Resource adjustment method and device of optical network, electronic equipment and medium

Abstract

The embodiment of the present application provides a resource adjustment method of an optical network, which comprises the following steps: obtaining optical network service data and a service quality mapping table output by an optical network management system, and obtaining network resource data output by the optical network management system; obtaining a plurality of service index items and corresponding strong constraint conditions of each index item according to the optical network service data and the service quality mapping table; generating a resource adjustment candidate scheme according to the network resource data, a quality target weight, a cost target weight and an energy consumption target weight; and determining a resource adjustment target scheme according to the resource adjustment candidate scheme and the corresponding strong constraint conditions of each service index item, so as to realize the real root cause of the increase of the optical network delay caused by the service data and the service quality mapping, avoid the situation that the invalid expansion is caused because the service growth and the equipment state change are also attributed to the bandwidth shortage only by relying on the bandwidth occupation rate to trigger the expansion, and thus the resource waste and the cost expenditure are reduced.

Description

Technical Field

[0001] This invention relates to the technical field of resource adjustment in optical networks, and in particular to a method, apparatus, electronic device, and readable storage medium for resource adjustment in optical networks. Background Technology

[0002] With the continuous expansion of optical network scale and the diversification of service types, optical network management and control systems are gradually evolving from single bandwidth management to multi-objective intelligent scheduling, and the requirements for the accuracy and adaptability of network resource adjustments are increasing. Optical network resource optimization and adjustment is a highly complex task. To ensure service quality in multi-service scenarios, the management system needs to possess multi-dimensional service perception, differentiated root cause identification, and multi-objective joint optimization capabilities. During operation, due to dynamic changes in traffic volume, degradation of equipment physical layer status, and the diversity of service quality constraints, existing optical network optimization and adjustment schemes are limited in their resource adjustment trigger judgment, typically relying only on bandwidth utilization as a single indicator for start-up and shutdown control.

[0003] In related technologies, when both the increase in service volume and changes in equipment status manifest as an increase in latency, the optical network management system only uses the bandwidth utilization threshold to determine and trigger bandwidth compensation operations. However, when physical layer degradation leads to increased latency but the bandwidth utilization does not increase significantly, it still fails to distinguish the root cause and misjudges it as insufficient bandwidth, triggering capacity expansion in a uniform manner. This results in repeated ineffective capacity expansion, accumulating redundant resources and ineffective costs. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention are proposed to provide a resource adjustment method, apparatus, electronic device, and readable storage medium for an optical network that overcomes or at least partially solves the above problems.

[0005] In a first aspect, embodiments of the present invention provide a resource adjustment method for an optical network, the method comprising: Obtain optical network service data and service quality mapping table output by the optical network management and control system; the optical network service data includes: service scenario, service type, service runtime, and bandwidth usage value. Based on the optical network service data and the service quality mapping table, multiple service indicators and corresponding strong constraints are obtained. Obtain the weight mapping table, and based on the optical network service data and the weight mapping table, obtain the quality target weight, cost target weight, and energy consumption target weight; Acquire network resource data output by the optical network management and control system; Based on the network resource data, the quality target weight, the cost target weight, and the energy consumption target weight, a resource adjustment candidate scheme is generated; Based on the candidate resource adjustment schemes and the strong constraints corresponding to the multiple business service indicator items, the target resource adjustment scheme is determined; The resource adjustment target plan is sent to the optical network management system to adjust the resources of the optical network.

[0006] Optionally, the service metrics include latency, bandwidth, and packet loss rate. The step of obtaining multiple service metrics and corresponding strong constraints based on the optical network service data and the service quality mapping table includes: Based on the service type, the corresponding service runtime segment is determined from the first mapping relationship included in the service quality mapping table; the first mapping relationship is the mapping relationship between the service type and the service runtime segment. Based on the service runtime segment, the corresponding bandwidth usage value is determined from the second mapping relationship included in the service quality mapping table; the second mapping relationship is the mapping relationship between the service runtime segment and the bandwidth usage value. Based on the bandwidth occupancy value, the corresponding latency, bandwidth, and packet loss rate are determined from the third mapping relationship included in the service quality mapping table, as well as the strong constraints corresponding to the latency, bandwidth, and packet loss rate; the third mapping relationship is the mapping relationship between the bandwidth occupancy value and the latency, bandwidth, and packet loss rate, as well as the mapping relationship between the strong constraints corresponding to the latency, bandwidth, and packet loss rate.

[0007] Optionally, obtaining the weight mapping table, and obtaining the quality target weight, cost target weight, and energy consumption target weight based on the optical network service data and the weight mapping table, includes: Based on the business scenario, the corresponding business runtime segment is determined from the fourth mapping relationship included in the weight mapping table; the fourth mapping relationship is the mapping relationship between the business scenario and the business runtime segment. Based on the service runtime segment, the corresponding quality target weight, cost target weight, and energy consumption target weight are determined from the fifth mapping relationship included in the weight mapping table; the fifth mapping relationship is the mapping relationship between the service runtime segment and the quality target weight, the cost target weight, and the energy consumption target weight.

[0008] Optionally, the method further includes: Obtain business operation and maintenance policies, including energy consumption operation and maintenance policies and cost operation and maintenance policies; The weight of the energy consumption target is adjusted according to the energy consumption operation and maintenance policy, and the weight of the cost target is adjusted according to the cost operation and maintenance policy; The weights of the quality target, the cost target, and the energy consumption target are normalized proportionally so that the sum of the weights of the quality target, the cost target, and the energy consumption target is 1.

[0009] Optionally, the method further includes: When the business service indicator has strong constraints and the quality target weight of the business service indicator is less than the quality weight threshold, the quality target weight is increased to the quality weight threshold. After the quality target weight is increased, the quality target weight, the cost target weight, and the energy consumption target weight are normalized proportionally so that the sum of the quality target weight, the cost target weight, and the energy consumption target weight is 1.

[0010] Optionally, the network resource data includes currently available bandwidth, number of idle wavelengths, number of idle ports, unit cost of each expansion device, and real-time energy consumption of the devices; determining the target resource adjustment scheme based on the candidate resource adjustment schemes and the strong constraints corresponding to the multiple service indicator items includes: Based on the currently available bandwidth, a bandwidth adjustment scheme is generated, which is used to indicate the reallocation of service bandwidth; And / or, Based on the number of idle wavelengths and / or the number of idle ports, a resource reuse scheme is generated, which is used to indicate that the current service traffic is distributed to idle wavelengths and / or idle ports; And / or, Based on the expansion equipment, an expansion plan is generated, which is used to indicate the addition of boards and / or the expansion of ports.

[0011] Optionally, determining the target resource adjustment scheme based on the candidate resource adjustment schemes and the strong constraints corresponding to the multiple business service indicator items includes: Determine the latency, packet loss rate, equipment cost, and equipment power consumption of the optical network management system after adjustment according to the resource adjustment candidate scheme; A quality score is obtained based on the latency and the packet loss rate; a cost score is obtained based on the adjusted equipment cost; and an energy consumption score is obtained based on the equipment operating power consumption. The sum of the product of the quality score and the quality target weight, the product of the cost score and the cost target weight, and the product of the energy consumption score and the energy consumption target weight is determined as the comprehensive score of the resource adjustment candidate scheme. The resource adjustment candidate schemes are ranked from highest to lowest based on their comprehensive scores. The resource adjustment candidate schemes that satisfy the aforementioned strong constraints are determined as the resource adjustment target schemes; The step of determining the resource adjustment candidate schemes that satisfy the strong constraints as the resource adjustment target scheme includes: If the currently ranked top solution satisfies the aforementioned strong constraint condition, then that solution is determined as the target solution for resource adjustment. If the currently ranked first solution does not meet the strong constraint condition, then the strong constraint condition is verified for the next ranked solution, and the resource adjustment candidate solution that meets the strong constraint condition is determined as the resource adjustment target solution.

[0012] Secondly, embodiments of the present invention provide an apparatus for resource adjustment in an optical network, the apparatus comprising: The optical network service data acquisition module is used to acquire optical network service data and service quality mapping table output by the optical network management and control system; the optical network service data includes: service scenario, service type, service runtime, and bandwidth usage value. The service service data determination module is used to obtain multiple service service indicators and strong constraints corresponding to the multiple service service indicators based on the optical network service data and the service service quality mapping table. The weight determination module is used to obtain a weight mapping table and to obtain the quality target weight, cost target weight, and energy consumption target weight based on the optical network service data and the weight mapping table. The network resource data acquisition module is used to acquire network resource data output by the optical network management and control system; The candidate solution generation module is used to generate resource adjustment candidate solutions based on the network resource data, the quality target weight, the cost target weight, and the energy consumption target weight. The target solution determination module is used to determine the target solution for resource adjustment based on the candidate solutions for resource adjustment and the strong constraints corresponding to the multiple business service indicator items. The optical network adjustment module is used to send the resource adjustment target plan to the optical network management system to adjust the resources of the optical network.

[0013] Optionally, the service metrics include latency, bandwidth, and packet loss rate, and the service data determination module includes: The first mapping submodule is used to determine the corresponding service runtime segment from the first mapping relationship included in the service quality mapping table according to the service type; the first mapping relationship is the mapping relationship between the service type and the service runtime segment; The second mapping submodule is used to determine the corresponding bandwidth usage value from the second mapping relationship included in the service quality mapping table according to the service runtime segment; the second mapping relationship is the mapping relationship between the service runtime segment and the bandwidth usage value; The third mapping submodule is used to determine the corresponding latency, bandwidth, and packet loss rate, as well as the strong constraints corresponding to the latency, bandwidth, and packet loss rate, from the third mapping relationship included in the service quality mapping table based on the bandwidth occupancy value; the third mapping relationship is the mapping relationship between the bandwidth occupancy value and the latency, bandwidth, and packet loss rate, as well as the mapping relationship between the strong constraints corresponding to the latency, bandwidth, and packet loss rate.

[0014] Optionally, the weight determination module includes: The fourth mapping submodule is used to determine the corresponding business runtime segment from the fourth mapping relationship included in the weight mapping table according to the business scenario; the fourth mapping relationship is the mapping relationship between the business scenario and the business runtime segment. The fifth mapping submodule is used to determine the corresponding quality target weight, cost target weight, and energy consumption target weight from the fifth mapping relationship included in the weight mapping table according to the service runtime segment; the fifth mapping relationship is the mapping relationship between the service runtime segment and the quality target weight, the cost target weight, and the energy consumption target weight.

[0015] Optionally, the device further includes: The operation and maintenance policy acquisition module is used to acquire business operation and maintenance policies, which include energy consumption operation and maintenance policies and cost operation and maintenance policies. The first weight adjustment module is used to adjust the weight of the energy consumption target according to the energy consumption operation and maintenance policy, and to adjust the weight of the cost target according to the cost operation and maintenance policy; The second weight adjustment module is used to normalize the quality target weight, the cost target weight, and the energy consumption target weight proportionally, so that the sum of the quality target weight, the cost target weight, and the energy consumption target weight is 1.

[0016] Optionally, the device further includes: The third weight adjustment module is used to increase the quality target weight to the quality weight threshold when the business service indicator item has strong constraints and the quality target weight of the business service indicator item is less than the quality weight threshold. The fourth weight adjustment module is used to normalize the quality target weight, the cost target weight, and the energy consumption target weight proportionally after the quality target weight is increased, so that the sum of the quality target weight, the cost target weight, and the energy consumption target weight is 1.

[0017] Optionally, the network resource data includes currently available bandwidth, number of idle wavelengths, number of idle ports, unit cost of each expansion device, and real-time energy consumption of the devices; the target solution determination module includes: The first resource adjustment module is used to generate a bandwidth adjustment scheme based on the currently available bandwidth, and the bandwidth adjustment scheme is used to indicate the reallocation of service bandwidth; And / or, The second resource adjustment module is used to generate a resource reuse scheme based on the number of idle wavelengths and / or the number of idle ports. The generated resource reuse scheme is used to indicate that the current service traffic is distributed to idle wavelengths and / or idle ports. And / or, The third resource adjustment module is used to generate an expansion plan based on the expansion equipment. The expansion plan is used to indicate the addition of boards and / or the expansion of ports.

[0018] Optionally, the target solution determination module includes: The adjustment prediction submodule is used to determine the latency, packet loss rate, adjustment equipment cost, and equipment operating power consumption of the optical network management system after adjustment according to the resource adjustment candidate scheme; The first score determination submodule is used to obtain a quality score based on the latency and the packet loss rate, a cost score based on the adjusted equipment cost, and an energy consumption score based on the equipment operating power consumption. The second score determination submodule is used to determine the comprehensive score of the resource adjustment candidate scheme by summing the product of the quality score and the quality target weight, the product of the cost score and the cost target weight, and the product of the energy consumption score and the energy consumption target weight. The scheme ranking submodule is used to rank the resource adjustment candidate schemes from high to low according to their comprehensive scores. The scheme verification submodule is used to determine the resource adjustment candidate schemes that meet the strong constraints as the resource adjustment target schemes; The scheme verification submodule includes: The first scheme verification unit is used to determine the scheme as the resource adjustment target scheme if the scheme currently ranked first satisfies the strong constraint condition. The second scheme verification unit is used to verify the strong constraint condition for the next scheme if the current first-ranked scheme does not meet the strong constraint condition, and to determine the resource adjustment candidate scheme that meets the strong constraint condition as the resource adjustment target scheme.

[0019] Thirdly, embodiments of the present invention provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the resource adjustment method for an optical network as described in the first aspect.

[0020] Fourthly, embodiments of the present invention provide a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the resource adjustment method for an optical network as described in the first aspect.

[0021] The embodiments of the present invention have the following advantages: This invention acquires optical network service data and a service quality of service (SHS) mapping table output by the optical network management system, as well as network resource data output by the same system. Based on the optical network service data and SHS mapping table, it obtains multiple service indicators and corresponding strong constraints. Based on network resource data, quality target weights, cost target weights, and energy consumption target weights, it generates candidate resource adjustment schemes. Based on the candidate schemes and the strong constraints corresponding to each service indicator, it determines the target resource adjustment scheme. This achieves multi-dimensional correlation analysis between optical network service data and the SHS mapping table to identify the true root cause of increased optical network latency. When increased traffic leads to increased latency, bandwidth occupancy increases accordingly. This situation is verified and identified through service scenarios and runtime conditions, triggering bandwidth compensation. When changes in device status lead to increased latency, bandwidth occupancy does not change significantly. The SHS mapping table eliminates traffic growth factors, thereby identifying the root cause of physical layer degradation and triggering link optimization. This avoids misjudging device status changes as insufficient bandwidth by relying solely on bandwidth occupancy for unified capacity expansion, leading to repeated ineffective capacity expansion. This reduces redundant resource accumulation and ineffective cost expenditures. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating the steps of a resource adjustment method for an optical network provided in an embodiment of the present invention; Figure 2 This is a flowchart of another method for adjusting resources in an optical network provided by an embodiment of the present invention; Figure 3This is a scene device diagram of a resource adjustment method for an optical network provided in an embodiment of the present invention; Figure 4 This is a structural block diagram of a resource adjustment device for an optical network provided in an embodiment of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] The terms "first," "second," etc., used in the specification and claims of this invention are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0026] With the evolution of optical network technology and the increasing complexity of services, optical network management and control systems are gradually shifting from simple resource allocation to intelligent and refined management. The need for optimization and adjustment in multi-service scenarios is becoming increasingly prominent. Resource optimization in optical network management and control systems is a highly complex task. To ensure stable operation and service quality under various service scenarios, the management system needs accurate service perception capabilities, rapid resource adjustment decision-making capabilities, and adaptive multi-objective optimization capabilities. During operation, due to the diversity of service types, the suddenness of network traffic, and the unpredictability of changes in the physical layer state of equipment, existing optical network resource adjustment schemes typically rely solely on bandwidth utilization as a single indicator for triggering decisions. In related technologies, optical network management and control systems need to adjust resources to ensure service quality in multi-service concurrent scenarios, but often only rely on bandwidth utilization thresholds to determine the start and stop of adjustments. When both increased service volume and changes in the physical layer state of equipment manifest as increased latency, the system cannot distinguish between these two different root causes to trigger bandwidth compensation operations uniformly. This leads to misjudgments of insufficient bandwidth in physical layer degradation scenarios, resulting in repeated capacity expansion and generating a large amount of redundant resources and ineffective costs.

[0027] Therefore, how to identify the true root cause of increased latency in optical networks, and avoid ineffective resource expansion and cost accumulation due to misjudgment of a single bandwidth utilization indicator, has become an urgent technical problem to be solved in the field of optical network management.

[0028] One of the core concepts of this invention is to obtain optical network service data and a service quality of service mapping table output by the optical network management system, as well as network resource data output by the optical network management system; to obtain multiple service indicators and corresponding strong constraints based on the optical network service data and the service quality of service mapping table; to generate resource adjustment candidate schemes based on network resource data, quality target weights, cost target weights, and energy consumption target weights; and to determine the target resource adjustment scheme based on the resource adjustment candidate schemes and the strong constraints corresponding to each service indicator, thereby realizing the connection between optical network service data and service quality of service mapping. Multidimensional correlation analysis of the mapping table identifies the true root cause of increased latency in optical networks. When increased traffic leads to increased latency, bandwidth usage rises accordingly. This situation is verified and identified through business scenarios and runtime periods, triggering bandwidth compensation. When changes in device status lead to increased latency, bandwidth usage does not change significantly. By excluding traffic growth factors through the service quality mapping table, the root cause of physical layer degradation is identified, and link optimization is triggered. This avoids the situation where simply relying on bandwidth usage to trigger capacity expansion leads to misjudging changes in device status as insufficient bandwidth, resulting in repeated and ineffective capacity expansion. This reduces the accumulation of redundant resources and ineffective cost expenditures.

[0029] Figure 1 This is a flowchart of the steps of a resource adjustment method for an optical network provided in an embodiment of the present invention.

[0030] like Figure 1 As shown, the method may specifically include the following steps: Step 101: Obtain the optical network service data and service quality mapping table output by the optical network management and control system; the optical network service data includes: service scenario, service type, service runtime, and bandwidth usage value; In this embodiment of the invention, the optical network management and control system can be a control system for unified management and scheduling of optical network resources. It operates in multi-service concurrent scenarios and needs to perceive the network service status in real time and make resource optimization decisions. Optical network service data can characterize the operational status data of each service traffic carried by the optical network management and control system, including service scenario, service type, service runtime, and bandwidth usage. Specifically, the service scenario can characterize the specific application environment of the service operation, such as data center interconnection, mobile fronthaul, mobile backhaul, or enterprise private line scenarios; the service type can characterize the service's sensitivity to network performance, such as low-latency sensitive services, high-bandwidth-consuming services, or ordinary best-effort forwarding services; the service runtime can characterize the temporal distribution characteristics of service traffic, such as peak, off-peak, or low-peak periods, with different network load pressures corresponding to different time periods; and the bandwidth usage can characterize the actual bandwidth occupied by the current service. A service quality mapping table can characterize the correspondence between service scenario, service type, service runtime, and service quality indicators.

[0031] By acquiring the optical network service data and service quality mapping table output by the optical network management and control system, it is possible to directly utilize the existing service status information of the management and control system to obtain the current network service load and service quality requirements without waking up or calling additional measurement resources.

[0032] Step 102: Obtain multiple service indicator items and corresponding strong constraints based on the optical network service data and the service quality mapping table; In this embodiment of the invention, service metrics can characterize key performance indicators for measuring service quality, such as end-to-end latency, packet loss rate, jitter, and available bandwidth. Strong constraints can characterize hard threshold boundaries that service metrics must meet. For example, the maximum end-to-end latency of a low-latency-sensitive service must not exceed 5ms, and the available bandwidth of a high-bandwidth-consuming service must not be less than 1Gbps. If the adjusted metrics exceed these constraints, service quality cannot be guaranteed.

[0033] Based on the service scenario, service type, and service runtime in the optical network service data, and combined with the service quality mapping table, multiple service indicators corresponding to each service in the current service scenario, as well as the strong constraints corresponding to each indicator, can be obtained by looking up the table. For example, in the mobile fronthaul scenario, if the service type is low latency sensitive and the service runtime is during peak periods, the mapping table can output end-to-end latency ≤ 5ms and packet loss rate ≤ 1×10⁻⁶. -6 Strong constraints; in data center interconnection scenarios, if the service type is high bandwidth consumption, then a strong constraint condition with available bandwidth ≥ 10Gbps can be output.

[0034] By transforming raw business data into quantifiable business service metrics and their strong constraints, this invention transforms vague business service quality requirements into clear boundary parameters that can participate in subsequent resource optimization decisions, ensuring that resource adjustment schemes always adhere to the premise of not exceeding the bottom line of business service quality.

[0035] Step 103: Obtain the weight mapping table, and obtain the quality target weight, cost target weight, and energy consumption target weight based on the optical network service data and the weight mapping table; In this embodiment of the invention, the weight mapping table can represent the correspondence between business scenarios, business types, business runtime periods, and quality target weights, cost target weights, and energy consumption target weights. The quality target weight can represent the degree of emphasis on ensuring the quality of business services during resource adjustment, the cost target weight can represent the degree of emphasis on controlling resource usage costs, and the energy consumption target weight can represent the degree of emphasis on controlling equipment energy consumption.

[0036] Based on the different optimization objectives under different business scenarios, the weight mapping table can pre-set corresponding weight allocations: for example, in mobile fronthaul scenarios, the service has extremely high requirements for latency and reliability, so the quality target weight is set to the highest value; in data center interconnection scenarios, the resource consumption cost brought by high bandwidth transmission is high, so the cost target weight is increased accordingly; in energy-sensitive scenarios, the energy consumption target weight dominates. By looking up the table, the quality target weight, cost target weight, and energy consumption target weight corresponding to the current optical network service data can be obtained from the weight mapping table.

[0037] By introducing a weight mapping table, this embodiment of the invention enables the resource adjustment scheme to dynamically adjust the optimization focus according to different business scenarios and runtime periods, avoiding the problem of insufficient adaptability of single-target optimization under different business needs.

[0038] Step 104: Obtain network resource data output by the optical network management and control system; In this embodiment of the invention, network resource data can characterize the status information of the physical and logical resources that the optical network management and control system can currently call upon, including but not limited to available bandwidth resources, optical link status, optical amplifier gain, wavelength channel occupancy, redundant path resources, etc.

[0039] By acquiring network resource data, this embodiment of the invention can grasp the current real resource inventory and status of the network, providing a data foundation for generating subsequent resource adjustment candidate schemes and ensuring that the generated candidate schemes are physically feasible.

[0040] Step 105: Generate resource adjustment candidate schemes based on the network resource data, the quality target weight, the cost target weight, and the energy consumption target weight; In this embodiment of the invention, the resource adjustment candidate scheme can represent a set of one or more feasible resource adjustment operations, such as bandwidth expansion scheme, link switching scheme, wavelength rerouting scheme, power adjustment scheme, etc.

[0041] Based on the network resource data obtained in step 104, the currently available resource inventory is determined. A multi-objective optimization function is constructed based on the quality target weight, cost target weight, and energy consumption target weight obtained in step 103. During the optimization process, a higher quality target weight indicates that candidate solutions are more likely to prioritize ensuring business service quality indicators; a higher cost target weight indicates that candidate solutions are more likely to choose operations with lower resource consumption costs; and a higher energy consumption target weight indicates that candidate solutions are more likely to choose adjustment paths with lower energy consumption. Under the joint guidance of the multi-objective weights, one or more resource adjustment candidate solutions are generated.

[0042] By combining the weights of quality, cost, and energy consumption, the candidate solutions generated in this embodiment of the invention no longer rely on a single indicator, but can comprehensively weigh multiple optimization dimensions, thus avoiding the optimization deviation caused by only considering bandwidth utilization in traditional solutions.

[0043] Step 106: Determine the target resource adjustment scheme based on the candidate resource adjustment schemes and the strong constraints corresponding to the multiple business service indicator items; In this embodiment of the invention, the resource adjustment target scheme can represent the final execution scheme selected from the candidate schemes that satisfies all strong constraints and has the best overall optimization effect.

[0044] The resource adjustment candidate schemes generated in step 105 are input one by one into the strong constraints corresponding to the multiple business service indicator items obtained in step 102 for verification. For any candidate scheme, if its adjusted business service indicator item cannot meet any strong constraint condition, the scheme is eliminated; if multiple candidate schemes meet all strong constraints, a comprehensive score is calculated based on the weights of the quality target, cost target, and energy consumption target, and the scheme with the best comprehensive score is selected as the target resource adjustment scheme.

[0045] By combining hard screening with strong constraints with soft scoring with multi-objective weights, this embodiment of the invention ensures that the final resource adjustment target plan will not break the bottom line of business service quality, and will achieve the optimal balance in the multi-objective optimization dimensions.

[0046] Step 107: Send the resource adjustment target plan to the optical network management system to adjust the resources of the optical network.

[0047] In this embodiment of the invention, the control interface of the optical network management system can output corresponding adjustment instructions according to the resource adjustment target scheme, such as bandwidth adjustment instructions, link switching instructions, wavelength rerouting instructions, or power adjustment instructions, so that the optical network management system can switch from the current state to the resource allocation state indicated by the target scheme.

[0048] This invention acquires optical network service data and a service quality of service (SHS) mapping table output by the optical network management system, as well as network resource data output by the same system. Based on the optical network service data and SHS mapping table, it obtains multiple service indicators and corresponding strong constraints. Based on network resource data, quality target weights, cost target weights, and energy consumption target weights, it generates candidate resource adjustment schemes. Based on the candidate schemes and the strong constraints corresponding to each service indicator, it determines the target resource adjustment scheme. This achieves multi-dimensional correlation analysis between optical network service data and the SHS mapping table to identify the true root cause of increased optical network latency. When increased traffic leads to increased latency, bandwidth occupancy increases accordingly. This situation is verified and identified through service scenarios and runtime conditions, triggering bandwidth compensation. When changes in device status lead to increased latency, bandwidth occupancy does not change significantly. The SHS mapping table eliminates traffic growth factors, thereby identifying the root cause of physical layer degradation and triggering link optimization. This avoids misjudging device status changes as insufficient bandwidth by relying solely on bandwidth occupancy for unified capacity expansion, leading to repeated ineffective capacity expansion. This reduces redundant resource accumulation and ineffective cost expenditures.

[0049] Figure 2 This is a flowchart of another method for adjusting resources in an optical network provided by an embodiment of the present invention.

[0050] like Figure 2 As shown, the method may specifically include the following steps: Step 201: Obtain the optical network service data and service quality mapping table output by the optical network management and control system; the optical network service data includes: service scenario, service type, service runtime, and bandwidth usage value; In this embodiment of the invention, the optical network management and control system can represent a control system used for unified management and scheduling of optical network resources. Optical network service data can represent the operational status data of each service traffic currently carried by the optical network management and control system. Specifically, the service scenario can represent the specific application environment of the service operation, such as 5G medical image transmission, industrial control, video surveillance, or broadband internet access; different scenarios have fundamentally different network performance requirements. The service type can represent the sensitivity of the service to network performance, such as latency-sensitive services, bandwidth-intensive services, or best-effort forwarding services. The service runtime can represent the temporal distribution characteristics of the service traffic, such as the peak service period from 8:00 to 12:00 on weekdays or the off-peak service period from 23:00 to 6:00 the next day. The bandwidth occupancy value can represent the actual bandwidth occupied by the current service.

[0051] By acquiring the above data, embodiments of the present invention can achieve initial perception of business status without additional measurement.

[0052] Step 202: Obtain multiple service indicator items and corresponding strong constraints based on the optical network service data and the service quality mapping table; In this embodiment of the invention, service metrics can characterize key performance indicators for measuring service quality, including latency, bandwidth, and packet loss rate. Strong constraints can characterize hard threshold boundaries that service metrics must meet. If the adjusted metrics exceed these constraints, the service will not be able to be provided normally. For example, in a 5G medical image transmission scenario, if the latency exceeds 10ms, the remote diagnostic video will stutter, directly affecting diagnostic accuracy. Therefore, latency ≤ 10ms is a strong constraint in this scenario.

[0053] In some embodiments, step 202 may include the following sub-steps, wherein the service metrics in step 202 may include latency, bandwidth, and packet loss rate.

[0054] Sub-step S11: Based on the service type, determine the corresponding service runtime segment from the first mapping relationship included in the service quality mapping table; the first mapping relationship is the mapping relationship between the service type and the service runtime segment; In this embodiment of the invention, different business types can have different time-sharing patterns. For example, medical imaging business is usually concentrated during the daytime surgery scheduling period on weekdays, video surveillance business operates around the clock but traffic decreases significantly at night, while industrial control business is often strongly correlated with production line scheduling.

[0055] The candidate range of business runtime segments can be initially determined by the business type.

[0056] Sub-step S12: Based on the service runtime segment, determine the corresponding bandwidth usage value from the second mapping relationship included in the service quality mapping table; the second mapping relationship is the mapping relationship between the service runtime segment and the bandwidth usage value. In this embodiment of the invention, the bandwidth requirements of the same service vary significantly in different operating periods. Taking video surveillance as an example, daytime surveillance footage is characterized by frequent movement and rich detail, requiring higher bandwidth; while nighttime footage is relatively static, resulting in a significant decrease in bandwidth requirements.

[0057] The corresponding bandwidth usage range can be determined by the business runtime segment, providing a basis for accurate matching of subsequent strong constraints.

[0058] Sub-step S13: Based on the bandwidth occupancy value, determine the corresponding latency, bandwidth, and packet loss rate from the third mapping relationship included in the service quality mapping table, as well as the strong constraints corresponding to the latency, bandwidth, and packet loss rate; the third mapping relationship is the mapping relationship between the bandwidth occupancy value and the latency, bandwidth, and packet loss rate, as well as the mapping relationship between the strong constraints corresponding to the latency, bandwidth, and packet loss rate.

[0059] In this embodiment of the invention, there is a clear correspondence between bandwidth occupancy and service quality indicators. When bandwidth occupancy approaches the link capacity limit, increased network congestion leads to increased latency and packet loss rate. In this case, strict constraints on latency and packet loss rate are required to ensure service quality. When bandwidth occupancy is at a low level, the constraints can be appropriately relaxed to reduce operation and maintenance costs. For example, when the bandwidth occupancy of medical imaging services reaches 120Mbps, if the total link capacity is only 100Mbps, there is a resource gap. In this case, latency ≤10ms and packet loss rate ≤0.001% should be set as strong constraints to ensure that any adjustment scheme does not exceed these limits.

[0060] Step 203: Obtain the weight mapping table, and obtain the quality target weight, cost target weight, and energy consumption target weight based on the optical network service data and the weight mapping table; In this embodiment of the invention, the weight mapping table can represent the correspondence between business scenarios, business runtime periods, and the weights of quality targets, cost targets, and energy consumption targets. The quality target weight represents the degree of emphasis on ensuring the quality of business services, the cost target weight represents the degree of emphasis on controlling resource consumption costs, and the energy consumption target weight represents the degree of emphasis on controlling equipment energy consumption. The importance of these three targets varies significantly across different business scenarios. For example, in 5G medical imaging services, quality is crucial to patient safety, so the quality target weight should be dominant; while in nighttime video surveillance services, due to higher service tolerance and idle resources during off-peak hours, cost and energy consumption become the main optimization directions.

[0061] In some embodiments, step 203 may include the following sub-steps: Sub-step S21: Based on the business scenario, determine the corresponding business runtime segment from the fourth mapping relationship included in the weight mapping table; the fourth mapping relationship is the mapping relationship between the business scenario and the business runtime segment. In this embodiment of the invention, different business scenarios correspond to different time period characteristics. Industrial control operations are typically aligned with production line schedules and concentrated during daytime working hours; while multinational enterprise data synchronization operations rely on cross-time zone collaboration windows. Based on the business scenario, the distribution pattern of business runtime periods can be determined.

[0062] Sub-step S22: Based on the service runtime segment, determine the corresponding quality target weight, cost target weight, and energy consumption target weight from the fifth mapping relationship included in the weight mapping table; the fifth mapping relationship is the mapping relationship between the service runtime segment and the quality target weight, the cost target weight, and the energy consumption target weight.

[0063] In this embodiment of the invention, the emphasis on quality, cost, and energy consumption varies for the same service at different times. Taking data center interconnection services as an example, during peak daytime hours, priority should be given to ensuring data transmission quality, and the weight of quality targets should be increased accordingly; while during low-load nighttime hours, more bandwidth resources can be allocated to cost optimization and energy consumption reduction.

[0064] Through the above mapping relationship, the weight mapping table can automatically output weight configurations that are adapted to the current scenario based on the business runtime.

[0065] Step 204: Obtain the business operation and maintenance policy, which includes energy consumption operation and maintenance policy and cost operation and maintenance policy; In this embodiment of the invention, the service operation and maintenance policy can characterize the phased operation and maintenance strategy formulated by the network operator based on macro-management objectives. The energy consumption operation and maintenance policy can characterize the mandatory requirements for energy consumption control within a specific period, such as the constraint of prioritizing energy consumption control during a dual-carbon period, requiring network operation and maintenance to minimize energy consumption while meeting service quality requirements. The cost operation and maintenance policy can characterize the priority orientation of operating cost control within a specific period, such as prioritizing cost control during a cost reduction and efficiency improvement period, requiring the reduction of unnecessary resource expenditures.

[0066] Step 205: Adjust the weight of the energy consumption target according to the energy consumption operation and maintenance policy, and adjust the weight of the cost target according to the cost operation and maintenance policy; In this embodiment of the invention, the operation and maintenance policy directly intervenes in the optimization direction by adjusting the weight ratio. For example, during the implementation of the dual-carbon policy, the optical network resource adjustment system increases the weight of the energy consumption target from 0.2 to 0.3, so that the multi-objective optimization model prioritizes the adjustment path with lower energy consumption when generating the solution; when the cost reduction and efficiency improvement cycle is launched, the weight of the cost target is increased accordingly, and the optical network management and control system tends to use resource reuse to replace high-cost operations such as capacity expansion.

[0067] Step 206: Normalize the weights of the quality target, the cost target, and the energy consumption target proportionally so that the sum of the weights of the quality target, the cost target, and the energy consumption target is 1.

[0068] In this embodiment of the invention, normalization ensures that the three target weights participate in the comprehensive score calculation under the same dimensional scale, avoiding optimization deviations caused by differences in the absolute values ​​of the weights. Specifically, the adjusted weights of the quality target, cost target, and energy consumption target are divided by the sum of the three to obtain the normalized weight values, ensuring that the sum of the three is always 1.

[0069] Step 207: When the business service indicator item has strong constraints and the quality target weight of the business service indicator item is less than the quality weight threshold, the quality target weight is increased to the quality weight threshold. In this embodiment of the invention, the quality weight threshold can represent the minimum quality target weight value required to ensure the quality of business services. This threshold can be preset or configured by operations and maintenance personnel according to the importance of the business. For example, in a 5G medical image transmission scenario, latency ≤10ms is a strong constraint. If the current quality target weight is only 0.2, the multi-objective optimization model may choose an unstable solution with higher latency but still barely meeting the threshold due to a focus on cost or energy consumption. In this case, the quality target weight is automatically increased to 0.5 to ensure that the quality target obtains sufficient optimization driving force in the optimization calculation.

[0070] In some examples, the weight of the quality target in step 207 can be adjusted in sync with the weight of the energy consumption target in step 205, and / or the weight of the cost target. One or two of the three target weights can also be adjusted.

[0071] Step 208: After the quality target weight is increased, the quality target weight, the cost target weight, and the energy consumption target weight are normalized proportionally so that the sum of the quality target weight, the cost target weight, and the energy consumption target weight is 1.

[0072] In this embodiment of the invention, after the weight of the quality target is increased, normalization processing needs to be performed again to ensure that the sum of the three is always 1. For example, if the original weights are quality 0.2, cost 0.4, and energy consumption 0.4, and the quality weight threshold is 0.5, after increasing the quality to 0.5, the sum of the three is 1.3. After normalization, they are 0.385, 0.308, and 0.308 respectively, thus satisfying the constraint that the sum of the weights is 1 again.

[0073] Step 209: Obtain network resource data output by the optical network management and control system; In this embodiment of the invention, network resource data can characterize the status information of the physical and logical resources currently available to the optical network management and control system. Specifically, network resource data includes, but is not limited to, currently available bandwidth, number of idle wavelengths, number of idle ports, unit cost of each expansion device, and real-time power consumption of the devices.

[0074] By acquiring network resource data, embodiments of the present invention can grasp the current real resource inventory and status of the network, providing a data foundation for the generation of subsequent candidate solutions and ensuring that the generated solutions have physical feasibility.

[0075] Step 210: Generate resource adjustment candidate schemes based on the network resource data, the quality target weight, the cost target weight, and the energy consumption target weight; In this embodiment of the invention, the resource adjustment candidate scheme can represent one or more sets of feasible resource adjustment operations. Based on the available resource status in the network resource data, multiple feasible adjustment schemes are generated, covering three gradients: bandwidth adjustment, resource reuse, and capacity expansion.

[0076] In some embodiments, step 210 may further include the following sub-step: in step 211, the network resource data may include the current available bandwidth, the number of idle wavelengths, the number of idle ports, the unit cost of each expansion device, and the real-time energy consumption of the device.

[0077] Sub-step S31: Based on the currently available bandwidth, generate a bandwidth adjustment scheme, which is used to indicate the reallocation of service bandwidth; In this embodiment of the invention, the bandwidth adjustment scheme can represent the operation of dynamically adjusting the service bandwidth based on the currently available bandwidth. When there is room for adjustment in network resources and no new hardware is required, bandwidth adjustment is the lowest-cost and most lightweight optimization method.

[0078] Sub-step S32: Based on the number of idle wavelengths and / or the number of idle ports, generate a resource reuse scheme. The generated resource reuse scheme is used to indicate that the current service traffic is distributed to idle wavelengths and / or idle ports. In this embodiment of the invention, the resource reuse scheme can characterize the operation of using currently idle wavelength channels or port resources in the network to carry service traffic. When the current link bandwidth is insufficient to support service traffic, but there are still idle wavelengths or idle ports in the network, some traffic can be distributed to idle resources to avoid the high costs of direct capacity expansion.

[0079] Sub-step S33: Based on the expansion device, generate an expansion plan, which is used to indicate the addition of boards and / or the expansion of ports.

[0080] In this embodiment of the invention, the capacity expansion scheme can represent the operation of expanding resources by adding physical hardware when bandwidth adjustment and resource reuse cannot meet business needs. For example, adding new boards or expanding ports to improve overall bandwidth capacity. The capacity expansion scheme has the highest cost and energy consumption, but when the business is in a continuous growth cycle and idle resources are exhausted, capacity expansion is the only feasible solution.

[0081] Step 211: Determine the latency, packet loss rate, adjustment equipment cost, and equipment operating power consumption of the optical network management system after adjustment according to the resource adjustment candidate scheme; In this embodiment of the invention, for each candidate scheme generated in step 210, it is necessary to predict and extract its adjusted key indicator values. Among these, latency and packet loss rate reflect the degree of impact of the scheme on service quality, adjusted equipment cost reflects the resource investment required by the scheme, and equipment operating power consumption reflects the impact of the scheme on energy consumption. Taking three candidate schemes as examples: the bandwidth adjustment scheme has an expected latency of 7ms, a cost of 0 yuan, and an energy consumption of 20W; the wavelength multiplexing scheme has an expected latency of 8ms, a cost of 500 yuan / month, and an energy consumption of 18W; and the board expansion scheme has an expected latency of 10ms, a cost of 2800 yuan / month, and an energy consumption of 25W.

[0082] Step 212: Obtain a quality score based on the latency and the packet loss rate, obtain a cost score based on the adjusted equipment cost, and obtain an energy consumption score based on the equipment operating power consumption. In this embodiment of the invention, the quality score characterizes the merits of a candidate solution in terms of service quality, specifically calculated by combining latency and packet loss rate. The cost score characterizes the merits of a candidate solution in terms of resource cost, calculated by adjusting equipment costs. The energy consumption score characterizes the merits of a candidate solution in terms of energy consumption, calculated by the power consumption of the operating equipment.

[0083] For example, the latency score is calculated as follows: when the latency is less than or equal to the QoS threshold, the score is between 0.6 and 1.0; when the latency is greater than the QoS threshold, the score is 0. Specifically, taking a latency threshold of 10ms for medical imaging services as an example, the score for Scheme 1 with a latency of 7ms is (10-7) / (10-7)=1.0, the score for Scheme 2 with a latency of 8ms is (10-8) / (10-7)≈0.667, and the score for Scheme 3 with a latency of 10ms is (10-10) / (10-7)=0.0.

[0084] Step 213: The sum of the product of the quality score and the quality target weight, the product of the cost score and the cost target weight, and the product of the energy consumption score and the energy consumption target weight is determined as the comprehensive score of the resource adjustment candidate scheme. In this embodiment of the invention, the comprehensive score characterizes the overall optimization degree of the candidate solution across the three target dimensions of quality, cost, and energy consumption. The calculation formula is: Comprehensive Score = Quality Score × Quality Target Weight + Cost Score × Cost Target Weight + Energy Consumption Score × Energy Consumption Target Weight. A higher comprehensive score indicates better overall performance of the solution under the current weight configuration.

[0085] Step 214: Sort the resource adjustment candidate schemes from high to low according to their comprehensive scores; In this embodiment of the invention, the comprehensive scores of all candidate solutions calculated in step 213 are sorted in descending order from high to low, and the solution with the highest score is the optimal solution from the perspective of multi-objective optimization. By sorting, the solution with the best comprehensive score is first checked in the subsequent verification process to see if it meets the strong constraints.

[0086] Step 215: Determine the resource adjustment candidate schemes that satisfy the strong constraints as the resource adjustment target schemes; In this embodiment of the invention, the solution with the highest overall score may not necessarily meet the strong constraints of the business service indicators. For example, a low-cost solution may have a high overall score, but its adjusted latency may exceed the threshold range allowed by the business. Therefore, it is necessary to check whether all strong constraint indicators are met one by one, starting with the highest-ranked solution, and determine the first solution that meets all the requirements as the final resource adjustment target solution to be executed.

[0087] In some examples, step 215 may also include the following sub-steps: Sub-step S41: If the currently ranked first solution satisfies the strong constraint condition, then determine that solution as the resource adjustment target solution; For example, in the medical imaging scenario, Option 1 (bandwidth adjustment) has the highest overall score. Its latency is 7ms≤10ms, bandwidth is 120Mbps≥120Mbps, cost is 0 yuan≤3000 yuan, and energy consumption is 20W≤25W. It meets all the strong constraints and Option 1 is directly determined as the target option for resource adjustment.

[0088] Sub-step S42: If the currently ranked first solution does not meet the strong constraint condition, then the strong constraint condition is verified for the next ranked solution, and the resource adjustment candidate solution that meets the strong constraint condition is determined as the resource adjustment target solution.

[0089] If the currently ranked top solution does not meet any of the strong constraints, then that solution is eliminated, and the second-ranked solution is re-verified until the first solution that meets all the strong constraints is found. If none of the candidate solutions meet the strong constraints, then solution reconstruction is triggered, which involves fusing two or more gradients to generate a hybrid solution, such as "bandwidth adjustment + partial resource reuse," and then re-entering the loop from steps 210 to 215 until a solution that meets the requirements is output or the preset maximum number of reconstructions is reached.

[0090] Step 216: Send the resource adjustment target plan to the optical network management system to adjust the resources of the optical network.

[0091] In this embodiment of the invention, according to the resource adjustment target scheme determined in step 215, the corresponding adjustment instructions, such as bandwidth adjustment instructions, resource reuse instructions, or capacity expansion instructions, are output through the control interface of the optical network management system, so that the optical network management system switches from the current state to the resource allocation state indicated by the target scheme.

[0092] In some embodiments, after the adjustment is completed, the actual operating data after the scheme is executed is collected, the deviation between the actual data and the expected value of the scheme is compared, and the comparison results are fed back to the business service quality mapping table and the weight mapping table to optimize the weights and strong constraints of subsequent decisions.

[0093] This invention acquires optical network service data and a service quality of service mapping table output by the optical network management system, as well as network resource data. Based on the optical network service data and the service quality of service mapping table, it obtains multiple service indicators and strong constraints. Then, it generates resource adjustment candidate schemes. After ranking the adjusted latency, packet loss rate, equipment adjustment cost, and equipment operating power consumption of each candidate scheme, it determines the candidate scheme that meets the strong constraints as the resource adjustment target scheme. The optical network management system is then adjusted according to the target scheme. This achieves the ability to identify the true root cause of increased optical network latency through multi-dimensional correlation analysis. When increased traffic leads to increased latency, bandwidth compensation is triggered by verifying the service scenario and runtime. When changes in equipment status lead to increased latency, the service quality of service mapping table excludes traffic growth factors, thereby identifying the physical layer degradation root cause and triggering link optimization operations. This avoids the situation where relying solely on bandwidth occupancy to uniformly trigger capacity expansion leads to misjudging equipment status changes as insufficient bandwidth, resulting in repeated ineffective capacity expansion. This reduces the accumulation of redundant resources and ineffective cost expenditures.

[0094] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0095] Figure 3 This is a scene device diagram of a resource adjustment method for an optical network provided in an embodiment of the present invention.

[0096] like Figure 3 The diagram shown is a scenario device diagram of a resource adjustment method for an optical network provided by an embodiment of the present invention, as detailed below: The resource adjustment scenario of the optical network management and control system provided in this embodiment of the invention includes the following core processes: data preparation stage, multi-objective optimization calculation stage, scheme evaluation and selection stage, and execution and data feedback stage.

[0097] During the data preparation phase, real-time service basic data, network time period data, and real-time network resource data are acquired through the optical network management and control system interface, and combined with traffic prediction results as input parameters. Simultaneously, the system calls the service QoS requirement mapping library (Quality of Service) to determine the corresponding service indicators and strong constraints based on the service type and scenario; it also calls the pre-set weight template library and operation and maintenance policy parameters to determine the initial configuration of quality target weights, cost target weights, and energy consumption target weights. Through service-specific dynamic configuration, target weight configuration results are generated, forming a standardized dataset.

[0098] In the multi-objective optimization calculation phase, based on the real-time network resource data, traffic prediction results, and the weights of quality, cost, and energy consumption objectives in the standardized dataset, multi-objective optimization calculations are performed to generate one or more candidate resource adjustment schemes.

[0099] During the scheme evaluation and selection phase, each scheme in the candidate scheme list is input into the service QoS constraints for verification. Based on the adjusted latency, packet loss rate, adjusted equipment cost, and equipment operating power consumption of each scheme, a quality score, a cost score, and an energy consumption score are calculated respectively. These scores are then weighted and summed with the corresponding target weights to obtain a comprehensive score. After sorting by comprehensive score, the schemes that meet the strong QoS constraints are determined as the target schemes for resource adjustment.

[0100] During the execution and data feedback phase, the network is adjusted through the optical network management system interface according to the resource adjustment target plan, and the adjusted network status data is fed back to the data preparation phase to achieve continuous optimization of optical network resources.

[0101] Figure 4 This is a structural block diagram of a resource adjustment device for an optical network provided in an embodiment of the present invention.

[0102] like Figure 4 As shown in the figure, an embodiment of the present invention provides a resource adjustment device for an optical network, which may specifically include the following modules: The optical network service data acquisition module 301 is used to acquire optical network service data and service quality mapping table output by the optical network management and control system; the optical network service data includes: service scenario, service type, service runtime, and bandwidth usage value. The service service data determination module 302 is used to obtain multiple service service indicators and strong constraints corresponding to the multiple service service indicators based on the optical network service data and the service service quality mapping table. The weight determination module 303 is used to obtain a weight mapping table and to obtain the quality target weight, cost target weight, and energy consumption target weight based on the optical network service data and the weight mapping table. Network resource data acquisition module 304 is used to acquire network resource data output by the optical network management and control system; The candidate solution generation module 305 is used to generate resource adjustment candidate solutions based on the network resource data, the quality target weight, the cost target weight, and the energy consumption target weight. The target solution determination module 306 is used to determine the target solution for resource adjustment based on the candidate solutions for resource adjustment and the strong constraints corresponding to the multiple business service indicator items. The optical network adjustment module 307 is used to send the resource adjustment target scheme to the optical network management system to adjust the resources of the optical network.

[0103] In this embodiment of the invention, the service metrics include latency, bandwidth, and packet loss rate, and the service data determination module includes: The first mapping submodule is used to determine the corresponding service runtime segment from the first mapping relationship included in the service quality mapping table according to the service type; the first mapping relationship is the mapping relationship between the service type and the service runtime segment; The second mapping submodule is used to determine the corresponding bandwidth usage value from the second mapping relationship included in the service quality mapping table according to the service runtime segment; the second mapping relationship is the mapping relationship between the service runtime segment and the bandwidth usage value; The third mapping submodule is used to determine the corresponding latency, bandwidth, and packet loss rate, as well as the strong constraints corresponding to the latency, bandwidth, and packet loss rate, from the third mapping relationship included in the service quality mapping table based on the bandwidth occupancy value; the third mapping relationship is the mapping relationship between the bandwidth occupancy value and the latency, bandwidth, and packet loss rate, as well as the mapping relationship between the strong constraints corresponding to the latency, bandwidth, and packet loss rate.

[0104] In this embodiment of the invention, the weight determination module includes: The fourth mapping submodule is used to determine the corresponding business runtime segment from the fourth mapping relationship included in the weight mapping table according to the business scenario; the fourth mapping relationship is the mapping relationship between the business scenario and the business runtime segment. The fifth mapping submodule is used to determine the corresponding quality target weight, cost target weight, and energy consumption target weight from the fifth mapping relationship included in the weight mapping table according to the service runtime segment; the fifth mapping relationship is the mapping relationship between the service runtime segment and the quality target weight, the cost target weight, and the energy consumption target weight.

[0105] In this embodiment of the invention, the device further includes: The operation and maintenance policy acquisition module is used to acquire business operation and maintenance policies, which include energy consumption operation and maintenance policies and cost operation and maintenance policies. The first weight adjustment module is used to adjust the weight of the energy consumption target according to the energy consumption operation and maintenance policy, and to adjust the weight of the cost target according to the cost operation and maintenance policy; The second weight adjustment module is used to normalize the quality target weight, the cost target weight, and the energy consumption target weight proportionally, so that the sum of the quality target weight, the cost target weight, and the energy consumption target weight is 1.

[0106] In this embodiment of the invention, the device further includes: The third weight adjustment module is used to increase the quality target weight to the quality weight threshold when the business service indicator item has strong constraints and the quality target weight of the business service indicator item is less than the quality weight threshold. The fourth weight adjustment module is used to normalize the quality target weight, the cost target weight, and the energy consumption target weight proportionally after the quality target weight is increased, so that the sum of the quality target weight, the cost target weight, and the energy consumption target weight is 1.

[0107] In this embodiment of the invention, the network resource data includes currently available bandwidth, number of idle wavelengths, number of idle ports, unit cost of each expansion device, and real-time energy consumption of the devices; the target solution determination module includes: The first resource adjustment module is used to generate a bandwidth adjustment scheme based on the currently available bandwidth, and the bandwidth adjustment scheme is used to indicate the reallocation of service bandwidth; And / or, The second resource adjustment module is used to generate a resource reuse scheme based on the number of idle wavelengths and / or the number of idle ports. The generated resource reuse scheme is used to indicate that the current service traffic is distributed to idle wavelengths and / or idle ports. And / or, The third resource adjustment module is used to generate an expansion plan based on the expansion equipment. The expansion plan is used to indicate the addition of boards and / or the expansion of ports.

[0108] In this embodiment of the invention, the target solution determination module includes: The adjustment prediction submodule is used to determine the latency, packet loss rate, adjustment equipment cost, and equipment operating power consumption of the optical network management system after adjustment according to the resource adjustment candidate scheme; The first score determination submodule is used to obtain a quality score based on the latency and the packet loss rate, a cost score based on the adjusted equipment cost, and an energy consumption score based on the equipment operating power consumption. The second score determination submodule is used to determine the comprehensive score of the resource adjustment candidate scheme by summing the product of the quality score and the quality target weight, the product of the cost score and the cost target weight, and the product of the energy consumption score and the energy consumption target weight. The scheme ranking submodule is used to rank the resource adjustment candidate schemes from high to low according to their comprehensive scores. The scheme verification submodule is used to determine the resource adjustment candidate schemes that meet the strong constraints as the resource adjustment target schemes; The scheme verification submodule includes: The first scheme verification unit is used to determine the scheme as the resource adjustment target scheme if the scheme currently ranked first satisfies the strong constraint condition. The second scheme verification unit is used to verify the strong constraint condition for the next scheme if the current first-ranked scheme does not meet the strong constraint condition, and to determine the resource adjustment candidate scheme that meets the strong constraint condition as the resource adjustment target scheme.

[0109] This invention acquires optical network service data and a service quality of service (SHS) mapping table output by the optical network management system, as well as network resource data output by the same system. Based on the optical network service data and SHS mapping table, it obtains multiple service indicators and corresponding strong constraints. Based on network resource data, quality target weights, cost target weights, and energy consumption target weights, it generates candidate resource adjustment schemes. Based on the candidate schemes and the strong constraints corresponding to each service indicator, it determines the target resource adjustment scheme. This achieves multi-dimensional correlation analysis between optical network service data and the SHS mapping table to identify the true root cause of increased optical network latency. When increased traffic leads to increased latency, bandwidth occupancy increases accordingly. This situation is verified and identified through service scenarios and runtime conditions, triggering bandwidth compensation. When changes in device status lead to increased latency, bandwidth occupancy does not change significantly. The SHS mapping table eliminates traffic growth factors, thereby identifying the root cause of physical layer degradation and triggering link optimization. This avoids misjudging device status changes as insufficient bandwidth by relying solely on bandwidth occupancy for unified capacity expansion, leading to repeated ineffective capacity expansion. This reduces redundant resource accumulation and ineffective cost expenditures.

[0110] As the apparatus embodiment is basically similar to the method embodiment, it is described in a relatively simple manner. For relevant details, please refer to the description of the method embodiment.

[0111] This invention also provides an electronic device, including a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, they implement the various processes of the resource adjustment method embodiments of the optical network described above and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0112] It should be noted that the electronic devices in the embodiments of the present invention include the mobile electronic devices and non-mobile electronic devices described above.

[0113] This invention also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described optical network resource adjustment method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0114] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0115] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0116] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0118] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0120] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0121] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device 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 terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0122] The resource adjustment method, apparatus, electronic device, and computer-readable storage medium for an optical network provided by the present invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A resource adjustment method for an optical network, characterized in that, include: Obtain the optical network service data and service quality mapping table output by the optical network management and control system; The optical network service data includes: service scenario, service type, service runtime, and bandwidth usage. Based on the optical network service data and the service quality mapping table, multiple service indicators and corresponding strong constraints are obtained. Obtain the weight mapping table, and based on the optical network service data and the weight mapping table, obtain the quality target weight, cost target weight, and energy consumption target weight; Acquire network resource data output by the optical network management and control system; Based on the network resource data, the quality target weight, the cost target weight, and the energy consumption target weight, a resource adjustment candidate scheme is generated; Based on the candidate resource adjustment schemes and the strong constraints corresponding to the multiple business service indicator items, the target resource adjustment scheme is determined; The resource adjustment target plan is sent to the optical network management system to adjust the resources of the optical network.

2. The resource adjustment method for an optical network according to claim 1, characterized in that, The service metrics include latency, bandwidth, and packet loss rate. The process of obtaining multiple service metrics and corresponding strong constraints based on the optical network service data and the service quality mapping table includes: Based on the service type, the corresponding service runtime segment is determined from the first mapping relationship included in the service quality mapping table; the first mapping relationship is the mapping relationship between the service type and the service runtime segment. Based on the service runtime segment, the corresponding bandwidth usage value is determined from the second mapping relationship included in the service quality mapping table; the second mapping relationship is the mapping relationship between the service runtime segment and the bandwidth usage value. Based on the bandwidth occupancy value, the corresponding latency, bandwidth, and packet loss rate are determined from the third mapping relationship included in the service quality mapping table, as well as the strong constraints corresponding to the latency, bandwidth, and packet loss rate; the third mapping relationship is the mapping relationship between the bandwidth occupancy value and the latency, bandwidth, and packet loss rate, as well as the mapping relationship between the strong constraints corresponding to the latency, bandwidth, and packet loss rate.

3. The resource adjustment method for an optical network according to claim 1, characterized in that, The process of obtaining the weight mapping table, which involves deriving the quality target weight, cost target weight, and energy consumption target weight based on the optical network service data and the weight mapping table, includes: Based on the business scenario, the corresponding business runtime segment is determined from the fourth mapping relationship included in the weight mapping table; the fourth mapping relationship is the mapping relationship between the business scenario and the business runtime segment. Based on the service runtime segment, the corresponding quality target weight, cost target weight, and energy consumption target weight are determined from the fifth mapping relationship included in the weight mapping table; the fifth mapping relationship is the mapping relationship between the service runtime segment and the quality target weight, the cost target weight, and the energy consumption target weight.

4. The resource adjustment method for an optical network according to claim 1, characterized in that, The method further includes: Obtain business operation and maintenance policies, including energy consumption operation and maintenance policies and cost operation and maintenance policies; The weight of the energy consumption target is adjusted according to the energy consumption operation and maintenance policy, and the weight of the cost target is adjusted according to the cost operation and maintenance policy; The weights of the quality target, the cost target, and the energy consumption target are normalized proportionally so that the sum of the weights of the quality target, the cost target, and the energy consumption target is 1.

5. The resource adjustment method for an optical network according to claim 1, characterized in that, The method further includes: When the business service indicator has strong constraints and the quality target weight of the business service indicator is less than the quality weight threshold, the quality target weight is increased to the quality weight threshold. After the quality target weight is increased, the quality target weight, the cost target weight, and the energy consumption target weight are normalized proportionally so that the sum of the quality target weight, the cost target weight, and the energy consumption target weight is 1.

6. The resource adjustment method for an optical network according to claim 1, characterized in that, The network resource data includes currently available bandwidth, number of idle wavelengths, number of idle ports, unit cost of each expansion device, and real-time energy consumption of the devices; the process of determining the target resource adjustment scheme based on the candidate resource adjustment schemes and the strong constraints corresponding to the multiple service indicators includes: Based on the currently available bandwidth, a bandwidth adjustment scheme is generated, which is used to indicate the reallocation of service bandwidth; And / or, Based on the number of idle wavelengths and / or the number of idle ports, a resource reuse scheme is generated, which is used to indicate that the current service traffic is distributed to idle wavelengths and / or idle ports; And / or, Based on the expansion equipment, an expansion plan is generated, which is used to indicate the addition of boards and / or the expansion of ports.

7. The resource adjustment method for an optical network according to claim 1, characterized in that, The step of determining the target resource adjustment plan based on the candidate resource adjustment plans and the strong constraints corresponding to the multiple business service indicator items includes: Determine the latency, packet loss rate, equipment cost, and equipment power consumption of the optical network management system after adjustment according to the resource adjustment candidate scheme; A quality score is obtained based on the latency and the packet loss rate; a cost score is obtained based on the adjusted equipment cost; and an energy consumption score is obtained based on the equipment operating power consumption. The sum of the product of the quality score and the quality target weight, the product of the cost score and the cost target weight, and the product of the energy consumption score and the energy consumption target weight is determined as the comprehensive score of the resource adjustment candidate scheme. The resource adjustment candidate schemes are ranked from highest to lowest based on their comprehensive scores. The resource adjustment candidate schemes that satisfy the aforementioned strong constraints are determined as the resource adjustment target schemes; The step of determining the resource adjustment candidate schemes that satisfy the strong constraints as the resource adjustment target scheme includes: If the currently ranked top solution satisfies the aforementioned strong constraint condition, then that solution is determined as the target solution for resource adjustment. If the currently ranked first solution does not meet the strong constraint condition, then the strong constraint condition is verified for the next ranked solution, and the resource adjustment candidate solution that meets the strong constraint condition is determined as the resource adjustment target solution.

8. A resource adjustment device for an optical network, characterized in that, include: The optical network service data acquisition module is used to acquire optical network service data and service quality mapping table output by the optical network management and control system; The optical network service data includes: service scenario, service type, service runtime, and bandwidth usage. The service service data determination module is used to obtain multiple service service indicators and strong constraints corresponding to the multiple service service indicators based on the optical network service data and the service service quality mapping table. The weight determination module is used to obtain a weight mapping table and to obtain the quality target weight, cost target weight, and energy consumption target weight based on the optical network service data and the weight mapping table. The network resource data acquisition module is used to acquire network resource data output by the optical network management and control system; The candidate solution generation module is used to generate resource adjustment candidate solutions based on the network resource data, the quality target weight, the cost target weight, and the energy consumption target weight. The target solution determination module is used to determine the target solution for resource adjustment based on the candidate solutions for resource adjustment and the strong constraints corresponding to the multiple business service indicator items. The optical network adjustment module is used to send the resource adjustment target plan to the optical network management system to adjust the resources of the optical network.

9. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory, which, when executed by the processor, implement the resource adjustment steps of the optical network as described in claims 1-7.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the resource adjustment steps of the optical network according to claims 1-7.

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