A Communication Network Optimization Method Based on Fiber Optic Sensing and the Importance of Bearer Services

Abstract

This application relates to the field of optical fiber communication network technology and discloses a communication network optimization method based on optical fiber sensing and the importance of carried services. The method includes: periodically injecting optical time-domain reflectometry (OTDR) sensing signals into all spare fiber cores; calculating the current loss and crosstalk values ​​of each spare fiber core based on the backscattered signals; monitoring and analyzing the service flows carried on the operating fiber cores; determining the current service importance level of each service flow according to a power communication service type-level mapping table; when an operating fiber core fails, selecting and removing target fiber cores from the set of available spare fiber cores in descending order of service importance level according to fiber core selection rules, forming a mapping relationship; generating and sending port switching control commands based on the mapping relationship to migrate services and updating the network routing table. This application achieves refined perception of spare resources and intelligent protection of differentiated service needs during communication network fault recovery.

Description

Technical Field

[0001] This application relates to the field of optical fiber communication network technology, specifically a communication network optimization method based on optical fiber sensing and the importance of carried services. Background Technology

[0002] In critical industries such as power and transportation, fiber optic communication networks carrying production control services (such as relay protection and safety and stability control) and management information services are the nerve center ensuring the safe operation of the system. These networks typically employ multi-core optical cables and are configured with spare fiber cores to improve reliability. However, the currently widely used network protection switching mechanisms have inherent limitations. On the one hand, spare fiber cores are often idle for extended periods, and their actual transmission performance (such as loss degradation and increased crosstalk) cannot be accurately monitored in real time. This means that in the event of a fault, services may be switched to a spare resource with an unknown or even defective status, leading to secondary interruptions or performance degradation, posing a potential threat to highly reliable services. On the other hand, existing switching strategies are mostly one-size-fits-all, meaning all services indiscriminately occupy the first available spare fiber core found. This ignores the differentiated channel quality requirements of different services, failing to guarantee that extremely important services, such as relay protection, which are highly sensitive to delay and bit error rate, always receive the optimal transmission channel. Furthermore, it is difficult to achieve optimal allocation of limited and varying spare fiber core resources.

[0003] Therefore, there is an urgent need for an intelligent network optimization method that can accurately understand the status of network physical resources and provide differentiated guarantees for different value services, so as to achieve an improvement from connectivity restoration to high-quality and guaranteed restoration. Summary of the Invention

[0004] The purpose of this application is to provide a communication network optimization method based on fiber optic sensing and the importance of carried services, so as to solve the technical problems mentioned in the background art.

[0005] To achieve the above objectives, this application discloses the following technical solution: a communication network optimization method based on fiber optic sensing and the importance of carried services, applied to an optical fiber communication network with operating fiber cores and spare fiber cores, the method comprising: Continuous sensing steps: Periodically inject optical time-domain reflectometry signals into all spare fiber cores, and calculate the current loss value and current crosstalk value of each spare fiber core based on the backscattering signal of each spare fiber core. Dynamic mapping steps: Monitor and analyze the service flows carried on the operating fiber core, and determine the current service importance level of each service flow according to the preset level mapping table associated with power communication service types; wherein, the power communication service types include at least relay protection services, safety and stability control services, dispatch automation services and management information services; Differential decision-making steps: When any operating fiber core failure is detected, the current service importance level of all affected service flows on the failed operating fiber core is obtained. Fiber core allocation operations are performed sequentially for each affected service flow in descending order of service importance level, until target fiber cores are allocated to all affected service flows, forming a mapping relationship between service flows and target fiber cores. The fiber core allocation operation includes: according to the fiber core selection rules pre-configured for the service importance level, selecting target fiber cores that meet the rules from the currently available set of spare fiber cores, and removing the target fiber core from the set of spare fiber cores. The fiber core selection rules pre-configured for high service importance levels have stricter performance thresholds for the current loss value and / or current crosstalk value of spare fiber cores than the rules pre-configured for low service importance levels. Switching and reconfiguration steps: Based on the mapping relationship between the service flow and the target fiber core, generate and send corresponding port switching control commands to the optical path switching equipment to switch each service flow to its assigned target fiber core and update the network routing table.

[0006] Optionally, in the continuous sensing step, the optical time-domain reflectometry (OTDR) signal is a phase-sensitive OTD signal; the calculation of the current crosstalk value for each spare fiber core includes: The frequency domain characteristics of the backscattered signal are analyzed, and the current crosstalk value is calculated by demodulating the specific spectral components generated by mode field coupling between adjacent fiber cores.

[0007] Optionally, in the difference decision step, the fiber core selection rule pre-configured for high business importance level is defined as the first rule. The first rule includes: selecting a fiber core with the lowest current loss value and the current crosstalk value below a first threshold from the set of spare fiber cores as the corresponding target fiber core. The fiber core selection rule pre-configured for other levels below the high business importance level is defined as the second rule. The second rule includes: selecting a fiber core from the set of spare fiber cores whose current loss value is lower than a second threshold and whose current crosstalk value is lower than a third threshold as the corresponding target fiber core; wherein, the second threshold is greater than the loss level corresponding to the first threshold.

[0008] Optionally, a policy pre-configuration step may also be included: Based on the safety zoning principle of the power production control area and the management information area, relay protection business and safety and stability control business are mapped to the highest business importance level and associated with the first rule; The scheduling automation service is mapped to the second highest service importance level, and associated with a third rule whose loss and crosstalk thresholds are between the first rule and the second rule; Map management information business to the importance level of ordinary business, and associate it with the second rule.

[0009] Optionally, between the continuous sensing step and the difference decision step, an evaluation modeling step is also included: based on the current loss value and current crosstalk value calculated by the continuous sensing step, a comprehensive quality score is calculated for each spare fiber core, the comprehensive quality score = W1×N(current loss value) + W2×N(current crosstalk value), where N(·) represents the normalization function, W1 and W2 are preset weight coefficients, satisfying W1>W2>0 and W1+W2=1; The comprehensive quality score is used in the difference decision step to select the fiber with the highest comprehensive quality score from the multiple backup fiber cores when multiple backup fiber cores that meet the conditions are selected according to the rule, in order to select the final target fiber core.

[0010] Optionally, the evaluation modeling step further includes: Based on historical input and output data, the weighting coefficients W1 and W2 are periodically calibrated to optimize the accuracy of the comprehensive quality score in characterizing the fiber core performance.

[0011] Optionally, in the dynamic mapping step, determining the current service importance level of each service flow based on a preset level mapping table associated with power communication service types includes: Deep packet inspection technology is used to identify the protocol type and destination IP address range of the service flow; The protocol type and the destination IP address range are matched with a predefined power service feature database to determine the type of power communication service to which they belong. Query the level mapping table to obtain the service importance level corresponding to the power communication service type.

[0012] Optionally, in the switching and reconfiguration step, generating and sending the corresponding port switching control command to the optical path switching device includes: generating a cross-configuration command for establishing an optical path connection as the port switching control command based on the physical port identifier of the optical cross-connect matrix corresponding to the target fiber core; The update of the network routing table includes: in the control plane, based on the mapping relationship between the service flow and the target fiber core, flooding the network with updated link status announcements through a routing protocol to synchronize the routing information of the entire network.

[0013] Optionally, after the switching and refactoring step, a verification and backtracking step is also included: Monitor the key performance indicators of each service flow on its target fiber core after the switchover; If the key performance indicators of a certain service flow continue to deteriorate and exceed the health threshold corresponding to its service importance level, the service flow will be remarked as a service to be migrated, and the difference decision step will be re-executed to select a new target fiber core. At the same time, the performance abnormality event of the original target fiber core will be marked in the fiber core status record.

[0014] Optionally, the verification and backtracking steps further include: Based on the recorded performance anomaly events, the threshold or health threshold used in the core selection rule in the differential decision-making step is dynamically adjusted.

[0015] Beneficial Effects: The communication network optimization method based on fiber optic sensing and the importance of carried services in this application can, when a fault occurs in the operating fiber core, execute a differentiated, priority-based intelligent fiber core selection and switching process based on online acquired and quantified backup fiber core performance data (loss, crosstalk) and the importance level identified in real time by the service flow. This ensures that the highest importance services (such as relay protection) can preferentially occupy the best-performing backup fiber core, thereby obtaining the highest recovery quality guarantee; while other services are reasonably allocated remaining resources under the premise of meeting their basic performance thresholds. In this way, not only is the service quality and network reliability of critical services improved in fault recovery scenarios, but also the refined and value-based scheduling of backup fiber core resources across the entire network based on their actual state is realized, thereby improving the overall resilience and intelligent operation and maintenance level of the communication network. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the communication network optimization method based on fiber optic sensing and the importance of carried services provided in this application embodiment. Detailed Implementation

[0018] To facilitate understanding of the technical solutions provided in the embodiments of this application, the background technology involved in the embodiments of this application will be described below.

[0019] In critical infrastructure sectors such as power and rail transportation, production control and operation management heavily rely on the underlying fiber optic communication network. This network acts as the system's nerve center, not only carrying daily management information but, more importantly, transmitting in real-time production control services directly related to the safety of power grid equipment and the stable operation of the system, such as relay protection and safety and stability control. These services place near-stringent requirements on the transmission latency, packet loss rate, and availability of the communication channel. For example, line differential protection typically requires end-to-end transmission latency of less than 10 milliseconds, and the channel must be absolutely reliable. To cope with physical faults such as accidental fiber optic cable breaks, existing networks generally adopt an "N+1" or "1+1" protection architecture based on multi-core fiber optic cables, configuring dedicated backup fiber cores to achieve rapid service failover and recovery in the event of a primary fiber core failure.

[0020] However, the network protection switching technologies currently widely deployed are primarily designed to restore connectivity. When faced with the aforementioned high-reliability and differentiated service assurance requirements, they are gradually revealing two deep-seated limitations: The first dimension is the black box nature of resource status: spare fiber cores are idle most of the time, and traditional operation and maintenance methods cannot continuously and accurately quantify their inherent transmission performance. Fiber loss may slowly increase due to micro-bending and aging; in multi-core fibers, crosstalk between cores may also change due to environmental stress. These performance degradations are gradual and implicit, and are difficult to detect in routine testing. This means that when a fault triggers protection switching, the network management terminal is unaware of the true health status of each spare fiber core, and may switch a critical service (such as relay protection for a 500kV line) to a spare fiber core whose actual performance has been severely degraded. This blind switching leads to an extremely high risk of secondary faults or severe performance degradation, making the spare resources set up to improve reliability themselves a potential weakness in reliability.

[0021] The second dimension is the crudeness of recovery strategies: existing automatic protection switching mechanisms typically rely on the core logic of preempting the first available resource. Regardless of whether the faulty fiber core carries millisecond-response relay protection services or minute-response data acquisition services, all services follow the same simple switching rules, competing indiscriminately for backup fiber cores. This one-size-fits-all approach completely ignores the inherent value differences and varying transmission quality requirements of different services. As a result, high-importance services may suffer additional delays or bit errors due to failing to secure the optimal channel, affecting the correctness and speed of their protection actions; while low-importance services may accidentally occupy a high-quality fiber core, causing a misallocation and waste of high-value network resources. This blind allocation of resources makes it difficult for the network to maximize its protection effectiveness when facing faults.

[0022] In summary, the core contradiction in existing technologies lies in the disconnect between the intelligent requirements of network layer switchover control and the unknowable reality of physical layer resource status; and the contradiction between the differentiated requirements of service layer assurance and the singular nature of link layer recovery strategies. Therefore, there is an urgent need in this field for a collaborative optimization method that can bridge the gap between physical layer awareness, network layer control, and service layer requirements. This method should not only acquire the real-time performance spectrum of backup fiber cores but also clearly define the intrinsic value level of service flows. This would enable the execution of state-aware and value-discriminatory intelligent recovery decisions during fault occurrence, achieving an improvement from connectivity restoration to guaranteed quality restoration. This is precisely the fundamental technical problem that the technical solution of this application aims to solve.

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application. Secondly, in this document, the term "comprising" is 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.

[0024] This embodiment provides a communication network optimization method based on fiber optic sensing and the importance of carried services, applicable to fiber optic communication networks with operating and spare fiber cores, such as... Figure 1 As shown, the method includes the following steps in sequence: Continuous sensing steps: Periodically inject optical time-domain reflectometry signals into all spare fiber cores, and calculate the current loss value and current crosstalk value of each spare fiber core based on the backscattering signal of each spare fiber core. Dynamic mapping steps: Monitor and analyze the service flows carried on the operating fiber core, and determine the current service importance level of each service flow according to the pre-set level mapping table associated with power communication service types; among which, power communication service types include at least relay protection services, safety and stability control services, dispatch automation services, and management information services; Differential decision-making steps: When any operating fiber core failure is detected, the current service importance level of all affected service flows on the failed operating fiber core is obtained. Fiber core allocation operations are performed sequentially for each affected service flow in descending order of service importance level until target fiber cores are allocated to all affected service flows, forming a mapping relationship between service flows and target fiber cores. The fiber core allocation operation includes: according to the fiber core selection rules pre-configured for the service importance level, selecting target fiber cores that meet the rules from the currently available set of spare fiber cores, and removing the target fiber core from the set of spare fiber cores; wherein, the fiber core selection rules pre-configured for high service importance levels have stricter performance thresholds for the current loss value and / or current crosstalk value of spare fiber cores than the rules pre-configured for low service importance levels. Switching and reconfiguration steps: Based on the mapping relationship between service flows and target fiber cores, generate and send corresponding port switching control commands to the optical switching equipment to switch each service flow to its assigned target fiber core and update the network routing table.

[0025] Specifically, in the continuous sensing step, an integrated or independent optical time-domain reflectometry (OTDR) test unit is controlled. This test unit, for example, can be an AQ1200 test module, which has high dynamic range and sensitivity, suitable for performance testing of long-distance optical fibers. In practical applications, other models of this test unit can also be selected; this embodiment does not limit this choice. By controlling an optical switch matrix sequentially connected to the end of each spare fiber core, a probe optical pulse of a specific pulse width (e.g., 10 nanoseconds) and wavelength is injected into the fiber core at a preset period (e.g., every 5 minutes). When the optical pulse propagates in the optical fiber, a backscattered signal is generated due to Rayleigh scattering. The receiving end acquires this signal and, by analyzing the signal intensity attenuation curve with distance (time), calculates the loss coefficient of the entire fiber core, i.e., the current loss value, typically in dB / km, using the standard principles of an optical time-domain reflectometer. Simultaneously, for multi-core optical fibers, by analyzing the additional modulation components generated by optical power coupling between adjacent operating fiber cores in the backscattered signal, the current crosstalk value, typically in dB, characterizing the isolation between fiber cores, can be calculated. This step transforms all spare fiber cores from a black box state into an evaluable resource with well-defined, quantifiable performance parameters.

[0026] In the dynamic mapping step, deep packet inspection (DIP) technology is used at the core nodes of the network to monitor the data flow in real time. The header information of the service flow packets is parsed, including source / destination IP addresses, port numbers, and specific protocol fields. A pre-defined level mapping table is stored in the configuration database. This table defines the binding relationship between the identification characteristics of different power communication service types (such as specific IP address ranges and protocol types) and their corresponding service importance levels. For example, traffic whose destination IP address belongs to the substation protection device network segment and uses the IEC 61850 GOOSE protocol is identified as "relay protection service" and mapped to the "highest" importance level; traffic using the IEC 60870-5-104 protocol and flowing to the dispatch center master station is identified as "dispatch automation service" and mapped to the "high" importance level. Through real-time matching, the system dynamically labels the current service importance level of each active service flow. This step transforms the abstract service importance into identifiable and operable tags in the network, laying the foundation for differentiated decision-making.

[0027] In the differential decision-making step, a fault alarm is triggered when optical power loss or a sudden increase in bit error rate is detected in a running fiber core via optical power monitoring. First, the identifiers and current service importance levels of all service flows on the faulty fiber core are obtained from the results of the dynamic mapping step. Then, these service flows are sorted according to their importance level, for example: "Highest" > "High" > "Normal". Next, each service flow is processed sequentially in this order. For the currently pending service flow, the fiber core selection rule pre-associated with the service importance level is invoked. This rule is a set of logical judgment conditions, mainly setting performance thresholds for the standby fiber core status data (current loss value, current crosstalk value) obtained from the continuous sensing step. All fiber cores that meet the rule conditions are selected from the currently available standby fiber core pool, and then a unique fiber core is determined as the target fiber core based on the specific logic of the rule (e.g., selecting the one with the lowest loss). Once selected, the identifier of the target fiber core is removed from the available standby fiber core pool to prevent it from being duplicated by subsequent priority services, and it is bound to the current service flow ID and recorded in the service flow and target fiber core mapping table. This process repeats until all affected service flows are allocated to the target fiber core. This step is the core of this method, utilizing quantified fiber core status and service importance to achieve orderly and optimal resource allocation, ensuring that critical services receive high-quality channels.

[0028] In the handover and reconfiguration step, the final generated service flow-to-target fiber core mapping table is converted into device-executable instructions. For optical layer handover, based on the physical port corresponding to the target fiber core, standard TL1 or NETCONF format cross-connect configuration commands are generated and sent to the optical cross-connect device to control its internal matrix to switch the optical signal of the service flow from the faulty port to the target backup fiber core port. For electrical or IP layer handover, through control plane protocols, such as GMPLS or SDN-based controllers, the new link connection relationship (i.e., the binding of service flows to the new fiber core) is flooded to the entire network in the form of updated link-state advertisements via routing protocols such as OSPF or IS-IS, causing all routers to update their routing tables, thereby guiding the IP packets of the service flow to the new physical path. This step completes the closed loop from intelligent decision-making to physical network reconfiguration, enabling the service flow to resume transmission on the new, preferred fiber core.

[0029] Based on the above, through the collaborative work of the four steps, the continuous perception step breaks the black box of resource status, providing accurate data for decision-making; the dynamic mapping step identifies differences in business value; the difference decision-making step utilizes the information from the first two steps to execute intelligent recovery with state awareness and value differentiation, replacing the extensive one-size-fits-all approach; and finally, high-quality recovery is achieved through the switching and reconstruction step. This ensures that the most important services can obtain the best-performing backup fiber cores first, thereby achieving the highest recovery quality assurance, while simultaneously realizing refined and value-based scheduling of backup fiber core resources across the entire network.

[0030] To more accurately sense microscopic changes in the spare fiber cores, especially performance degradation caused by weak environmental disturbances, as an optional implementation method in this embodiment, the optical time-domain reflectometry (OTDR) signal is a phase-sensitive OTD signal in the continuous sensing step; the calculation of the current crosstalk value for each spare fiber core includes: By analyzing the frequency domain characteristics of the backscattered signal and demodulating the specific spectral components generated by mode field coupling between adjacent fiber cores, the current crosstalk value is calculated.

[0031] Specifically, this method employs a detection unit based on phase-sensitive optical time-domain reflectometry (OTDR). This unit emits highly coherent probe light pulses and detects the phase change of the backscattered Rayleigh signal with extreme precision. Unlike ordinary optical time-domain reflectometers that only analyze light intensity, phase-sensitive OTDR is extremely sensitive to micro-vibrations, stress, and temperature changes in the optical fiber, and can detect even weaker signal distortions. When calculating the current crosstalk value, the backscattered signal is processed, analyzing not only its time-domain intensity but also performing a Fast Fourier Transform (FFT) to analyze it in the frequency domain. When an adjacent fiber core (especially a running fiber core) transmits an optical signal, a specific frequency modulation component is introduced into the backscattered signal of the spare fiber core through mode field coupling. The frequency of this component is related to the baud rate of the signal from the adjacent fiber core. The power of this specific spectral component can be extracted using a bandpass filter or a peak detection algorithm. Assume the main signal power is (This can be estimated using known transmit power and baseline loss), then the current crosstalk value... (In dB) can be obtained through the formula The calculations show that this method, compared to relying solely on time-domain waveform analysis, can more sensitively and specifically quantify the crosstalk level between fiber cores.

[0032] Based on the above, by utilizing the high sensitivity of a phase-sensitive optical time-domain reflectometer and combining it with frequency domain analysis, components caused by crosstalk can be accurately separated from complex backscattered signals. This allows for earlier and more accurate detection of potential performance degradation in backup fiber cores due to crosstalk, providing more reliable and detailed current crosstalk data for differential decision-making steps. This further reduces the risk of switching services to fiber cores with potential interference and improves the transmission quality of services after recovery.

[0033] To ensure the clarity and operability of the performance threshold in the differential decision-making process and to avoid ambiguity in the rules, as an optional implementation method in this embodiment, the fiber core selection rule pre-configured for high business importance level is defined as the first rule in the differential decision-making process. The first rule includes: selecting a fiber core with the lowest current loss value and the current crosstalk value below the first threshold from the set of spare fiber cores as the corresponding target fiber core. The fiber core selection rule pre-configured for other levels below the high business importance level is defined as the second rule. The second rule includes: selecting a fiber core from the spare fiber core set whose current loss value is lower than the second threshold and whose current crosstalk value is lower than the third threshold as the corresponding target fiber core; wherein, the second threshold is greater than the loss level corresponding to the first threshold.

[0034] Specifically, in this method, the rules are explicitly encoded. The first rule applies to the highest business importance level (e.g., "highest"), and its logic is as follows: First, select all current crosstalk values ​​from the currently available spare fiber cores. Less than the preset first threshold Fiber cores with a loss of -40dB (e.g., -40dB) form candidate set A; then, the current loss value is selected from candidate set A. The lowest (i.e., best performing) fiber core is selected; if candidate set A is empty, an alarm is triggered, indicating that there are no qualified backup resources. The second rule applies to lower levels (e.g., "high" or "normal"), and its logic is: from the available set, all current loss values ​​are selected. Less than the second threshold (e.g., 0.25 dB / km) and the current crosstalk value Less than the third threshold Fiber cores with a loss of -35dB (e.g., -35dB) constitute candidate set B. Since the second rule requires the loss to be "below a threshold" rather than "lowest," candidate set B may contain multiple fiber cores. In this case, the fiber with the lowest loss value can be selected by default, or a random fiber can be selected as the target fiber core. The key point is the second threshold. The loss level is numerically greater than the minimum loss value sought by the first rule. In other words, the first rule aims to find a fiber core with extremely low loss, while the second rule only requires that the loss be good enough (below a more lenient threshold).

[0035] Based on the above, by setting specific, tiered numerical thresholds (first threshold, second threshold, and third threshold), abstract rules are transformed into programmable and executable logical judgments. This allows the highest-priority services to lock in high-quality fiber cores with low loss and low crosstalk, while lower-priority services are allocated resources while meeting a relatively lenient but still acceptable dual threshold. This clearly and reliably achieves differentiated protection and avoids arbitrariness in resource allocation.

[0036] To achieve accurate mapping from service type to importance level in the dynamic mapping step, and to pre-configure callable fiber core selection rules for the difference decision step, as a further optional implementation of this embodiment, the method also includes a strategy pre-configuration step: Based on the safety zoning principle of the power production control area and the management information area, relay protection business and safety and stability control business are mapped to the highest business importance level and associated with the first rule; Map the scheduling automation business to the second highest business importance level, and associate it with a third rule whose loss and crosstalk thresholds are between the first rule and the second rule; Map management information business to the importance level of ordinary business, and associate it with the second rule.

[0037] Specifically, policy pre-configuration is performed before method execution or during the initialization phase. The configuration process strictly adheres to the mandatory provisions of power system security zoning: the production control area (including real-time control sub-areas and non-control production sub-areas) has the highest business security requirements. Therefore, relay protection and safety and stability control services originating from the real-time control sub-area are mapped to the "highest" business importance level and bound to the aforementioned, most stringent first rule. Dispatch automation services (such as SCADA) originating from the non-control production sub-areas are mapped to the "second highest" business importance level. Considering that their importance, while lower than real-time control services, is still higher than management information services, a third rule is specifically defined for them. This third rule is similar in form to the second rule, but its loss threshold... and crosstalk threshold The value is set at the threshold of the first rule (aiming for the lowest possible loss) and the threshold of the second rule ( , Between, for example dB / km, Finally, management information business items belonging to the management information zone are mapped to the "normal" business importance level and associated with the relatively lenient second rule. These mappings and associations are persistently stored in the form of database tables or configuration files.

[0038] Based on the above, industry safety standards (power safety zoning) are directly translated into configuration strategies for the technical system, ensuring a close integration of the technical solution with business security requirements. This provides a clear, compliant, and flexibly adjustable strategic basis for the two steps of dynamic mapping and differential decision-making, guaranteeing that the entire optimization method is not only technically feasible but also meets the high safety standards of the power industry, enhancing the practicality and creativity of this method.

[0039] After obtaining the original state parameters (current loss value, current crosstalk value) in the continuous sensing step, directly using them for decision rule judgment may face the complexity of multi-dimensional comparison. In order to evaluate the overall quality of a fiber core more scientifically and comprehensively, and to provide a more refined decision basis when multiple choices appear in rule matching, as a further optional implementation method of this embodiment, an evaluation modeling step is also included between the continuous sensing step and the difference decision step: based on the current loss value and current crosstalk value calculated by the continuous sensing step, a comprehensive quality score is calculated for each spare fiber core, and the comprehensive quality score = W1×N(current loss value) + W2×N(current crosstalk value), where N(·) represents the normalization function, and W1 and W2 are preset weight coefficients that satisfy W1>W2>0 and W1+W2=1; The comprehensive quality score is used when executing the first or second rule in the difference decision-making step. When multiple qualified spare fiber cores are selected according to the rule, the one with the highest comprehensive quality score is selected as the final target fiber core.

[0040] Specifically, the evaluation modeling step receives the current loss value for each fiber core from the continuous sensing step. and current crosstalk value First, normalization is performed. Since both loss and crosstalk are indicators where "smaller values ​​are better," the following maximum-minimum normalization method can be used: , .in, , , , This refers to the maximum and minimum values ​​of this parameter among all currently available spare fiber cores, or a fixed reference range set based on historical data and engineering experience. After normalization, and The value falls within the range [0,1], and a larger value indicates better performance for that item. Then, the overall quality score is calculated. : Weighting coefficients and It is preset, for example, based on the analysis of historical network fault data, and set. , The impact of fiber loss performance on optical fiber transmission quality is weighted higher than that of crosstalk. Each fiber core receives one... A higher score indicates better overall quality. In the difference decision-making step, when applying the first rule, if multiple fiber cores have current loss values ​​within the measurement accuracy error range (e.g., ±0.01 dB / km) and are all considered "lowest," then among these fiber cores, the one with the highest loss value is selected. The tallest fiber is taken as the final target. When applying the second (or third) rule, the qualified fiber core set selected by the rule may contain multiple fibers; in this case, the fiber core from that set is directly selected. The highest one is the target.

[0041] Based on the above, by eliminating dimensions through normalization and merging multiple performance indicators into a single, comparable score through weighted summation, a quantitative ranking of the overall performance of fiber cores is achieved. This provides a more refined resource comparison tool that goes beyond simple threshold judgment. Without altering the existing pool of qualified available spare fiber cores selected by the original rules, it further optimizes the selection within this pool, ensuring that even among fiber cores meeting basic thresholds, the one with the best overall performance can be chosen. This improves the rationality of resource allocation and optimizes the overall performance base of services after recovery.

[0042] The aforementioned comprehensive quality scoring model relies on preset weight coefficients W1 and W2. Fixed weights may not adapt to changes in the network environment or the differences in characteristics between different fiber optic segments. To make the evaluation model adaptive and continuously optimize its scoring accuracy, as a further optional implementation method in this embodiment, the evaluation modeling step also includes: Based on historical input and output data, the weighting coefficients W1 and W2 are periodically calibrated to optimize the accuracy of the comprehensive quality score in characterizing the core performance.

[0043] Specifically, during the calibration process, a historical database is maintained and used to record two types of data: first, the input for the evaluation modeling steps, namely the loss and crosstalk values ​​of the fiber cores sensed in each iteration; and second, indirect output verification signals, such as whether the key performance indicators of the service flow recorded in the verification and backtracking steps meet the standards after the fiber core is assigned to carry services, or whether the fiber core is subsequently marked as having performance anomalies. The calibration process is initiated periodically (e.g., weekly). Data from a historical time period is selected, assuming there are... Each fiber core has a clearly defined "performance" label (e.g., "good performance" or "deteriorating performance") after being assigned a service. It has its historical status. and according to the current weight Calculated old rating The goal of the calibration algorithm is to find new weights. This leads to a new rating This allows for a better differentiation between "good performance" and "poor performance" fiber cores. One feasible approach is to construct an optimization problem: maximizing the difference between the average new score of the "good performance" fiber core group and the average new score of the "poor performance" fiber core group, while simultaneously satisfying... and The constraints are addressed. This optimization problem can be solved using existing optimization algorithms such as gradient descent and grid search. The new weights obtained from the solution will replace the old weights and be used for the comprehensive quality score calculation in the next cycle. In practical applications, other optimization algorithms can also be selected, and this application embodiment does not limit this.

[0044] Based on the above, by using real service performance feedback generated during network operation as a monitoring signal, the parameters of the evaluation model are adjusted in reverse, so that the comprehensive quality scoring model can continuously evolve with the accumulation of network operation time. Its scoring results can predict the performance of a single fiber core when it actually carries services more and more accurately, thereby making the decision based on the score more reliable and intelligent, and improving the long-term adaptability and robustness of the entire optimization method.

[0045] To automatically and accurately identify the service types carried on the operating fiber core during the dynamic mapping step, as an optional implementation method in this embodiment, the current service importance level of each service flow is determined according to a preset level mapping table associated with power communication service types during the dynamic mapping step, including: Deep packet inspection technology is used to identify the protocol type and destination IP address range of the service flow; The protocol type and destination IP address range are matched with a predefined power service feature database to determine the type of power communication service to which it belongs. Query the level mapping table to obtain the service importance level corresponding to this power communication service type.

[0046] Specifically, this step is performed by deploying software or hardware probes with deep packet inspection capabilities. As traffic flows through, the probe not only parses the IP and TCP / UDP headers but also further analyzes the characteristic fields of the application layer protocol. For example, for IEC 61850 messages, it parses the AppID to distinguish between MMS, GOOSE, and SV; for IEC 60870-5-104 messages, it parses the transmission reason. Simultaneously, the destination IP address of the traffic is recorded. A predefined power service characteristic library is used; this is a database or rule file that defines combinations of identification rules for various power communication service types. For example, a rule could be: traffic with a "protocol type" of "IEC 61850 GOOSE" and a "destination IP address range" of "10.1.1.0 / 24" (substation protection network segment) is identified as "relay protection service". Another rule could be: traffic with a "protocol type" of "IEC 60870-5-104" and a "destination IP address range" of "10.2.2.2 / 32" (dispatch center address) is identified as "dispatch automation service". The parsed (protocol type, destination IP) tuple is matched against all rules in the feature library. Once a match is found, the power communication service type to which the service flow belongs is determined. Finally, the level mapping table is queried to obtain the service importance level corresponding to this service type.

[0047] Based on the above, deep packet inspection (DBI) technology is used to obtain deep features of business flows, and these features are then combined with a predefined feature library for precise matching, thereby achieving automated and fine-grained identification of power-specific businesses. This enables real-time, dynamic, and accurate determination of business importance levels, providing reliable input for subsequent differential decision-making and avoiding the tediousness and lag of manually configuring static flow tables.

[0048] The handover and reconfiguration step requires translating the logical mapping relationship into the actual actions of physical devices and the updates of network protocols. To ensure the accuracy of the handover and the rapid convergence of the network, as an optional implementation method in this embodiment, generating and sending corresponding port switching control commands to the optical path switching device in the handover and reconfiguration step includes: generating a cross-configuration command for establishing an optical path connection as a port switching control command based on the physical port identifier of the optical cross-connect matrix corresponding to the target fiber core; Updating the network routing table includes: in the control plane, based on the mapping relationship between service flows and target fiber cores, flooding the network with updated link state announcements through routing protocols to synchronize routing information across the entire network.

[0049] Specifically, an optical cross-connect matrix typically has a management interface. Based on the mapping relationship between service flows and target fiber cores, the new physical port (target fiber core port) corresponding to each service flow and the old faulty port that needs to be removed are found. Then, a device vendor-specific configuration command string is generated. For example, for an optical cross-connect device using the TL1 language, the generated command might be similar to "ENT-CRS-ODU:::SRC=1-1-1,DST=2-2-2,BW=10G", meaning to establish a 10G cross-connect between ports 1-1-1 and 2-2-2. These commands are distributed to the device in batches via network management protocols such as SNMP or NETCONF. For route updates, in IP / MPLS-based bearer networks, the new fiber link (i.e., the link composed of target spare fiber cores) needs to be treated as an available route. A new Link State Advertisement (LSA) is constructed through a southbound interface (such as OpenFlow) or on a network element acting as a routing protocol speaker. This LSA contains information such as the new link ID and metric (which can be set based on the fiber core's overall quality score). Then, this LSA is flooded to the entire routing domain via OSPF or IS-IS protocols. After receiving the update, all routers in the domain will re-run the shortest path first algorithm, update their routing tables, and thus redirect the service IP traffic that was originally pointing to the failed path to this new path provided by the high-quality backup fiber core.

[0050] Based on the above, high-level optimization decisions are decomposed into direct configuration commands for optical layer devices and protocol-level drivers for the IP / MPLS control plane, thereby collaboratively completing service reconstruction across multiple network layers. This achieves seamless integration from intelligent decision-making to actual network topology changes, ensuring accurate execution of service switching actions and rapid, global convergence of network routing, thus minimizing service interruption time and guaranteeing efficient recovery.

[0051] The differential decision-making step is based on the prediction of the fiber core's state before the fault, while the actual performance after the service is switched to the target fiber core needs to be verified. To form an optimization closed loop, promptly address potential performance issues after the switch, and accumulate data for improvement, as an optional implementation in this embodiment, a verification and backtracking step is also included after the switchover and reconstruction step: Monitor the key performance indicators of each service flow on its target fiber core after the switchover; If the key performance indicators of a certain business flow continue to deteriorate and exceed the health threshold corresponding to its business importance level, the business flow will be remarked as a business to be migrated, and the difference decision step will be re-executed to select a new target fiber core. At the same time, the performance abnormality event of the original target fiber core will be marked in the fiber core status record.

[0052] Specifically, after the service switchover is completed, a performance monitoring agent is activated to obtain key performance indicators of the service flow, such as latency (measured via loopback timestamp messages), packet loss rate, and bit error rate, by mirroring the traffic at the target fiber core port or reading the performance management counters of the transmission equipment itself. Corresponding "health thresholds" are predefined for each service importance level; for example, the latency threshold for the "highest" level service is set to 5 milliseconds, and the bit error rate threshold is set to... The latency threshold for "normal" level services can be set to 50 milliseconds. Metrics are continuously collected (e.g., every second) and compared with the threshold. If a service flow's metric (e.g., latency) exceeds its health threshold for multiple consecutive monitoring periods (e.g., 3 periods), it is considered to be in continuous degradation. At this point, a backtracking process is triggered: First, the service flow's status is reset to pending migration. Second, a performance anomaly event is recorded, including at least the occurrence time, the original target fiber ID, the exceeding performance metric, and its value. Then, using this service flow as new input, the differential decision step is re-triggered, selecting a new target fiber from the currently available backup fiber pool (excluding the original fiber that was just marked as abnormal), and the switching and reconstruction step is executed again.

[0053] Based on the above, continuous post-hoc performance monitoring verifies the effectiveness of previous decisions and transitions, and remedial and recording mechanisms are initiated when expectations are not met. This forms a complete closed loop of decision-making, execution, verification, and re-decision, ensuring that even in rare cases where predictions deviate from reality, timely corrections can be made through secondary optimization, guaranteeing the ultimate stability of the business experience. Simultaneously, marking performance anomalies provides valuable data sources for subsequent analysis and model optimization.

[0054] The performance anomalies marked in the verification and backtracking steps are important feedback reflecting the reasonableness of existing decision rules (thresholds) or health thresholds. To utilize this feedback to enable the rules to self-optimize, as a further optional implementation of this embodiment, the verification and backtracking steps also include: Based on the recorded performance anomaly events, the thresholds or health thresholds used in the core selection rules in the differential decision-making process are dynamically adjusted.

[0055] Specifically, accumulated performance anomaly records are analyzed periodically (e.g., monthly). The analysis focuses on two types of thresholds: one is the threshold used in the fiber core selection rules (such as the first threshold). Second threshold Third threshold Second, the health thresholds used in the verification and backtracking steps. For the fiber core selection rule thresholds, the analysis logic is as follows: If multiple events are found where the business flow is switched to meet the current... If performance degradation due to crosstalk persists even after a fiber core with a threshold (e.g., -40dB), it may indicate that the current... The settings are too lenient. They could be automatically suggested or approved by the administrator. Tighten the threshold, for example, to -42dB. Conversely, if no events occur for a long period and a large number of high-quality fiber cores are found to be underutilized due to slightly exceeding the current strict threshold, the threshold can be appropriately relaxed to improve resource utilization. The adjustment process can be based on statistical methods; for example, setting the threshold so that, at a certain confidence level (e.g., 95%), historically performing fiber cores can be selected into the qualified pool. A similar principle can be used to adjust the health threshold. For example, if it is found that the latency of "highest" level services rarely exceeds 3 milliseconds, and the threshold is set to 5 milliseconds, the health threshold can be tightened to 4 milliseconds to trigger an earlier and more sensitive anomaly response. Dynamic adjustment of the threshold is achieved by updating the policy configuration file.

[0056] Based on the above, the experience process of adjusting strategies according to fault feedback in operation and maintenance practice is automated and algorithmized, so that the entire optimization method can not only make intelligent decisions in a single fault, but also continuously evolve its decision criteria in long-term operation, so that the rule threshold and health threshold are always kept at the most reasonable level, thereby continuously improving the overall performance of this method and its ability to adapt to different network environments, and realizing a higher level of intelligence.

[0057] In the embodiments provided in this application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor may be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments may be performed by a computer program instructing the associated hardware. During implementation, the program may be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible to a computer. Computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0058] Finally, it should be noted that the above description is only a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A communication network optimization method based on fiber optic sensing and the importance of carried services, applied to fiber optic communication networks with operating fiber cores and spare fiber cores, characterized in that, The method includes: Continuous sensing steps: Periodically inject optical time-domain reflectometry signals into all spare fiber cores, and calculate the current loss value and current crosstalk value of each spare fiber core based on the backscattering signal of each spare fiber core. Dynamic mapping steps: Monitor and analyze the service flows carried on the operating fiber core, and determine the current service importance level of each service flow according to the preset level mapping table associated with power communication service types; wherein, the power communication service types include at least relay protection services, safety and stability control services, dispatch automation services and management information services; Differential decision-making steps: When any operating fiber core failure is detected, the current service importance level of all affected service flows on the failed operating fiber core is obtained. Fiber core allocation operations are performed sequentially for each affected service flow in descending order of service importance level, until target fiber cores are allocated to all affected service flows, forming a mapping relationship between service flows and target fiber cores. The fiber core allocation operation includes: according to the fiber core selection rules pre-configured for the service importance level, selecting target fiber cores that meet the rules from the currently available set of spare fiber cores, and removing the target fiber core from the set of spare fiber cores. The fiber core selection rules pre-configured for high service importance levels have stricter performance thresholds for the current loss value and / or current crosstalk value of spare fiber cores than the rules pre-configured for low service importance levels. Switching and reconfiguration steps: Based on the mapping relationship between the service flow and the target fiber core, generate and send corresponding port switching control commands to the optical path switching equipment to switch each service flow to its assigned target fiber core and update the network routing table.

2. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 1, characterized in that, In the continuous sensing step, the optical time-domain reflectometry (OTDR) sensing signal is a phase-sensitive OTD signal; the calculation of the current crosstalk value for each spare fiber core includes: The frequency domain characteristics of the backscattered signal are analyzed, and the current crosstalk value is calculated by demodulating the specific spectral components generated by mode field coupling between adjacent fiber cores.

3. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 1, characterized in that, In the difference decision-making step, the fiber core selection rule pre-configured for high business importance level is defined as the first rule. The first rule includes: selecting a fiber core with the lowest current loss value and the current crosstalk value below a first threshold from the set of spare fiber cores as the corresponding target fiber core. The fiber core selection rule pre-configured for other levels below the high business importance level is defined as the second rule. The second rule includes: selecting a fiber core from the set of spare fiber cores whose current loss value is lower than a second threshold and whose current crosstalk value is lower than a third threshold as the corresponding target fiber core; wherein, the second threshold is greater than the loss level corresponding to the first threshold.

4. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 3, characterized in that, It also includes a policy pre-configuration step: Based on the safety zoning principle of the power production control area and the management information area, relay protection business and safety and stability control business are mapped to the highest business importance level and associated with the first rule; The scheduling automation service is mapped to the second highest service importance level, and associated with a third rule whose loss and crosstalk thresholds are between the first rule and the second rule; Map management information business to the importance level of ordinary business, and associate it with the second rule.

5. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 4, characterized in that, Between the continuous sensing step and the difference decision step, there is also an evaluation modeling step: based on the current loss value and current crosstalk value calculated by the continuous sensing step, a comprehensive quality score is calculated for each spare fiber core, the comprehensive quality score = W1×N(current loss value) + W2×N(current crosstalk value), where N(·) represents the normalization function, W1 and W2 are preset weight coefficients, satisfying W1>W2>0 and W1+W2=1; The comprehensive quality score is used in the difference decision step to select the fiber with the highest comprehensive quality score from the multiple backup fiber cores when multiple backup fiber cores that meet the conditions are selected according to the rule, in order to select the final target fiber core.

6. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 5, characterized in that, The evaluation modeling steps also include: Based on historical input and output data, the weighting coefficients W1 and W2 are periodically calibrated to optimize the accuracy of the comprehensive quality score in characterizing the fiber core performance.

7. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 1, characterized in that, In the dynamic mapping step, determining the current service importance level of each service flow based on a preset level mapping table associated with power communication service types includes: Deep packet inspection technology is used to identify the protocol type and destination IP address range of the service flow; The protocol type and the destination IP address range are matched with a predefined power service feature database to determine the type of power communication service to which they belong. Query the level mapping table to obtain the service importance level corresponding to the power communication service type.

8. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 1, characterized in that, In the switching and reconfiguration step, generating and sending the corresponding port switching control command to the optical path switching device includes: generating a cross-configuration command for establishing an optical path connection as the port switching control command based on the physical port identifier of the optical cross-connect matrix corresponding to the target fiber core; The update of the network routing table includes: in the control plane, based on the mapping relationship between the service flow and the target fiber core, flooding the network with updated link status announcements through a routing protocol to synchronize the routing information of the entire network.

9. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 1, characterized in that, Following the switching and refactoring step, a verification and backtracking step is also included: Monitor the key performance indicators of each service flow on its target fiber core after the switchover; If the key performance indicators of a certain service flow continue to deteriorate and exceed the health threshold corresponding to its service importance level, the service flow will be remarked as a service to be migrated, and the difference decision step will be re-executed to select a new target fiber core. At the same time, the performance abnormality event of the original target fiber core will be marked in the fiber core status record.

10. The communication network optimization method based on fiber optic sensing and the importance of carried services according to claim 9, characterized in that, The verification and backtracking steps also include: Based on the recorded performance anomaly events, the threshold or health threshold used in the core selection rule in the differential decision-making step is dynamically adjusted.

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