based on the location and number of users within the preliminary area, a candidate area with a user density exceeding a preset density threshold is determined. The network services provided by deploying the OLT in the candidate area are evaluated to ensure they meet preset network service standards. The OLT is then deployed in a target area within the candidate area that meets the preset network service standards. This fully utilizes key information about user distribution and, combined with network service standards, selects a suitable OLT deployment location, achieving scientific management and optimized decision-making for OLT deployment. This improves network coverage and resource utilization efficiency, increases user satisfaction, reduces operating costs and risks, and adapts to the needs of modern network services.

[0074] Optionally, such as Figure 3 As shown in the figure, this application embodiment also provides an optical line terminal deployment device 2000, including a processor 2400 and a memory 2200. The memory 2200 stores a program or instructions that can run on the processor 2400. When the program or instructions are executed by the processor 2400, they implement the various steps of the above-described optical line terminal deployment method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0075] This application also provides a readable storage medium storing a program or instructions. When executed by a processor, the program or instructions implement the various processes of any of the above-described deployment method embodiments of the optical line terminal, achieving the same technical effect. To avoid repetition, further details are omitted here. The readable storage medium includes computer-readable storage media, such as read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0076] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. The computer program is operable to enable a computer to execute various processes of any of the above-described optical line terminal deployment method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0077] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0079] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for deploying an optical line terminal, characterized in that, include: Based on the service radius of the optical line terminal and the service demand area that requires the optical line terminal to provide network services, the initial selection area for deploying the optical line terminal is determined. Based on the location and number of users in the initial selection area, candidate areas with user density greater than a preset density threshold are determined. Evaluate whether the network services provided when deploying optical line terminals in candidate areas meet the preset network service standards. The optical line terminal is deployed in the target area of ​​the candidate area that meets the preset network service standard.

2. The method according to claim 1, characterized in that, Determining candidate regions where the user density in the initially selected region is greater than a preset density threshold includes: Based on the location distribution map corresponding to the location of each user in the initial selection area, the initial selection area is divided into multiple grids; Calculate the user density of each grid based on its area and the number of users it contains; The user density corresponding to each grid is mapped to different density levels, and two adjacent grids with the same user density level are merged into one grid; A heat map is generated based on each fused grid and its corresponding density level, and then overlaid onto the map of the initially selected area using geographic information system software to obtain a heat map. The heat map uses different colors to represent the density level of grids at different locations. Based on the heat map, grids with a density level greater than a preset density level are selected and identified as candidate regions.

3. The method according to claim 1, characterized in that, Based on the service radius of the optical line terminal and the service demand area requiring optical line terminal network services, the initial selection area for deploying the optical line terminal is determined, including: Geographic Information System (GIS) software is used to map and mark the service demand areas; Using any point in the service demand area as the center and the maximum service radius of the optical line terminal as the radius, draw a circle to obtain the corresponding circle to simulate multiple coverage areas of the optical line terminal. The intersection of all the circular areas whose coverage completely covers the service demand area is determined as the initial selection area for the deployment of optical line terminals.

4. The method according to claim 2, characterized in that, After obtaining the heatmap, it also includes: Obtain user density data and the multiple density levels defined in the heatmap; Statistical analysis is performed on each density level based on the user density data to determine the data variation of each density level. The statistical analysis includes calculating the average user density, user density standard deviation, minimum user density, and maximum user density for each density level. Normalize the user density data in the density level where the data variation is greater than the preset edge threshold; Based on the user density data of the normalized density levels, multiple density levels are clustered using a preset clustering algorithm to obtain the clustered density levels and the corresponding range of user density data. The step of selecting grids with a density level greater than a preset density level based on the heat map and determining them as candidate regions includes: selecting grids with a density level greater than a preset density level after clustering based on the heat map and determining them as candidate regions.

5. The method according to claim 1, characterized in that, The evaluation assesses whether the network services provided by the deployment of optical line terminals in candidate areas meet the preset network service standards, including: The center of the candidate area is used as the location for deploying optical line terminals; The network architecture for deploying optical line terminals at the specified locations is simulated using a preset network simulation tool, and the simulated network parameters for the optical line terminals are set. Based on the network architecture and the simulated network parameters, the network services provided when the optical line terminal is deployed at the location are evaluated to ensure that they meet the preset network service standards, including broadband performance and quality of service.

6. The method according to claim 1, characterized in that, The candidate regions include multiple regions. Before evaluating whether the network service provided by the deployment of optical line terminals in the candidate regions meets the preset network service standards, the evaluation also includes: Determine the standardized values ​​of the evaluation indicators for each candidate region, wherein the evaluation indicators include at least one of the following: total user demand, pipeline coverage, and population growth rate. Sort the candidate regions in descending order according to the standardized values, and select a predetermined number of candidate regions that rank first from each candidate region for the evaluation. The total user demand is related to the statistical population and average user density of each candidate region.

7. The method according to claim 6, characterized in that, The evaluation indicators include population growth rate. Standardized values ​​for the evaluation indicators for each candidate region are determined, including: Obtain current and historical population data for the target candidate region; The fluctuations in the historical population data are analyzed to determine whether the fluctuation trend of the historical population data is stationary or non-stationary. If the fluctuation is stationary, a linear regression model is used to predict the future population of the target candidate region; If the fluctuation is non-stationary, a pre-trained time series prediction model is used to predict the future population of the target candidate region; Based on the current and future population, a standardized value for the population growth rate of the target candidate region is determined.

8. A deployment device for an optical line terminal, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the method as described in any one of claims 1-7.

9. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, The computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform the steps of the method as described in any one of claims 1-7.

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