An optical cable wiring relationship configuration method, system, device and medium

Abstract

The application discloses a kind of optical cable wiring relationship configuration method, system, equipment and medium, belong to electric power system field, the method is: determine the time interval of optical fiber channel dynamic scheduling, to be scheduled region, can be borrowed and adjusted region, to be scheduled optical fiber channel set, can be borrowed and adjusted optical fiber channel set, and the matching scheme between can be borrowed and adjusted optical fiber channel set and to be scheduled optical fiber channel set;Determine wavelength sequence based on user behavior data and wavelength use data, and determine first wiring scheme based on wavelength sequence and matching scheme;According to the load balancing index and matching index of current iteration, iteratively update wavelength sequence, until the load balancing index is less than or equal to the equilibrium threshold, and the matching index is greater than or equal to the matching threshold, stop iteration, and output second wiring scheme, therefore, by implementing the application, the resource utilization and load balancing of optical cable wiring relationship configuration can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of optical fiber communication, and in particular to an optical cable wiring relationship configuration method, system, device and medium. BACKGROUND

[0002] As a pillar technology in modern information society, optical fiber communication plays a vital role in ensuring network connection in complex areas such as commercial parks and residential communities. With the acceleration of urbanization and the diversification of user behavior patterns, dynamic scheduling of optical cable resources has become a key to improving network service quality and resource utilization efficiency.

[0003] However, traditional management of optical cable wiring relationship relies on static configuration and manual intervention, such as determining a configuration scheme based on a fixed allocation model, which cannot effectively cope with tidal flow between different regions, where tidal flow refers to the regular migration of network traffic from one region to another within a fixed period, and lacks the ability to respond to dynamic changes in user behavior. Therefore, the traditional scheme has the problems of low resource utilization and poor load balancing of optical fiber channels. SUMMARY

[0004] The present application provides an optical cable wiring relationship configuration method, system, device and medium, which can solve the problems of low resource utilization and poor load balancing of optical fiber channels in optical cable wiring relationship configuration.

[0005] The present application provides an optical cable wiring relationship configuration method, comprising:

[0006] determining a time interval for dynamic scheduling of optical fiber channels based on a flow fluctuation curve, and determining a to-be-scheduled region and a borrowable region in the time interval; in the to-be-scheduled region, determining a set of to-be-scheduled optical fiber channels for which first load data meets scheduling conditions; in the borrowable region, determining a set of borrowable optical fiber channels for which bandwidth data meets borrowing conditions; and determining a matching scheme between the set of borrowable optical fiber channels and the set of to-be-scheduled optical fiber channels;

[0007] determining a wavelength sequence based on user behavior data and wavelength usage data in the to-be-scheduled region in the time interval, and determining a first wiring scheme between the set of to-be-scheduled optical fiber channels and the set of borrowable optical fiber channels based on the wavelength sequence and the matching scheme;

[0008] updating the wavelength sequence according to the load balancing index and the matching index of the current iteration, until the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, stopping iteration, and outputting a second wiring scheme; wherein, at each iteration, the first wiring scheme is updated according to the wavelength sequence updated in the current iteration, and the load balancing index of each fiber channel to be scheduled in the updated first wiring scheme is calculated; the matching index is the index between the wavelength sequence of the current iteration and the traffic fluctuation curve; and the second wiring scheme is used to configure the cable wiring relationship between the to-be-scheduled area and the borrowable area.

[0009] The embodiment of the application determines a time interval of cable scheduling based on a traffic fluctuation curve, ensures accurate timing of scheduling, and avoids invalid scheduling. Through iterative updating of the load balancing index and the matching index, the wavelength sequence is optimized, the balanced allocation of cable load is realized, and the network stability is improved. In combination with user behavior data and wavelength usage data, the wiring relationship is dynamically adjusted to adapt to traffic changes and improve resource utilization efficiency.

[0010] Further, the wavelength sequence is determined based on the user behavior data and the wavelength usage data of the to-be-scheduled area in the time interval, and the first wiring scheme between the set of to-be-scheduled fiber channels and the set of borrowable fiber channels is determined based on the wavelength sequence and the matching scheme, specifically as follows:

[0011] The traffic data in the time interval is analyzed to obtain user behavior data, wherein the user behavior data includes multiple user behavior features and wavelength usage frequencies corresponding to each wavelength, and each user behavior feature corresponds to multiple wavelengths.

[0012] A plurality of first wavelengths with a wavelength usage frequency greater than or equal to a first preset threshold are sorted according to the wavelength usage frequency to obtain a first wavelength set corresponding to the wavelength sequence.

[0013] Based on the wavelength sequence, the bandwidth data of each first wavelength in the first wavelength set is matched with the bandwidth data of each channel in the set of borrowable fiber channels in sequence, and the first wavelength that is successfully matched is allocated to the corresponding channel to obtain the first wiring scheme.

[0014] In this way, by sorting the wavelength usage frequency, high-frequency wavelengths are preferentially configured to improve the utilization efficiency of wavelength resources. By matching the bandwidth data, the wavelength and the channel are accurately configured to ensure the rationality of resource allocation. Based on the user behavior data, the wavelength sequence is determined to make the configuration scheme more in line with the actual user demand and improve the user experience.

[0015] Further, the wavelength sequence is determined based on the user behavior data and the wavelength usage data of the to-be-scheduled region within the time interval, and a first wiring scheme between the set of to-be-scheduled fiber channels and the set of borrowable fiber channels is determined based on the wavelength sequence and the matching scheme, specifically:

[0016] Real-time traffic data is acquired, if the real-time usage rate of the second wavelength continues to rise and the duration is greater than or equal to a preset time threshold, the second wavelength is added to the first wavelength set to obtain a second wavelength sequence and a second wavelength set, wherein the second wavelength refers to a wavelength with a usage frequency less than a first preset threshold;

[0017] Based on the second wavelength sequence, the bandwidth data of each second wavelength in the second wavelength set is matched with the bandwidth data of the channels in the set of borrowable fiber channels that have not been successfully matched to obtain an updated first wiring scheme.

[0018] In this way, by dynamically adding the wavelength set for the wavelength with a low usage frequency but a continuously rising usage rate, the adaptive ability of the system is enhanced. By secondary matching, the fiber channels that have not been successfully matched are fully utilized to further optimize resource allocation. The wavelength sequence and the wiring relationship can be adjusted in real time according to traffic changes to adapt to complex network environments.

[0019] Further, the set of to-be-scheduled fiber channels is determined by the first load data of the multiple fiber channels in the to-be-scheduled region that satisfy the scheduling condition, the set of borrowable fiber channels is determined by the bandwidth data of the multiple fiber channels in the borrowable region that satisfy the borrowing condition, and a matching scheme between the set of borrowable fiber channels and the set of to-be-scheduled fiber channels is determined, specifically:

[0020] The traffic fluctuation curves corresponding to each operation region are analyzed to obtain operation region grouping data, wherein each operation region grouping includes a to-be-scheduled region and a to-be-scheduled region corresponding borrowable region;

[0021] Based on the bandwidth data of each fiber channel in the to-be-scheduled region, each fiber channel in the set of to-be-scheduled fiber channels is clustered to obtain a plurality of channel sets, and there is a scheduling sequence between each channel set;

[0022] Based on the scheduling sequence, the size relationship between the load data of each channel in each channel set and a second preset threshold is compared in sequence, and the multiple channels with load data greater than or equal to the second preset threshold are determined as the set of to-be-scheduled fiber channels;

[0023] Determine the multiple channels in the borrowable area as the set of borrowable FCs and determine the matching scheme based on the size relationship between the bandwidth data of each channel in the set of FCs to be scheduled and the bandwidth data of each channel in the borrowable area.

[0024] In this way, the area to be scheduled and the borrowable area are determined by grouping the operation areas, the scheduling process is simplified, and the scheduling efficiency is improved. The channels are clustered and analyzed to determine the scheduling sequence, ensuring the orderliness of the scheduling. Based on the matching of the load data and the bandwidth data, the FCs to be scheduled and the FCs that can be borrowed are accurately identified, and resource waste is avoided.

[0025] Further, the time interval for dynamic scheduling of the FCs is determined based on the traffic fluctuation curve, and the area to be scheduled and the borrowable area of the time interval are determined, specifically:

[0026] Obtain the initial bandwidth data of all channels, perform data cleaning and format conversion on the initial bandwidth data to obtain bandwidth data, and use a sliding window to perform traffic calculation and Fourier transform analysis on the bandwidth data to obtain the traffic fluctuation curve;

[0027] Identify multiple traffic maxima and multiple traffic minima of the traffic fluctuation curve, and perform time series analysis on the distribution characteristics of each traffic maxima and traffic minima switching to obtain a first time node and a second time node corresponding to hot spot migration;

[0028] Calculate the difference value of the bandwidth data between the first time node and the second time node to obtain an initial time interval, and when the difference value is greater than or equal to a third preset threshold, adjust the initial time interval by a linear interpolation method to obtain a time interval.

[0029] In the time interval, generate a heat map based on the obtained multiple resource scheduling requests, wherein the heat map identifies the bandwidth data by color;

[0030] Determine an initial area based on the coordinate position corresponding to the maximum value of the bandwidth data in the heat map, and when the bandwidth data of the initial area exceeds a fourth preset threshold, adjust the initial area by a linear interpolation method to obtain the area to be scheduled.

[0031] In this way, the traffic extreme value and the hot spot migration time point are accurately identified through the traffic fluctuation curve analysis, providing a scientific basis for scheduling. The time interval is adjusted by a linear interpolation method to ensure the accuracy of the scheduling time. The heat map is generated to visually display the bandwidth data distribution, which assists in determining the area to be scheduled and improves the visualization degree of the scheduling.

[0032] Further, the wavelength sequence is iteratively updated according to the load balancing index and the matching index of the current iteration, and the iteration is stopped when the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, specifically:

[0033] The wavelength sequence is updated according to the load balancing index of the current iteration, and it is determined whether the matching index is greater than or equal to the matching threshold when the load balancing index is less than or equal to the balancing threshold, and if so, the iteration is stopped.

[0034] If not, the load balancing index is updated based on the matching index, and the wavelength sequence is iteratively updated based on the updated load balancing index until the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, and the iteration is stopped.

[0035] In this way, the wavelength sequence is gradually optimized through the iterative update of the load balancing index and the matching index, ensuring the optimality of resource allocation. The comprehensiveness and effectiveness of the scheduling scheme are ensured by considering load balancing and matching degree. The wavelength sequence is dynamically adjusted according to real-time data to adapt to traffic changes and improve the adaptive ability of the system.

[0036] Further, the optical cable wiring relationship configuration method further comprises:

[0037] The optical cable wiring relationship configuration method further comprises:

[0038] According to the first mapping rule, the initial load data and the initial wavelength data of each channel in each of the to-be-scheduled fiber channel sets in the initial state are mapped to generate a first index map;

[0039] Based on the initial load data and the real-time load data of each channel in each of the to-be-scheduled fiber channel sets, a load fluctuation value is calculated, and if the load fluctuation value is greater than or equal to a fifth preset threshold, the second wiring scheme is updated until the load fluctuation value is less than the fifth preset threshold, and the target load data and the target wavelength data of each channel in the to-be-scheduled fiber channel are obtained.

[0040] According to the second mapping rule, the target load data and the target wavelength data are remapped to generate a second index map;

[0041] In combination with the user's visual demand and the second index map, a target configuration image is generated and image rendering is performed, wherein the target configuration image is used to display the updated second wiring scheme.

[0042] In this way, by generating an index map and a target configuration image, the configuration scheme is intuitively displayed, and the transparency and operability of the configuration are enhanced. In the scheduling process, the wiring relationship is adjusted in real time to ensure that the load fluctuation is within a reasonable range and to improve the network stability. In combination with the visual needs of the user, the target configuration image is generated and image rendering is performed, thereby improving the understanding and acceptance of the user for the configuration scheme.

[0043] Another embodiment of the present application also provides an optical cable wiring relationship configuration system, comprising a channel matching module, a wavelength allocation module and a configuration module.

[0044] The channel matching module is configured to determine a time interval of optical fiber channel dynamic scheduling based on a traffic fluctuation curve, determine a to-be-scheduled area and a borrowable area of the time interval, determine, in the to-be-scheduled area, a plurality of optical fiber channels whose first load data satisfy a scheduling condition as a to-be-scheduled optical fiber channel set, determine, in the borrowable area, a plurality of optical fiber channels whose bandwidth data satisfy a borrowing condition as a borrowable optical fiber channel set, and determine a matching scheme between the borrowable optical fiber channel set and the to-be-scheduled optical fiber channel set.

[0045] The wavelength allocation module is configured to determine a wavelength sequence based on user behavior data and wavelength usage data of the to-be-scheduled area in the time interval, and determine a first wiring scheme between the to-be-scheduled optical fiber channel set and the borrowable optical fiber channel set based on the wavelength sequence and the matching scheme.

[0046] The configuration module is configured to iteratively update the wavelength sequence according to a load balancing index and a matching index of a current iteration until the load balancing index is less than or equal to an equilibrium threshold and the matching index is greater than or equal to a matching threshold, stop the iteration, and output a second wiring scheme. In each iteration, the first wiring scheme is updated according to the wavelength sequence updated in the current iteration, and a load balancing index of each to-be-scheduled optical fiber channel in the updated first wiring scheme is calculated. The matching index is an index between the wavelength sequence of the current iteration and the traffic fluctuation curve. The second wiring scheme is used to configure the optical cable wiring relationship of the to-be-scheduled area and the borrowable area.

[0047] The embodiment of the present application determines the time interval of optical cable scheduling based on the traffic fluctuation curve, ensures the timing of scheduling, and avoids invalid scheduling. Through the iterative update of the load balancing index and the matching index, the wavelength sequence is optimized, the balanced allocation of the optical cable load is realized, and the network stability is improved. In combination with the user behavior data and the wavelength usage data, the wiring relationship is dynamically adjusted to adapt to the traffic changes and improve the resource utilization efficiency.

[0048] Another embodiment of the present application also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, when the computer program is executed by the processor, steps of the power system operation state identification method of the present application are implemented.

[0049] Another embodiment of the present application also provides a computer readable storage medium item, comprising: a stored computer program, when the computer program is executed, the device where the computer readable storage medium is located is controlled to execute steps of the power system operation state identification method of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings described in the following are only some of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0051] Figure 1 is a flowchart of an embodiment of the optical cable wiring relationship configuration method;

[0052] Figure 2 is a structural schematic diagram of an embodiment of the optical cable wiring relationship configuration system. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the present application more clear, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "include" and "have" and any variations thereof in the specification and claims of the present application and the above description of drawings are intended to cover non-exclusive inclusion.

[0055] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0056] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. As those skilled in the art will appreciate, embodiments described herein can be combined with one another.

[0057] In the description of the embodiments of the application, the term "and / or" is merely an association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after it.

[0058] In the description of the embodiments of the application, the term "a plurality of" refers to two or more (including two), and similarly, "a plurality of groups" refers to two or more groups (including two groups), and "a plurality of pieces" refers to two or more pieces (including two pieces).

[0059] In the description of the embodiments of the application, unless otherwise explicitly specified and limited, the technical terms "mounting", "connection", "connection", "fixing" and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanical connection, or it can be electrical connection; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meaning of the above terms in the embodiments of the application can be understood according to the specific circumstances.

[0060] Reference Figure 1 To solve the problems of low resource utilization and poor load balancing of optical fiber channels in the prior art cable wiring relationship configuration, an embodiment of the application provides a cable wiring relationship configuration method, as shown in Figure 1 The method comprises steps S101-S103, and each step is specifically as follows:

[0061] S101, determining a time interval of optical fiber channel dynamic scheduling based on a flow fluctuation curve, and determining a to-be-scheduled area and a borrowable area of the time interval; in the to-be-scheduled area, a plurality of optical fiber channels whose first load data satisfy a scheduling condition are determined as a to-be-scheduled optical fiber channel set; in the borrowable area, a plurality of optical fiber channels whose bandwidth data satisfy a borrowing condition are determined as a borrowable optical fiber channel set; and a matching scheme between the borrowable optical fiber channel set and the to-be-scheduled optical fiber channel set is determined.

[0062] In this embodiment, for the area where there is tidal flow, the flow fluctuation curve corresponding to each channel is obtained, wherein the flow fluctuation curve refers to the trend graph of the flow in each optical fiber channel with time, which is used to reveal the intuitive law of flow fluctuation. For each channel, the peak and trough of its flow fluctuation curve can be identified. If the flow fluctuation curve of the channel shows that the channel reaches the flow peak period from the flow trough period, the channel may have channel resource shortage, and fiber resource scheduling needs to be performed before the flow peak period is reached. The resource allocation ratio is adjusted according to the fiber usage to obtain the optimized resource state. If the flow fluctuation curve shows that the channel reaches the flow trough period from the flow peak period, the channel may have idle channel resources, and fiber resource borrowing can be performed before the next flow peak period or after the last flow peak period. The fiber usage can be compared and analyzed through historical flow data to determine whether to reduce resource allocation to obtain an adjusted allocation scheme. According to the adjusted resource allocation scheme, the future flow peak and trough are predicted in combination with the periodic characteristics of the fluctuation curve to obtain long-term resource planning data. For example, in the flow fluctuation curve, the peak period is from 14:00 to 16:00, and the utilization rate is 90%, while the trough period is only 20%. If the target time is 15:00, which is in the peak period, the resource allocation ratio is adjusted according to the fiber usage. Preferably, if a channel is overloaded, part of the flow can be distributed to a backup channel with lower utilization rate, and the optimized peak utilization rate is reduced to 70%, thereby improving network stability. The trough period is from 02:00 to 04:00, and the historical data comparison and analysis shows that, for example, the average utilization rate of the backup channel in the past week is 15%, and the current utilization rate is 20%, which has little difference. The resource allocation of the backup channel can be reduced, such as reducing the reserved bandwidth from 2Gbps to 1Gbps, thereby saving cost while maintaining service quality. According to the adjusted allocation scheme, the future flow peak and trough are predicted in combination with the periodicity of the fluctuation curve. For example, the analysis shows that the flow increases sharply at 14:00 every Monday, and the bandwidth can be increased to 12Gbps in advance, while the bandwidth is maintained at 8Gbps during the trough period. This long-term resource planning data supports dynamic adjustment, avoids resource waste or deficiency, and improves the overall efficiency of the optical fiber network. Further analysis of the flow fluctuation curves of all channels is performed to determine the time interval of dynamic scheduling of the optical fiber channels, and the area to be scheduled and the area that can be borrowed are determined.In the to-be-scheduled region, all fiber channel in the region is obtained based on the region coordinate position and the network topology structure, and whether each channel needs to be scheduled is judged according to the load value of each channel, so as to determine the to-be-scheduled channel, and a to-be-scheduled fiber channel set is obtained; and based on the region coordinate position of the to-be-scheduled region, a borrowable region that can provide fiber resources to the to-be-scheduled region is determined, and all fiber channels in the region are obtained based on the region coordinate position of the borrowable region, and whether each to-be-scheduled channel of the to-be-scheduled region can be provided with fiber resources is judged according to the bandwidth value of each channel in the borrowable region, so as to determine the borrowable channel and the corresponding relationship between the borrowable channel and the to-be-scheduled channel, and a borrowable channel set and a matching scheme are obtained.

[0063] As an example of an embodiment of the application, the time interval of the fiber channel dynamic scheduling is determined based on the traffic fluctuation curve, and the to-be-scheduled region and the borrowable region of the time interval are determined, specifically: the initial bandwidth data of all channels is obtained, the initial bandwidth data is data cleaned and format converted to obtain bandwidth data, and the bandwidth data is calculated and Fourier transform analyzed by using a sliding window to obtain the traffic fluctuation curve; a plurality of traffic maximum values and a plurality of traffic minimum values of the traffic fluctuation curve are identified, time series analysis is performed on the distribution characteristics of each traffic maximum value and the traffic minimum value when switching, a first time node and a second time node corresponding to hot spot migration are obtained; the difference value of the bandwidth data between the first time node and the second time node is calculated to obtain an initial time interval, when the difference value is greater than or equal to a third preset threshold, the initial time interval is adjusted by a linear interpolation method to obtain; in the time interval, a heat map is generated based on the obtained plurality of scheduling requests, wherein the heat map identifies the bandwidth data by color; the initial region is determined based on the coordinate position corresponding to the maximum value of the bandwidth data in the heat map, when the bandwidth data of the initial region exceeds a fourth preset threshold, the initial region is adjusted by a linear interpolation method to obtain the to-be-scheduled region.

[0064] In this embodiment, initial bandwidth data can be extracted from the fiber switch through a network management tool, including time, channel number and bandwidth usage. Through data cleaning and format conversion processing, the initial bandwidth data is converted into loan data including timestamp and utilization. For example, assuming that the bandwidth usage of a certain fiber channel is 5 Gbps at 08:00 on March 27, the total bandwidth is 10 Gbps, and the utilization is 50%. During data cleaning, abnormal values such as negative values or data exceeding the total bandwidth are removed, and the time format is unified to "YYYY-MM-DDHH:MM:SS" to generate bandwidth data containing timestamp and utilization. Based on the timestamp and utilization of the bandwidth data, a sliding window can be used to calculate the flow change value. For example, the window size is set to 1 hour and the step is 10 minutes. The difference value of the utilization in each window is calculated. If the utilization at 08:00 is 50% and the utilization at 08:10 is 55%, the change value is 5%. Through continuous calculation, the trend graph of the flow change over time is obtained. According to the change trend, Fourier transform is further used to analyze the periodic characteristics of the change trend to obtain the flow fluctuation curve. Assuming that the flow data presents a daily peak, the transformed data may show a 24-hour periodic frequency. After generating the flow fluctuation curve, the peak may occur at 14:00-16:00 and the trough at 02:00-04:00. This periodic analysis helps to predict the flow pattern and improve the scientificity of resource planning. Through the flow fluctuation curve, the peak and the trough are identified, i.e. the flow maximum value and the flow minimum value, and the distribution characteristics of the peak and the trough switching are obtained through time series analysis, which can reveal the regularity of the flow change in the fiber network. For example, assuming that the fiber network in a certain area presents multiple peak and trough switching points within a day, and after analyzing the historical data, it is found that the switching is mostly concentrated in 08:00-10:00 and 18:00-20:00, which reflects the time distribution of user usage habits. By observing the utilization mutation point, the time node of hot spot migration is determined. For example, a certain channel jumps from 20% to 80% at 09:00, indicating that hot spot migration occurs. This time node can be used as a key reference for fiber resource scheduling. The resource utilization data is extracted from the time node of hot spot migration, and the utilization difference value at the switching time is calculated, which is a direct way to evaluate the flow change amplitude. For example, the difference value between 20% at 09:00 and 80% at 09:10 is 60%. This difference value reflects the sharp change of resource demand. When determining the time interval of fiber channel dynamic scheduling using the difference value result, the initial time interval can be set to 09:00-09:30, covering the high demand stage in the initial stage of switching. Specifically, if the difference value is greater than or equal to a third preset threshold value, such as 50%, the boundary is adjusted through linear interpolation. For example, the utilization gradually increases from 20% to 80% in the window 09:00-09:30, and after interpolation, the window may be expanded to 08:50-09:40 to ensure that the complete change process is covered.After obtaining the adjusted time interval, the time interval for cross-regional rotation is determined in combination with the periodic characteristics of the time series. It should be noted that if the data presents a daily 09:00 periodic peak, the final range can be fixed as 08:50-09:40 to ensure scheduling consistency. Within the time interval, real-time heat maps can be generated by collecting scheduling request data, which can directly reflect the resource distribution state of the optical fiber network. For example, assuming that the optical fiber network of a city collects data from 08:00 to 10:00, the heat map shows that the central region is red and the edge region is green, indicating that the central region has a high demand for traffic. The heat map uses color depth to mark utilization, and the red area may reach more than 80%, while the green area is less than 30%, which provides a basis for subsequent analysis. By extracting the coordinate position of the high demand area from the heat map, the initial region is determined. For example, the coordinate range of the central region may be X=10-15, Y=20-25, and the utilization data indicates that this is a traffic concentration point; if the heat map shows that the utilization at X=12, Y=22 is 90%, which is the maximum utilization in the real-time heat map, then this position is taken as the initial region. It should be noted that coordinate extraction needs to be combined with network topology to ensure that the position corresponds to the actual channel. For the initial region, after obtaining the real-time data of the optical fiber resources, if the utilization exceeds the preset threshold, such as 70%, the range needs to be adjusted. Specifically, assuming that the utilization near X=12 increases from 60% to 90%, the range can be extended to X=11-13 through linear interpolation, covering potential high demand points, and obtaining the region to be scheduled. This adjustment considers the gradual nature of traffic fluctuations, ensuring that the range is more in line with reality.

[0065] As an example of an embodiment of the application, the first load data of the plurality of fiber channels in the region to be scheduled that meet the scheduling condition are determined as the set of fiber channels to be scheduled; the bandwidth data of the plurality of fiber channels in the region available for borrowing that meet the borrowing condition are determined as the set of fiber channels available for borrowing; and a matching scheme between the set of fiber channels available for borrowing and the set of fiber channels to be scheduled is determined, specifically: analyzing the traffic fluctuation curves corresponding to each operation region to obtain operation region grouping data, wherein each operation region grouping includes a region to be scheduled and a region available for borrowing corresponding to the region to be scheduled; clustering each fiber channel in the set of fiber channels to be scheduled based on the bandwidth data of each fiber channel in the region to be scheduled to obtain a plurality of channel sets, and there is a scheduling sequence between each of the channel sets; based on the scheduling sequence, the size relationship between the load data of each channel in each channel set and the second preset threshold value is compared in turn, and a plurality of channels with load data greater than or equal to the second preset threshold value are determined as the set of fiber channels to be scheduled; based on the scheduling sequence, the size relationship between the bandwidth data of each channel in the set of fiber channels to be scheduled and the bandwidth data of each channel in the region available for borrowing is judged in turn, and a plurality of channels in the region available for borrowing with bandwidth data greater than or equal to the bandwidth data of each channel in the set of fiber channels to be scheduled are determined as the set of fiber channels available for borrowing, and the matching scheme is determined.

[0066] In this embodiment, based on the traffic fluctuation curve of each operation area in the time interval, the operation area grouping data is obtained, that is, the operation area division data is obtained from the tidal operation, for example, the business district has high peak in the daytime and low valley at night, and the residential area has low traffic in the daytime and high traffic at night, the business district and the residential area can be determined as a group of operation areas, in the case of determining the business district as the to-be-scheduled area in the daytime, the residential area is determined as the borrowable area, in the heat map, during the morning peak period 08:00-10:00, the central area X=10-12 is divided into a high-load area, and the edge area X=15-17 is a low-load area. Further, for the high-load area, according to the bandwidth data of each channel in the channel set in the time interval, each channel is clustered, and the scheduling priority between the channels, that is, the scheduling sequence, is determined. Based on the coordinate position of the to-be-scheduled area, the optical fiber channel is matched, first, the optical fiber channel in the network topology needs to be associated with the specific coordinates, for example, assuming that in a certain city optical fiber network, the coordinates X=10, Y=20 correspond to a channel A, and the bandwidth is 100 Gbps, while X=11, Y=21 correspond to channel B, and the bandwidth is 80 Gbps. This matching depends on the pre-established coordinate and resource database to ensure that the position corresponds to the actual channel one by one. For example, the channel set includes all channels in X=10-12, Y=20-22, and the total bandwidth is 300 Gbps. For example, the channel set includes three channels A, B and C, and the bandwidth utilization rates are 85%, 75% and 40% respectively. Through K-means clustering, the channels are grouped, and A and B channels with 85% and 75% are grouped into a high-bandwidth group, and C channel with 40% is a low-bandwidth group. This grouping clearly divides the priority. After obtaining the priority order, the dynamic changes of the hotspot migration are predicted combined with real-time data. For example, the utilization rate of A channel continues to rise after 09:00, and the utilization rate of B channel is stable at 75%, and it can be predicted that A channel is the main scheduling target. Preferably, in the resource scheduling, A channel is set as the primary scheduling object, and B channel is used as the backup, which enhances the flexibility of scheduling. The load data of each channel in the channel set can be collected by the real-time monitoring system every 5 minutes, if the current load of A channel is 85 Gbps, the load of B channel is 60 Gbps, and the load of C channel is 20 Gbps, the data list clearly lists the status of each channel. If the preset threshold is 70 Gbps, through conditional judgment, A channel is selected as the to-be-scheduled optical fiber channel. This screening ensures that only overloaded resources are concerned, and the targeting of scheduling is improved. The resource matching process is performed between each optical fiber channel of the schedulable area and each optical fiber channel in the to-be-scheduled optical fiber channel set. For example, the standby resource matched with A channel is extracted from each optical fiber channel of the schedulable area. Assuming that the bandwidth of D channel in the schedulable area is 40 Gbps, it can be used as a matching item, and it is determined that the borrowable optical fiber channel set includes D channel. Preferably, combined with the operation area grouping data, it is determined that the high-bandwidth group where A channel is located has the highest priority, and the matching scheme that D channel supports A channel is confirmed.According to the matching scheme, the channel residual resource data is determined, and the residual resources are classified by using K-means clustering. For example, the load of channel B is reduced to 50 Gbps, and the load of channel C is still 20 Gbps. The clustering result classifies B as a medium load class and C as a low load class. This classification optimizes the resource distribution state and provides a reference for the next scheduling. If the tide operation shows that the traffic migrates to X = 11, the set of fiber channels to be scheduled can be expanded to the B channel. When allocating, the 30 Gbps bandwidth of the E channel in the set of borrowable fiber channels is preferentially borrowed. This flexible adjustment adapts to the traffic changes and ensures the overall stability of the network. The matching scheme combined with historical time series data can predict the future hotspot migration time node. For example, by analyzing the data of the past 30 days, the hotspot migration at 09:00 is particularly obvious every Monday, and it can be predicted that the same rule will be maintained next Monday. In the long-term planning, 08:50-09:40 is set as the key period.

[0067] S102, based on the user behavior data and wavelength usage data of the to-be-scheduled region in the time interval, determine a wavelength sequence, and based on the wavelength sequence and the matching scheme, determine a first wiring scheme between the set of to-be-scheduled fiber channels and the set of borrowable fiber channels.

[0068] In this embodiment, the time interval 20:00-21:00 of the to-be-scheduled region is taken as an example. The evening traffic data of the residential area increases sharply. By analyzing the traffic surge period, the user behavior characteristics are extracted to obtain the user behavior data. It can be understood that the evening is usually the peak period of residents using the network. Data collection needs to cover multiple time points to reflect traffic changes. For example, assuming that the traffic data is collected every hour between 18:00-23:00 in a certain residential area, it is found that the traffic increases to 500 Gbps during 20:00-21:00, while the average traffic during other periods is 200 Gbps. This surge may be related to users watching videos or playing games after work. The wavelength usage data is extracted from the user behavior data, and the wavelength preference distribution is determined by statistical analysis to obtain a preference sorting list. By comparing the preference sorting list with the preset threshold, if the preference value exceeds the threshold, the high-priority wavelengths are selected to obtain the wavelength sequence. Based on each channel of the set of borrowable fiber channels, the wavelengths are matched to determine the resource allocation set after matching. The channel state data is extracted from the set of to-be-scheduled fiber channels, and the correspondence between the channels and the resources is determined by matching the resource allocation set to obtain the first wiring scheme.

[0069] As an example of an embodiment of the application, the wavelength sequence is determined based on the user behavior data and wavelength usage data of the region to be scheduled within the time interval, and the first wiring scheme between the set of fiber channel to be scheduled and the set of fiber channel to be borrowed is determined based on the wavelength sequence and the matching scheme. Specifically, the user behavior data is obtained by analyzing the traffic data within the time interval, wherein the user behavior data includes multiple types of user behavior features and wavelength usage frequency corresponding to each wavelength, and each type of user behavior feature corresponds to multiple wavelengths. For multiple first wavelengths with wavelength usage frequency greater than or equal to a first preset threshold, the first wavelength set corresponding to the wavelength sequence is obtained by sorting the first wavelengths according to the wavelength usage frequency. Based on the wavelength sequence, the bandwidth data of each first wavelength in the first wavelength set is matched with the bandwidth data of each channel in the set of fiber channel to be borrowed in turn, and the first wavelength that matches successfully is assigned to the corresponding channel to obtain the first wiring scheme.

[0070] In the embodiment, the user behavior data is obtained by analyzing the packet type and access target of the flow data, for example, the analysis shows that the video flow accounts for 70% and the game flow accounts for 20%, indicating that the user prefers entertainment applications, and the user behavior data therefore contains the "high entertainment demand" feature. The wavelength usage rate of the wavelength division multiplexing equipment of the fiber network is recorded, the wavelength λ1 carries the video flow and the usage rate is 80%, while the wavelength λ2 carries the ordinary browsing flow and the usage rate is only 30%. Since the network activity of the user at different time periods will affect the usage frequency of the wavelength, the wavelength usage data can be collected based on the user behavior data, for example, the usage data of each wavelength in a week is collected in a residential area, it is found that the wavelength λ1 is called 100 times per day, the wavelength λ2 is called 50 times per day, and the wavelength λ3 is called only 20 times per day. Statistical features are extracted from the wavelength frequency distribution, including the average number of calls and the peak number of calls of each wavelength, for example, the average number of calls of the wavelength λ1 is 80 times and the peak number of calls is 120 times, the average number of calls of the wavelength λ2 is 40 times and the peak number of calls is 60 times, and therefore the priority of the wavelength λ1 is higher than that of the wavelength λ2. It is judged whether the wavelength usage frequency corresponding to each wavelength is greater than or equal to a preset threshold, for example, the threshold is set to 70 times per day, then the wavelength λ1 exceeds the threshold, and the wavelengths λ2 and λ3 do not meet the threshold, and therefore the first wavelength set only contains the wavelength λ1. For each wavelength in the first wavelength set, clustering analysis can be performed according to the usage time period and the flow type to determine the wavelength preference feature, for example, the usage rate of the wavelength λ1 is higher during the evening flow peak period and it carries more video flow, and the preference feature shows "high entertainment load", and the wavelength sequence places the wavelength λ1 at the first position. Based on the wavelength sequence, the bandwidth data of each first wavelength in the first wavelength set is matched with the bandwidth data of each channel in the set of borrowable fiber channels in turn, for example, the bandwidth of the channel A in the set of borrowable fiber channels is 100 Gbps and the bandwidth of the channel B is 50 Gbps, which is sufficient to support high flow demand, and therefore the wavelength λ1 is successfully matched with the channel A, the wavelength λ1 is carried by the channel A, and the first wiring scheme is obtained.

[0071] As an example of an embodiment of the application, the wavelength sequence is determined based on the user behavior data and the wavelength usage data of the to-be-scheduled area in the time interval, and the first wiring scheme between the set of to-be-scheduled fiber channels and the set of borrowable fiber channels is determined based on the wavelength sequence and the matching scheme, specifically: real-time flow data is obtained, if the real-time usage rate of the second wavelength continuously increases and the continuous time is greater than or equal to a preset time threshold, the second wavelength is added to the first wavelength set to obtain a second wavelength sequence and a second wavelength set, wherein the second wavelength refers to a wavelength with a wavelength usage frequency less than a first preset threshold; based on the second wavelength sequence, the bandwidth data of each second wavelength in the second wavelength set is matched with the bandwidth data of the channels in the set of borrowable fiber channels that are not successfully matched to obtain an updated first wiring scheme.

[0072] In the embodiment, if the load of λ2 increases, the priority is slightly improved, the wavelength sequence λ1 is still the first, λ2 is the second, and λ2 is increased to the first wavelength set. It can be understood that this adjustment ensures that the resource allocation closely follows the changes in user demand, optimizing network performance. If the evening traffic continues to concentrate on λ3, λ3 can be expanded to the first wavelength set. The K-means clustering is used to classify the unmatched fiber channels, and λ2 is matched with the unmatched fiber channels, including the remaining 30Gbps bandwidth of the C channel, to obtain the wiring scheme of matching λ2 to the edge area C channel, and the wiring scheme of retaining the A channel to carry λ1. This flexibility adapts to the fluctuations in user behavior, ensuring the efficiency of resource allocation. If the user behavior characteristics show that the user prefers low-latency game traffic, while λ1 is video, and the trends are inconsistent, the priority sequence can be optimized through logical adjustment. For example, λ4 is introduced, which has a frequency of 60 times a day but lower delay, and the adjusted order is λ4 first, λ1 second, to obtain the adjusted wavelength sequence. The bandwidth demand of each wavelength in the wavelength sequence is obtained, the channels without wiring schemes are obtained from the set of available fiber channels, and the resources are re-allocated using the greedy algorithm. For example, λ4 requires 50Gbps bandwidth, λ1 requires 80Gbps, and the current resources have 90Gbps remaining in channel A and 40Gbps in channel B, of which channel B is not occupied. When re-allocating, λ1 is matched with channel A first because its bandwidth is sufficient, and λ4 is matched with channel B. The optimized allocation set is A-λ1, B-λ4. This method ensures fast allocation of high-frequency wavelengths and improves resource utilization. The correspondence between wavelength frequency and allocation set is determined by the optimized allocation set. λ1 has a high frequency and is allocated to a large bandwidth channel A, and λ4 has a lower frequency but is delay-sensitive, and is allocated to B. The logic is self-consistent, and the final adjustment is based on "frequency priority + demand matching". For example, if the evening traffic suddenly increases, the frequency of λ1 increases to 150 times, and channel A can still support it, while the frequency of λ4 remains stable, and the allocation does not need to be adjusted. This method is flexible and adaptive to changes, ensuring network stability and user experience.

[0073] S103, iteratively updating the wavelength sequence according to the load balancing index and the matching index of the current iteration, stopping iteration when the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, and outputting a second wiring scheme; wherein, in each iteration, updating the first wiring scheme according to the wavelength sequence updated in the current iteration, and calculating the load balancing index of each fiber channel to be scheduled in the updated first wiring scheme; the matching index is the index between the wavelength sequence of the current iteration and the traffic fluctuation curve; the second wiring scheme is used to configure the optical cable wiring relationship between the to-be-scheduled area and the available area.

[0074] In the embodiment, the traffic change data is analyzed by the reordering view algorithm, the load distribution state of each channel is calculated, and the load balancing index is obtained. In each iteration process, the load balancing index is compared with the balancing threshold, and the matching index is compared with the matching threshold. If the iteration stop condition is not met, the wavelength sequence is iteratively updated, the updated wavelength sequence is matched with the channel load data to update the first wiring scheme, then the load balancing index and the matching index of each channel are recalculated based on the updated first wiring scheme, and the next iteration is performed until the iteration stop condition is met, and the wiring scheme used in the current iteration, i.e., the second wiring scheme, is output. For example, in a certain city residential network, wavelength data for one day is collected, and it is found that λ1 carries the highest traffic and λ3 carries the lowest traffic. The view algorithm sorts according to the traffic size, and the preliminary wavelength sequence is λ1, λ2, and λ3. It should be noted that this sorting reflects the initial priority distribution of the data, but does not consider load balancing. For the first wiring scheme, for example, channel X is associated with λ1, the traffic is 500 Gbps, channel Y is associated with λ2, the traffic is 200 Gbps, and channel Z is associated with λ3, the traffic is 50 Gbps. The load balancing index is calculated by analyzing the traffic data of each channel. If the balancing index is initially set to 0.8, it indicates that the load distribution difference is large. The matching degree is calculated according to the traffic change trend. For example, the traffic of X channel increases to 600 Gbps and the traffic of Y channel increases to 240 Gbps due to the increase of 20% of the traffic in the evening, and the matching degree is 85%. If the balancing threshold is set to 0.6 and the matching threshold is set to 90%, the load balancing index is greater than the balancing threshold, and the matching degree is less than the matching threshold, and the wavelength sequence needs to be further optimized. By analyzing the traffic data, if it is found that the traffic proportion of X channel is too high, the priority of λ2 can be increased to share the traffic with λ1. After adjustment, the wavelength sequence becomes λ1, λ2, and λ3, but the priority difference is reduced. It should be noted that this adjustment is based on the real-time change of the channel data to avoid overloading of a single wavelength. Based on the updated wavelength sequence, the wiring scheme is determined again, for example, λ1 and λ2 are preferentially matched with high-traffic channels, and λ3 processes low load to ensure the overall network stability and improve resource utilization.

[0075] As an example of an embodiment of the application, the wavelength sequence is iteratively updated according to the load balancing index and the matching index of the current iteration until the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, and the iteration is stopped. Specifically, the wavelength sequence is updated according to the load balancing index of the current iteration. When the load balancing index is less than or equal to the balancing threshold, it is determined whether the matching index is greater than or equal to the matching threshold. If yes, the iteration is stopped. If no, the load balancing index is updated based on the matching index, the wavelength sequence is iteratively updated based on the updated load balancing index, and the iteration is stopped when the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold.

[0076] In the embodiment, the load balancing index can be updated by matching degree, for example, the index adjustment value of channel X is set to +0.05 and that of channel Y is +0.03, after updating, the balancing index is reduced to 0.7, and the load distribution is more uniform. This method can quickly respond to traffic fluctuations and improve resource allocation efficiency. Based on the index adjustment value, the wavelength sequence is reordered, for example, the priority of λ2 is slightly increased, and the sequence is optimized to λ1, λ2, λ3, but the internal weight adjustment is 1.0, 0.9, 0.5. The optimized scheme set contains multiple combinations, for example, λ1 is allocated to channel X, and λ2 is allocated to channels Y and Z. This diversity facilitates coping with different time period demands. When obtaining the final distribution state for the scheme set, for example, the load of channel X is reduced to 450 Gbps, the load of channel Y is increased to 250 Gbps, and the load of channel Z is 70 Gbps. Specifically, the channel without allocated wavelength can be used as a standby resource to enhance flexibility.

[0077] As an example of an embodiment of the application, the optical cable wiring relationship configuration method further comprises: according to a first mapping rule, mapping the initial load data and the initial wavelength data of each channel in each of the to-be-scheduled optical fiber channel set in the initial state to generate a first index map; based on the initial load data and the real-time load data of each channel in each of the to-be-scheduled optical fiber channel set, calculating a load fluctuation value, if the load fluctuation value is greater than or equal to a fifth preset threshold, updating the second wiring scheme until the load fluctuation value is less than the fifth preset threshold, obtaining the target load data and the target wavelength data of each channel in the to-be-scheduled optical fiber channel; according to a second mapping rule, remapping the target load data and the target wavelength data to generate a second index map; combining the user visualization demand and the second index map to generate a target configuration image and perform image rendering, wherein the target configuration image is used to display the updated second wiring scheme.

[0078] In the embodiment, the data is converted into an index chart by using a preset mapping rule. Specifically, the load value can be mapped as the height of the column chart, and the wavelength is taken as the horizontal axis to generate a preliminary visual distribution. It should be noted that the chart intuitively reflects the resource occupation of each channel, which is convenient for subsequent analysis. The distribution characteristics are obtained from the index chart. If the load peak of channel X is obviously higher than that of channel Y, the distribution characteristics show that the resources are concentrated in a specific wavelength. Matching is performed for the borrowing process in dynamic scheduling. For example, part of the resources of channel Y can be borrowed to channel X. In the initial state, the resource utilization rate is 60% for channel X and 40% for channel Y. The fluctuation range of the change trend is calculated according to the initial state of resource utilization. For example, the load change in a period of time is analyzed, and it is found that the fluctuation range of channel X is ± 50 Gbps, and the fluctuation range of channel Y is ± 20 Gbps. The quantitative value of the scheduling result is 0.8. If the quantitative value of the change trend exceeds the preset threshold value, the threshold value is 0.7, the wiring relationship needs to be adjusted, and the borrowing frequency can be increased or the wavelength priority can be adjusted. When the data mapping method is associated with the interface for the updated wiring scheme, specifically, the new data can be remapped into a line chart to generate an adjusted index chart. The chart can more clearly show the change trend of the load over time. The output format of the configuration graph is determined through the adjusted index chart. For example, if the user needs to focus on real-time performance, a dynamic curve chart can be selected as the final output, and the matching scheme of wavelength allocation and resource utilization is determined as λ4 continues to be allocated to channel X, and λ5 is optimized to carry more load of channel Y. Key features are extracted from the matching scheme. For example, the load balancing degree is improved to 0.65, and in combination with the change trend condition, the load peak of channel X tends to be flat. The final configuration graph output is in the form of a dashboard, which intuitively displays the state of each channel.

[0079] It can be understood that this method provides a more flexible basis for resource scheduling by combining visualization and dynamic adjustment. Preferably, when the load suddenly increases during the peak period, the borrowing process can quickly respond to ensure more reasonable resource allocation.

[0080] As shown in Figure 2 on the basis of the above-mentioned method embodiment, a corresponding system embodiment is provided;

[0081] An embodiment of the present application provides a cable wiring relationship configuration system 200, comprising a channel matching module 201, a wavelength allocation module 202 and a configuration module 203.

[0082] The channel matching module 201 is configured to determine a time interval of dynamic scheduling of the fiber channel based on the traffic fluctuation curve, determine a to-be-scheduled area and a borrowable area of the time interval, determine, in the to-be-scheduled area, a plurality of fiber channels whose first load data satisfy a scheduling condition as a to-be-scheduled fiber channel set, determine, in the borrowable area, a plurality of fiber channels whose bandwidth data satisfy a borrowing condition as a borrowable fiber channel set, and determine a matching scheme between the to-be-scheduled fiber channel set and the borrowable fiber channel set.

[0083] The wavelength allocation module 202 is configured to determine a wavelength sequence based on user behavior data and wavelength usage data of the to-be-scheduled area in the time interval, and determine a first wiring scheme between the to-be-scheduled fiber channel set and the borrowable fiber channel set based on the wavelength sequence and the matching scheme.

[0084] The configuration module 203 is configured to iteratively update the wavelength sequence according to a load balancing index and a matching index of a current iteration until the load balancing index is less than or equal to an equilibrium threshold and the matching index is greater than or equal to a matching threshold, stop the iteration, and output a second wiring scheme; wherein, in each iteration, the first wiring scheme is updated according to the wavelength sequence updated in the current iteration, and a load balancing index of each to-be-scheduled fiber channel in the updated first wiring scheme is calculated; the matching index is an index between the wavelength sequence of the current iteration and the traffic fluctuation curve; and the second wiring scheme is used to configure the optical cable wiring relationship of the to-be-scheduled area and the borrowable area.

[0085] It can be understood that the above system embodiment is corresponding to the method embodiment of the present application, and can realize the optical cable wiring relationship configuration method provided by any one of the above method embodiments.

[0086] It should be noted that the system embodiments described above are only schematic, and part or all of the modules can be selected to achieve the purpose of the embodiment. In addition, in the system embodiment provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which can be realized as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0087] On the basis of the above embodiment of the optical cable wiring relationship configuration method, another embodiment of the present application provides a terminal device, which comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the optical cable wiring relationship configuration method of any one of the embodiments of the present application is realized.

[0088] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more module elements can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device.

[0089] The terminal device can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing devices. The terminal device can include, but is not limited to, a processor and a memory.

[0090] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and connects all parts of the terminal device through various interfaces and lines.

[0091] On the basis of the above-mentioned method embodiment, another embodiment of the present application provides a computer readable storage medium, including a stored computer program, wherein when the computer program runs, the device where the computer readable storage medium is located executes the optical cable wiring relationship matching method described in any one of the above-mentioned method embodiments of the present application.

[0092] The modules / units integrated in the device / terminal equipment, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0093] The above is the preferred embodiment of the present application. It should be pointed out that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which are also considered within the scope of protection of the present application.

Claims

1. A method for configuring optical cable wiring relationships, characterized in that, include: The time interval for dynamic scheduling of fiber optic channels is determined based on the flow fluctuation curve, and the area to be scheduled and the area that can be borrowed within the time interval are determined. Within the area to be scheduled, multiple fiber optic channels whose first load data meets the scheduling conditions are identified as the set of fiber optic channels to be scheduled; within the area that can be borrowed, multiple fiber optic channels whose bandwidth data meets the borrowing conditions are identified as the set of fiber optic channels that can be borrowed. And determine the matching scheme between the set of available fiber channels and the set of fiber channels to be scheduled; Based on user behavior data and wavelength usage data of the area to be scheduled within the time interval, a wavelength sequence is determined, and based on the wavelength sequence and the matching scheme, a first wiring scheme is determined between the set of fiber channels to be scheduled and the set of fiber channels available for borrowing. The wavelength sequence is iteratively updated based on the load balancing index and matching index of the current iteration until the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold. Then the iteration stops and a second wiring scheme is output. In each iteration, the first wiring scheme is updated based on the wavelength sequence updated in the current iteration, and the load balancing index of each fiber channel to be scheduled in the updated first wiring scheme is calculated. The matching index is the index between the wavelength sequence of the current iteration and the flow fluctuation curve; the second wiring scheme is used to configure the optical cable wiring relationship between the area to be scheduled and the area that can be borrowed.

2. The optical cable wiring configuration method as described in claim 1, characterized in that, The process involves determining a wavelength sequence based on user behavior data and wavelength usage data of the area to be scheduled within the time interval, and then determining a first wiring scheme between the set of fiber channels to be scheduled and the set of available fiber channels based on the wavelength sequence and the matching scheme. Specifically: The traffic data within the time interval is analyzed to obtain user behavior data, which includes multiple types of user behavior characteristics and wavelength usage frequencies corresponding to each wavelength. Each type of user behavior characteristic corresponds to multiple wavelengths. Multiple first wavelengths with a wavelength usage frequency greater than or equal to a first preset threshold are sorted according to their wavelength usage frequency to obtain the first wavelength set corresponding to the wavelength sequence; Based on the wavelength sequence, the bandwidth data of each first wavelength in the first wavelength set is matched with the bandwidth data of each channel in the set of adjustable fiber optic channels in turn, and the first wavelength that is successfully matched is assigned to the corresponding channel to obtain the first wiring scheme.

3. The optical cable wiring configuration method as described in claim 2, characterized in that, The process involves determining a wavelength sequence based on user behavior data and wavelength usage data of the area to be scheduled within the time interval, and then determining a first wiring scheme between the set of fiber channels to be scheduled and the set of available fiber channels based on the wavelength sequence and the matching scheme. Specifically: If the real-time utilization rate of the second wavelength continues to rise and the duration is greater than or equal to a preset time threshold, the second wavelength is added to the first wavelength set to obtain a second wavelength sequence and a second wavelength set. The second wavelength refers to the wavelength whose wavelength utilization frequency is less than the first preset threshold. Based on the second wavelength sequence, the bandwidth data of each second wavelength in the second wavelength set is sequentially matched with the bandwidth data of the unmatched channels in the set of available fiber optic channels to obtain the updated first wiring scheme.

4. The optical cable wiring configuration method as described in claim 1, characterized in that, Within the area to be scheduled, multiple fiber optic channels whose first load data meets the scheduling conditions are identified as a set of fiber optic channels to be scheduled; within the area that can be borrowed, multiple fiber optic channels whose bandwidth data meets the borrowing conditions are identified as a set of fiber optic channels that can be borrowed; and a matching scheme is determined between the set of fiber optic channels that can be borrowed and the set of fiber optic channels to be scheduled, specifically as follows: Analyze the traffic fluctuation curves corresponding to each operation area to obtain operation area grouping data. Each operation area group includes the area to be scheduled and the area to be borrowed corresponding to the area to be scheduled. Based on the bandwidth data of each fiber channel in the area to be scheduled, the fiber channels in the set of fiber channels to be scheduled are clustered to obtain multiple channel sets, and there is a scheduling sequence between each channel set. Based on the scheduling sequence, the load data of each channel in each channel set is compared with the second preset threshold in turn, and multiple channels with load data greater than or equal to the second preset threshold are determined as the set of optical fiber channels to be scheduled. Based on the scheduling sequence, the bandwidth data of each channel in the set of fiber channels to be scheduled is sequentially determined to be related to the bandwidth data of each channel in the available area. Multiple channels in the available area whose bandwidth data is greater than or equal to the bandwidth data of each channel in the set of fiber channels to be scheduled are identified as the set of available fiber channels, and the matching scheme is determined.

5. The optical cable wiring configuration method as described in claim 1, characterized in that, The process of determining the time interval for dynamic scheduling of fiber optic channels based on the flow fluctuation curve, and determining the area to be scheduled and the area available for borrowing within the time interval, specifically involves: The initial bandwidth data of all channels is obtained, and the initial bandwidth data is cleaned and converted to obtain bandwidth data. The bandwidth data is then analyzed by a sliding window to obtain the traffic fluctuation curve. Identify multiple traffic maxima and multiple traffic minima of the traffic fluctuation curve, and perform time series analysis on the distribution characteristics when switching between each traffic maxima and traffic minima to obtain the first time node and the second time node corresponding to the hotspot migration. Calculate the difference in bandwidth data between the first time node and the second time node to obtain an initial time interval. When the difference is greater than or equal to a third preset threshold, adjust the initial time interval using linear interpolation. Within the time interval, a heatmap is generated based on multiple acquired scheduling requests, wherein the bandwidth data is identified by color in the heatmap; The initial region is determined based on the coordinate position corresponding to the maximum bandwidth data in the heat map. When the bandwidth data of the initial region exceeds the fourth preset threshold, the initial region is adjusted by linear interpolation to obtain the region to be scheduled.

6. The optical cable wiring configuration method as described in claim 1, characterized in that, The process involves iteratively updating the wavelength sequence based on the load balancing index and matching index of the current iteration until the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, at which point the iteration stops. Specifically: The wavelength sequence is updated based on the load balancing index of the current iteration. When the load balancing index is less than or equal to the balancing threshold, it is determined whether the matching index is greater than or equal to the matching threshold. If the threshold is met, the iteration is stopped. If the conditions are not met, the load balancing index is updated based on the matching index, and the wavelength sequence is iteratively updated based on the updated load balancing index until the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, at which point the iteration stops.

7. The optical cable wiring configuration method as described in claim 1, characterized in that, The optical cable wiring configuration method also includes: According to the first mapping rule, the initial load data and initial wavelength data of each channel in the set of optical fiber channels to be scheduled are mapped in the initial state to generate the first index map; Based on the initial load data and real-time load data of each channel in each set of optical fiber channels to be scheduled, the load fluctuation value is calculated. If the load fluctuation value is greater than or equal to the fifth preset threshold, the second wiring scheme is updated until the load fluctuation value is less than the fifth preset threshold, and the target load data and target wavelength data of each channel in the optical fiber channels to be scheduled are obtained. According to the second mapping rule, the target load data and the target wavelength data are remapped to generate a second index map; Based on the user's visualization requirements and the second indicator chart, a target configuration image is generated and rendered. The target configuration image is used to display the updated second wiring scheme.

8. A fiber optic cable distribution configuration system, characterized in that, include: Channel matching module, wavelength allocation module, and configuration module; The channel matching module is used to determine the time interval for dynamic scheduling of optical fiber channels based on the traffic fluctuation curve, and to determine the area to be scheduled and the area that can be borrowed within the time interval. Within the area to be scheduled, multiple fiber optic channels whose first load data meets the scheduling conditions are identified as the set of fiber optic channels to be scheduled; within the area that can be borrowed, multiple fiber optic channels whose bandwidth data meets the borrowing conditions are identified as the set of fiber optic channels that can be borrowed. And determine the matching scheme between the set of available fiber channels and the set of fiber channels to be scheduled; The wavelength allocation module is used to determine a wavelength sequence based on user behavior data and wavelength usage data of the area to be scheduled within the time interval, and to determine a first wiring scheme between the set of fiber channels to be scheduled and the set of fiber channels available for borrowing based on the wavelength sequence and the matching scheme. The configuration module is used to iteratively update the wavelength sequence according to the load balancing index and matching index of the current iteration until the load balancing index is less than or equal to the balancing threshold and the matching index is greater than or equal to the matching threshold, then stop the iteration and output the second wiring scheme; wherein, in each iteration, the first wiring scheme is updated according to the wavelength sequence updated in the current iteration, and the load balancing index of each optical fiber channel to be scheduled in the updated first wiring scheme is calculated. The matching index is the index between the wavelength sequence of the current iteration and the flow fluctuation curve; the second wiring scheme is used to configure the optical cable wiring relationship between the area to be scheduled and the area that can be borrowed.

9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the optical cable wiring relationship configuration method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the optical cable wiring relationship configuration method as described in any one of claims 1-7.

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