Gateway service integrated management method and system based on FTTR demand

Abstract

The invention relates to the technical field of data processing, and discloses a gateway service integrated management method and system based on an FTTR demand. The method comprises the following steps: carrying out topology scanning on a test signal of an optical time domain reflectometer to obtain a room-level FTTR topology mapping table, carrying out feature extraction on service traffic of each room according to deep packet inspection to obtain a room function identification tag library, and carrying out attenuation compensation on a corresponding room optical port by an optical power meter to obtain an FTTR link quality evaluation matrix, and bandwidth allocation is carried out through a reinforcement learning algorithm to obtain a room-level QoS strategy configuration set, and building data interaction is carried out based on an MQTT protocol to obtain an FTTR gateway service integrated management scheme. According to the invention, the intelligent level of FTTR network room-level management and the resource allocation efficiency are improved. According to the invention, the real-time performance of optical fiber link quality monitoring and the collaboration of building network management are improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a gateway service integrated management method and system based on FTTR requirements. Background Art

[0002] Existing FTTR (Fiber to the Room) network management technologies primarily utilize traditional centralized gateway management, uniformly configuring and monitoring fiber access ports in all rooms through a single network management protocol. These technologies typically rely on the SNMP protocol or dedicated network management interfaces to collect basic operational status information for network devices and employ static bandwidth allocation strategies to configure fixed network resources for each room. Existing solutions primarily rely on regular manual inspections and simple connectivity tests for fiber link monitoring. They lack the ability to automatically identify room functional characteristics for service identification and rely on coarse-grained, port-based QoS policy configuration for service quality assurance.

[0003] However, existing technologies have significant shortcomings, primarily lacking refined room-level network topology awareness, an inability to accurately identify the specific functional types and service characteristics of each room, and a lack of differentiated service quality assurance mechanisms based on room functions. Traditional fiber link monitoring methods cannot detect optical power attenuation and transmission quality changes in real time. Static bandwidth allocation strategies cannot dynamically adjust to the actual service needs of the room, and centralized configuration management methods lack effective integration with intelligent building management systems. These technical limitations lead to inefficient management of FTTR networks in complex multi-room environments and an inability to meet the personalized network service requirements of different rooms.

[0004] Existing technologies lack the ability to automatically build room-level fiber network topologies, making it impossible to intelligently identify and classify service traffic based on room functional characteristics. This directly leads to a lack of targeted fiber link quality assessment and dynamic compensation mechanisms. Ultimately, network resource allocation cannot be intelligently adjusted based on the actual needs and priorities of the rooms, and there is also a lack of integrated data interaction capabilities with building management systems. Therefore, there is an urgent need for a comprehensive solution that can achieve automatic discovery of room-level FTTR network topology, intelligent identification of service characteristics based on room functions, adaptive compensation for fiber link quality, intelligent bandwidth resource allocation, and collaborative building-level data management. Summary of the Invention

[0005] This application provides a gateway service integrated management method and system based on FTTR requirements, which is used to improve the intelligence level and resource allocation efficiency of FTTR network room-level management. This application improves the real-time performance of optical fiber link quality monitoring and the coordination of building network management.

[0006] In the first aspect, the present application provides a gateway service integrated management method based on FTTR requirements, and the gateway service integrated management method based on FTTR requirements includes: performing topology scanning processing on the optical ports of each room through the optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table; performing feature extraction processing on the service traffic of each room in the room-level FTTR topology mapping table according to deep packet inspection to obtain a room function identification label library; performing attenuation compensation processing on the optical port of the room corresponding to the room function identification label library by the optical power meter to obtain an FTTR link quality assessment matrix; performing bandwidth allocation processing on each room according to the FTTR link quality assessment matrix through a reinforcement learning algorithm to obtain a room-level QoS policy configuration set; performing building data interaction processing on the room-level QoS policy configuration set based on the MQTT protocol to obtain an FTTR gateway service integrated management plan.

[0007] In a second aspect, the present application provides a gateway service integrated management system based on FTTR requirements, the gateway service integrated management system based on FTTR requirements comprising: The scanning module is used to perform topology scanning on the optical ports of each room using the optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table; An extraction module is used to perform feature extraction processing on the service traffic of each room in the room-level FTTR topology mapping table according to deep packet inspection to obtain a room function identification label library; A compensation module is used to perform attenuation compensation processing on the optical port of the room corresponding to the room function identification tag library by the optical power meter to obtain an FTTR link quality evaluation matrix; an allocation module, configured to perform bandwidth allocation processing on each room according to the FTTR link quality evaluation matrix through a reinforcement learning algorithm to obtain a room-level QoS policy configuration set; The interaction module is used to perform building data interaction processing on the room-level QoS policy configuration set based on the MQTT protocol to obtain a comprehensive management solution for FTTR gateway services.

[0008] In the third aspect, a gateway service integrated management device based on FTTR demand is provided, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the gateway service integrated management device based on FTTR demand executes the above-mentioned gateway service integrated management method based on FTTR demand.

[0009] In a fourth aspect, a computer-readable storage medium is provided, wherein instructions are stored in the computer-readable storage medium, which, when executed on a computer, enables the computer to execute the above-mentioned method for integrated management of gateway services based on FTTR requirements.

[0010] In the technical solution provided by this application, the optical ports of each room are topologically scanned and processed by the optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table, which solves the problem of the inability to automatically construct a room-level network topology in the existing technology, realizes the accurate identification of the physical connection relationship of the FTTR network and the accurate positioning of the spatial position, and lays the foundation for subsequent personalized management. According to deep packet inspection, the service traffic of each room in the room-level FTTR topology mapping table is feature extracted and processed to obtain a room function identification label library, breaking through the technical bottleneck of the lack of automatic identification capability of room functions in traditional network management. Through intelligent service traffic analysis and clustering algorithms, accurate classification of rooms with different functions such as conference rooms, offices, and public areas is achieved, providing a scientific basis for differentiated services. The optical power meter is used to perform attenuation compensation processing on the optical ports of the room corresponding to the room function identification label library and obtain the FTTR link quality evaluation matrix, which effectively solves the problems of signal attenuation and quality degradation during optical fiber transmission. Through real-time optical power monitoring and automatic gain adjustment, dynamic optimization of link quality is achieved, ensuring the stability of signal transmission in rooms with different functions. Through the reinforcement learning algorithm, bandwidth allocation is processed for each room according to the FTTR link quality evaluation matrix and a room-level QoS policy configuration set is obtained. This overcomes the limitation of static bandwidth allocation strategy that cannot adapt to dynamic business needs, realizes intelligent resource allocation based on room function and link quality, and significantly improves network resource utilization efficiency and user experience satisfaction.

[0011] This application achieves the optimal allocation of bandwidth resources through a state-action-reward decision-making framework. The self-learning and adaptive characteristics of the algorithm enable the network management strategy to be continuously optimized as the environment changes. Based on the MQTT protocol, the room-level QoS policy configuration set is processed for building data interaction and a comprehensive management solution for FTTR gateway services is obtained, achieving seamless integration of gateway devices and building intelligent management systems. Through standardized message transmission and real-time configuration synchronization mechanisms, the problem of information islands in traditional network management is solved, and a unified building-level network management platform is established. The entire technical solution forms a complete technical chain from physical layer topology discovery, business layer function identification, transport layer quality assurance, network layer resource allocation to management layer collaborative control, realizing all-round intelligent management of FTTR networks and providing efficient and reliable network infrastructure management solutions for smart buildings and digital office environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 This is a schematic diagram of an embodiment of a method for integrated gateway service management based on FTTR requirements in an embodiment of the present application; Figure 2 This is a schematic diagram of an embodiment of a gateway service integrated management system based on FTTR requirements in an embodiment of the present application; Figure 3 This is a schematic block diagram of the structure of a gateway service integrated management device based on FTTR requirements in an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The embodiments of the present application provide a method and system for integrated management of gateway services based on FTTR requirements. The terms "first," "second," "third," "fourth," and so on (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this way are interchangeable where appropriate so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0015] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In the embodiment of the present application, an embodiment of the gateway service integrated management method based on FTTR requirements includes: Step S101: Perform topology scanning on the optical ports of each room using an optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table; Step S102: performing feature extraction processing on the service traffic of each room in the room-level FTTR topology mapping table according to deep packet inspection to obtain a room function identification tag library; Step S103: Using an optical power meter to perform attenuation compensation processing on the optical port of the room corresponding to the room function identification tag library to obtain an FTTR link quality evaluation matrix; Step S104: bandwidth allocation is performed on each room according to the FTTR link quality evaluation matrix using a reinforcement learning algorithm to obtain a room-level QoS policy configuration set; Step S105: Based on the MQTT protocol, the room-level QoS policy configuration set is processed for building data interaction to obtain a comprehensive management solution for FTTR gateway services.

[0016] It is understandable that the execution subject of this application can be a gateway service integrated management system based on FTTR requirements, or a terminal or a server, which is not limited here. The embodiment of this application is described by taking the server as the execution subject as an example.

[0017] Specifically, the optical time-domain reflectometer (OTDR) test signal operates by transmitting a light pulse into an optical fiber. When the optical signal encounters a joint, bend, breakpoint, or impedance mismatch during fiber transmission, it generates backscattered light. The delay and intensity of these reflected light signals are then measured to analyze the physical properties of the optical fiber. The optical fiber physical link parameter set includes reflection delay and reflection intensity parameters. The reflection delay parameter directly reflects the propagation time of the optical signal in the fiber. Combined with the propagation speed of light in the fiber, the actual fiber length is calculated. The room optical link length data table records the fiber length information for each room's corresponding optical port. The transmission distance parameter takes into account the fiber's bend radius and the actual cabling path. The room spatial distribution coordinate matrix converts transmission distances into relative coordinate positions, establishing a spatial relationship model for the rooms within the building. The port-room mapping database associates the physical identifiers of optical ports with room numbers in a one-to-one correspondence, forming a search index structure. The topology construction process integrates the connectivity, distance information, and port mapping relationships of each room into a network topology map, ultimately generating a room-level FTTR topology mapping table that includes room location, connection path, and network hierarchy.

[0018] Deep packet inspection technology identifies service types by parsing the protocol headers and application-layer payloads of network packets. Protocol parsing extracts network-layer information such as the source address, destination address, port number, and protocol type. Application-layer payload extraction analyzes packet content features, including HTTP request type, video encoding format, and file transfer protocol. The room traffic feature vector collection converts each room's traffic data into a multidimensional feature vector, including a traffic type distribution vector, bandwidth usage pattern vector, and time distribution vector. Statistical analysis calculates traffic statistics for each room over different time windows, such as average bandwidth utilization, peak traffic times, and service type ratios, to generate data on room network usage patterns. Clustering uses a distance-based clustering method to group rooms with similar traffic characteristics into the same category, with cluster centers representing typical room functional characteristics. Based on the clustering results, room functional classification is performed to categorize rooms into conference room, office, and public area types. A function label dictionary contains predefined room function labels and their corresponding traffic feature thresholds. Matching and mapping determines the room function label by calculating the similarity between the room traffic features and the label features. The room function identification label sequence records the function label and confidence score corresponding to each room. The label library is constructed to establish an index structure for the label information of all rooms according to the room number.

[0019] The real-time optical power level detection process uses an optical power meter to measure the received optical power of each room's optical port, generating a room optical port power monitoring data set. The deviation calculation process compares the measured optical power values ​​with the standard optical power threshold for that type of optical port, calculating the absolute and relative values ​​of the power deviation. The optical power deviation parameter table records the power deviation value, deviation direction, and over-limit status of each room's optical port. The automatic optical transmit power gain adjustment process calculates the required power compensation based on the magnitude and direction of the power deviation and changes the optical output power by adjusting the optical transmitter's drive current. The link parameters after optical power compensation include adjusted optical power, optical signal-to-noise ratio, bit error rate, and other optical link quality indicators. The comprehensive quality score calculation process weights and sums the optical power parameters, fiber insertion loss, and transmission loss values ​​according to weight coefficients to determine the comprehensive quality score for each room's optical port. The room optical port quality score data records the quality score and quality grade classification of each room's optical port. The matrix arrangement process arranges the room quality scores into a two-dimensional array based on the room row index and port column index. The index construction process establishes a fast search mechanism for matrix elements.

[0020] The reinforcement learning algorithm uses a state-action-reward decision-making framework to optimize bandwidth allocation strategies. The association mapping process multiplies the room quality score from the FTTR link quality evaluation matrix with the priority weight from the room function identification tag library to generate a room bandwidth demand state vector that comprehensively considers both quality and function. The reinforcement learning environment state space includes environmental parameters such as the current total network bandwidth capacity, historical bandwidth usage by room, and real-time traffic load. The value function calculation process evaluates the impact of different bandwidth allocation actions on overall network performance and measures the effectiveness of allocation strategies through cumulative rewards. The room bandwidth allocation strategy decision sequence determines each room's bandwidth quota and service priority level. The QoS parameter configuration process sets appropriate quality of service parameters based on the room function type and bandwidth allocation results, including minimum guaranteed bandwidth, maximum allowed bandwidth, packet priority, and latency tolerance. The room personalized quality of service parameter set records the specific QoS configuration parameters for each room. The reward function evaluation process calculates the reward score for the current allocation strategy based on network performance monitoring data and user experience feedback, generating policy optimization instructions to improve the next round of allocation decisions. The configuration integration process integrates the QoS parameters of each room into a unified configuration data structure, and the policy encapsulation process encapsulates the configuration parameters in a standard format.

[0021] JSON serialization and encapsulation converts room-level QoS policy parameters into a standard JSON data format, including fields for information such as room identification, bandwidth quota, priority settings, and service parameters. The MQTT message payload data packet constructs a message header and payload according to the MQTT protocol specification. The message header contains control information such as the topic name, message type, and quality of service level. The building network's topic subscription mechanism establishes a topic-based publish-subscribe communication model. Gateway devices act as publishers, sending configuration messages to specific topics, and the building management center, as a subscriber, receives messages on these topics. The publish-subscribe process implements message routing and status management through an MQTT proxy server. The building data exchange communication link establishes a bidirectional communication channel between the gateway and the management center, supporting configuration distribution and status reporting. Real-time synchronization ensures consistency between the gateway's local configuration and the configuration information in the management center's database, detecting configuration changes through version numbers and timestamps. Gateway configuration status feedback data includes configuration execution results, error messages, device status, and other feedback. Consistency verification verifies data integrity by comparing the local configuration hash with the remote configuration hash. Policy execution status verification results record the correctness and validity of the configuration. The solution integration process integrates the network management strategies, service quality configurations, monitoring data and other information of each room, and the management strategy generation process generates a network management solution document based on the integration results.

[0022] In a specific embodiment, the process of executing step S101 may specifically include the following steps: Send optical pulse test signals to the optical ports of each room, detect the reflection delay and reflection intensity parameters of the optical signal, and obtain the optical fiber physical link parameter set; Calculate the fiber length and transmission distance based on the reflection delay parameter in the fiber physical link parameter set, and obtain a room fiber link length data table; Map the geographical location of each room based on the transmission distance in the room optical fiber link length data table to obtain the room space distribution coordinate matrix; Associating and binding the room space distribution coordinate matrix with the optical port identifier to obtain a port-room mapping relationship database; A topology structure is constructed on the port-room mapping relationship database to obtain a room-level FTTR topology mapping table.

[0023] Specifically, the optical pulse test signal is sent by the optical time domain reflectometer in the gateway device, which injects narrow pulse laser signals into the optical ports of each room. When these optical pulses propagate through the optical fiber, they encounter optical fiber joints, connectors, bending points, or impedance mismatches, generating Rayleigh scattering and Fresnel reflection. The reflected optical signal returns to the receiving end of the optical time domain reflectometer along the original path. The reflection delay parameter is obtained by measuring the time difference between the moment the optical pulse is emitted and the moment the reflected optical signal is received. The reflection intensity parameter is determined by converting the reflected optical signal into an electrical signal using a photodetector and measuring its amplitude. The optical fiber physical link parameter set stores the reflection delay value, reflection intensity value, optical fiber type identifier, connector type, and other information corresponding to each room's optical port in a structured manner, forming a multidimensional data set containing room number, port identifier, delay data, and intensity data.

[0024] Fiber length calculation is based on the product of the speed of light in the fiber and the reflection delay. Since optical signals require round-trip propagation, the actual fiber length is equal to the speed of light multiplied by the reflection delay, divided by twice the fiber's refractive index. Transmission distance calculations must consider the actual fiber installation path, including factors such as bends, detours, and redundant length within the duct. The actual transmission distance is determined by multiplying the calculated fiber length by the path correction factor. The room fiber link length data table indexes each room's fiber length, transmission distance, path loss, connection loss, and other parameters by room number, establishing a correspondence between room identifiers and physical fiber parameters.

[0025] Geolocation mapping converts transmission distance data into the relative spatial location of rooms within a building. By establishing a coordinate system with the gateway device as the origin, the coordinate location of each room is determined based on the main and branch paths of the fiber optic cabling. Rooms with shorter transmission distances are determined to be closer to the gateway device, while rooms with longer transmission distances are determined to be farther away. The coordinate calculation results are also corrected based on the building's structural information and fiber optic cabling drawings. The room spatial distribution coordinate matrix uses a two-dimensional coordinate system, with the X-axis representing the room's horizontal position and the Y-axis representing the room's vertical position or floor level. Each room occupies a coordinate point in the matrix, and the coordinate value is calculated based on the transmission distance and cabling path.

[0026] The association and binding process establishes a one-to-one data association between the coordinate information in the room spatial distribution coordinate matrix and the optical port identifier. The optical port identifier contains information such as the port's physical number, port type, and interface specifications. This binding process is achieved by establishing a lookup table whose primary key is the room coordinates and whose foreign key is the optical port identifier. The lookup table also records the binding timestamp and data source. The port-room mapping database utilizes a relational data structure and consists of three basic tables: the room table, the port table, and the mapping table. The room table stores information such as room number, coordinate location, and room type. The port table stores information such as port identifier, port status, and technical specifications. The mapping table stores the correspondence between room numbers and port identifiers.

[0027] The topology construction process generates a network topology diagram based on the association information in the port-room mapping database. The topology diagram uses a node-edge graph structure to represent the connection relationships between rooms. Each room is represented as a node in the graph, with node attributes including room number, coordinate location, and port information. Fiber connections are represented as edges in the graph, with edge attributes including transmission distance, link quality, and bandwidth capacity. The topology construction algorithm traverses all records in the mapping database and determines parent-child and sibling relationships between rooms based on the fiber trunk-branch structure, establishing a hierarchical topology. The room-level FTTR topology mapping table stores the constructed topology in a standardized format, including information such as node lists, edge lists, topology levels, and connection paths, forming a room-level fiber optic network topology description.

[0028] In a specific embodiment, the process of executing step S102 may specifically include the following steps: Perform protocol parsing and application layer payload extraction on the network data packets of each room in the room-level FTTR topology mapping table to obtain a set of room service traffic feature vectors; Perform statistical analysis based on the traffic type distribution and bandwidth occupancy pattern in the room service traffic feature vector set to obtain room network usage behavior pattern data; Based on the time window traffic change curve in the room network usage behavior pattern data, cluster calculation processing is performed to obtain the room function type classification result; Match and map the room function type classification results with the preset function label dictionary to obtain the room function identification label sequence; The room function identification tag sequence is subjected to tag library construction and index establishment processing to obtain a room function identification tag library.

[0029] Specifically, protocol parsing extracts key information by stripping the protocol headers layer by layer from network packets. It first parses the Ethernet frame header to obtain the source and destination MAC addresses, identifying the packet's sender and receiver. It then parses the IP header to obtain network-layer information such as the source and destination IP addresses, protocol type, and packet length. It then parses the TCP or UDP header to obtain transport-layer information such as the source and destination port numbers, sequence number, and window size. Application-layer payload extraction analyzes the application-layer content of the packet, identifying the client type by identifying the User-Agent field in the HTTP request header, identifying the type of website being accessed by parsing the URL path in the HTTP request, and identifying the encoding format of the audio and video streams by analyzing the payload type in the RTP packet. The room traffic feature vector collection converts each room's network traffic data into a structured multidimensional vector. Each dimension of the vector represents a service characteristic, including HTTP traffic share, video traffic share, file transfer traffic share, real-time communication traffic share, average packet size, and number of concurrent connections. Each room corresponds to a feature vector, and the values ​​in the vector are calculated by counting the room's traffic data within a specific time window. Statistical analysis processes data from a room's service traffic feature vector set through mathematical calculations to identify traffic patterns. Traffic type distribution analysis determines the room's primary service type by calculating the percentage of each service type's total traffic. Bandwidth usage pattern analysis identifies peak and low-peak periods by calculating bandwidth usage over different time periods. Room network usage behavior pattern data records typical room usage characteristics, including time-related behavioral features such as weekday and weekend traffic patterns, daytime and nighttime traffic trends, and static features such as service type preferences, bandwidth demand levels, and network access habits.

[0030] Clustering calculations employ an unsupervised learning method based on distance metrics to group rooms with similar network usage into the same category. A time window traffic curve depicts the trajectory of traffic changes in a room over a continuous period of time, with the horizontal axis representing a point in time and the vertical axis representing the traffic volume at that point in time. The clustering algorithm first calculates the Euclidean distance between the traffic curves of any two rooms, reflecting the degree of similarity in their network usage patterns. Then, through an iterative optimization process, rooms with close proximity are grouped into the same cluster center, ultimately forming several clusters, each representing a typical room function type. The room function type classification results record each room's cluster number and the distance between the room and the cluster center. A smaller distance value indicates a room that more closely matches the typical characteristics of that function type.

[0031] The matching mapping process associates the room function types derived from clustering with a preset dictionary of function labels. The dictionary contains predefined room function categories such as conference room, office, public area, and server room. Each label corresponds to a set of typical network usage characteristics. The mapping process determines the best match by comparing traffic characteristics from the clustering results with the characteristics in the label dictionary. When the traffic characteristics of a cluster have the highest similarity with the characteristics of the conference room label, all rooms in that cluster are labeled as conference room type. The room function identification label sequence records the function label and matching confidence score for each room in order of room number. The confidence score is calculated by calculating the similarity between the room characteristics and the label characteristics. A higher score indicates a more accurate label assignment. The label library construction process converts the room function identification label sequence into a database structure that is easy to query and manage. The label library stores data in key-value pairs, with the primary key being the room identifier and the value being a data record containing information such as the function label, confidence score, assignment time, and update time. The indexing process creates multiple query indexes for the tag library, including a primary index for room number queries, a secondary index for function tag queries, and a filtered index for confidence range queries. The index structure uses a B-tree or hash table to support fast retrieval. The room function identification tag library integrates the function tag information of all rooms to form a room function mapping dataset, and also records historical changes and statistics of tag assignments.

[0032] In a specific embodiment, the process of executing step S103 may specifically include the following steps: Based on the function label of each room in the room function identification label library, the optical power level of the corresponding optical port is detected in real time to obtain the room optical port power monitoring data set; The optical power deviation parameter table is obtained by calculating the deviation between the received optical power value in the room optical port power monitoring data set and the standard optical power threshold; Automatically adjust the optical transmit power gain for the deviation values ​​exceeding the preset range in the optical power deviation parameter table to obtain the link parameters after optical power compensation; The link parameters after optical power compensation are combined with the fiber insertion loss and transmission loss to perform comprehensive quality scoring calculations to obtain the room optical port quality score data; Based on the room optical port quality score data, matrix arrangement and index construction processing are performed to obtain the FTTR link quality evaluation matrix.

[0033] Specifically, the real-time optical power level detection process determines the corresponding optical power monitoring strategy based on the room function type recorded in the room function identification tag library. For rooms marked as conference rooms, the detection frequency is set to 10 times per second to ensure the stability of video conferencing services. For rooms marked as offices, the detection frequency is set to 5 times per second to balance monitoring accuracy and resource consumption. For rooms marked as public areas, the detection frequency is set to 2 times per second to meet basic monitoring needs. Optical power detection uses an optical power meter to measure the intensity of the optical signal received by the optical port. The optical power meter converts the optical signal into a corresponding electrical signal, which is then converted into a digital signal for processing using an analog-to-digital converter. The room optical port power monitoring dataset records the optical power measurement values ​​of each room at different time points. The data structure contains fields such as room identifier, port number, timestamp, optical power value, signal quality index, and records the changing trends and abnormal fluctuations of optical power. The deviation calculation compares the measured optical power value with the standard optical power threshold corresponding to the room's functional type. The standard optical power threshold is set based on the business requirements of each room type. For conference rooms requiring higher signal quality, the standard threshold is set at -12dBm, for offices at -15dBm, and for public areas at -18dBm. The deviation value is calculated by subtracting the standard threshold from the measured optical power value. A positive deviation indicates that the optical power is above the standard value, while a negative deviation indicates that the optical power is below the standard value. The optical power deviation parameter table records the deviation value, direction, magnitude, and duration of each room's optical port. It also marks abnormal ports that exceed the preset deviation range. The preset deviation range is determined by the fault tolerance requirements of the room's functional type: the allowable deviation range for conference rooms is ±1dB, for offices is ±2dB, and for public areas is ±3dB.

[0034] Automatic optical transmit power gain adjustment compensates for optical ports that exceed a preset deviation range. The adjustment algorithm calculates the required power adjustment based on the magnitude and direction of the deviation. When the optical power is low, the transmitter's drive current is increased to increase output power. When the optical power is high, the drive current is reduced to reduce output power. The power adjustment step size is determined by the deviation magnitude: small deviations use a fine adjustment step of 0.5dB, medium deviations use a standard step of 1dB, and large deviations use a coarse adjustment step of 2dB. The link parameters after optical power compensation include the adjusted optical power value, optical signal-to-noise ratio (OSNR), bit error rate (BER), and link stability index. These parameters are obtained by re-measuring the signal quality of the optical port to ensure that the power adjustment achieves the expected effect. The comprehensive quality score calculation process combines the compensated link parameters with fiber insertion loss and transmission loss data. Fiber insertion loss data is derived from physical measurements of optical connectors, including connector insertion loss, splice loss, and bend loss. Transmission loss data is calculated based on the attenuation coefficient of fiber length and fiber type. The quality scoring algorithm uses a weighted summation approach, assigning 40% weight to optical power, 30% to fiber insertion loss, 20% to transmission loss, and 10% to signal stability. Each parameter value is normalized and then weighted. The room optical port quality score data records the overall quality score, quality grade classification, and quality trend of each room's optical port. The quality grade is divided into four levels: excellent, good, fair, and poor, corresponding to score ranges of above 90, 70 to 90, 50 to 70, and below 50, respectively.

[0035] The matrix arrangement process arranges the optical port quality scores for each room into a two-dimensional array based on room and port numbers. The row index of the matrix represents the room number, the column index represents the port number, and the matrix elements store the quality score values ​​for the corresponding room and port. The index construction process creates multidimensional query indexes for the quality assessment matrix, including row indexes for room number queries, column indexes for port number queries, category indexes for quality level queries, and interval indexes for score range queries. The FTTR link quality assessment matrix integrates the quality information of all room optical ports to form a description of the network quality status. The matrix structure supports rapid retrieval of the quality status of a specific room or port, while also recording the timestamps and historical changes of the quality assessment.

[0036] In a specific embodiment, the process of automatically adjusting the optical transmission power gain for the deviation value exceeding the preset range in the optical power deviation parameter table may specifically include the following steps: Perform numerical comparison processing on the deviation values ​​in the optical power deviation parameter table and the preset optical power deviation threshold range to obtain a list of excessive deviation value marks; Calculate the optical transmission power gain compensation amount based on the deviation degree of each room in the over-limit deviation value mark list to obtain the room-level power gain adjustment parameter; Inputting the room-level power gain adjustment parameter into the optical transmitter to dynamically adjust the power output level to obtain the compensated optical transmission power value; The signal transmission quality of the optical port in each room is re-measured based on the compensated optical transmission power value to obtain the optical link transmission parameters after power compensation; Parameter integration and data structuring are performed on the optical link transmission parameters after power compensation to obtain the link parameters after optical power compensation.

[0037] Specifically, the numerical comparison process compares the deviation value of each room's optical port, as recorded in the optical power deviation parameter table, against the preset optical power deviation threshold range for the corresponding room's function type. The preset optical power deviation threshold range is set based on the room's service characteristics and service quality requirements: the threshold range for conference rooms is ±1dB, for offices is ±2dB, and for public areas is ±3dB. A comparison algorithm traverses all records in the deviation parameter table, determining whether each deviation value exceeds its corresponding threshold range boundary. When the absolute value of the deviation value exceeds the upper limit of the threshold range, the record is marked as out of limit. An out-of-limit deviation value flag list records information on all room optical ports that exceed the preset range, including data fields such as room identifier, port number, actual deviation value, threshold range, and degree of overreach. The degree of overreach is quantified by calculating the numerical value of the deviation value exceeding the threshold range, providing an accurate data basis for subsequent compensation calculations. The optical transmit power gain compensation calculation process determines the required power adjustment based on the specific deviation level for each room in the out-of-limit deviation value flag list. The calculation algorithm uses a linear mapping method to directly convert the deviation level into a power gain adjustment value. When the optical power at a room's optical port is low, the compensation is equal to the absolute value of the negative deviation value. When the optical power is high, the compensation is equal to the negative value of the positive deviation value. This calculation method ensures that the adjusted optical power value is close to the standard threshold. The room-level power gain adjustment parameters include the specific adjustment amount, adjustment direction, and adjustment priority for each room. The adjustment priority is determined by the room's function type, with conference rooms having the highest priority, offices having a medium priority, and public areas having a lower priority, ensuring that signal quality in critical business rooms is prioritized.

[0038] The dynamic power output level adjustment process inputs the room-level power gain adjustment parameters as control commands to the optical transmitter in the corresponding room. Upon receiving the adjustment parameters, the transmitter changes the laser diode's drive current based on the adjustment amount and direction specified in the parameters. The drive current is adjusted using a digital-to-analog converter, which converts the adjustment amount into a corresponding current change. A positive adjustment amount increases the drive current, while a negative adjustment amount decreases it. This current change directly affects the laser diode's optical output power. The compensated optical transmit power value is measured in real time by the optical power monitoring module. The monitoring module compares the adjusted optical power value with the pre-adjustment value to verify that the adjustment has achieved the desired effect. The power change trajectory and stabilization time during the adjustment process are also recorded. The signal transmission quality re-measurement process comprehensively tests the transmission performance of each room's optical port based on the compensated optical transmit power value. Key metrics measured include optical power stability, optical signal-to-noise ratio, bit error rate, and signal jitter. Optical power stability is assessed by continuously monitoring the power fluctuation range over a specified period of time. A smaller fluctuation range indicates a more stable signal. The optical signal-to-noise ratio (OSNR) is calculated by analyzing the ratio of the useful signal power to the noise power in the received signal. A higher ratio indicates better signal quality. Bit error rate (BER) is measured by sending a known test data packet and counting the number of bit errors at the receiver. The ratio of the number of error bits to the total number of transmitted bits is the BER. The power-compensated optical link transmission parameters combine all measured performance indicators to form a complete data set describing the transmission quality of each room's optical port.

[0039] Parameter integration and data structuring organize and store the power-compensated optical link transmission parameters in a standardized data format. The integration process unifies data from disparate measurement modules and establishes indexes based on room and port numbers. This data structuring utilizes a hierarchical data model. The top layer contains room-level data, including room identification and overall quality assessment; the middle layer contains port-level data, including specific transmission parameters for each port; and the bottom layer contains parameter-level data, including detailed values ​​and measurement timestamps for various performance indicators. The optical power-compensated link parameters form a complete link quality description document in a format that supports rapid query and data analysis, while also preserving parameter adjustment history and trend records.

[0040] In a specific embodiment, the process of executing step S104 may specifically include the following steps: The room quality score in the FTTR link quality evaluation matrix is ​​associated and mapped with the priority weight in the room function identification tag library to obtain the room bandwidth demand state vector; Based on the room bandwidth demand state vector, the reinforcement learning environment state space is constructed, and the bandwidth allocation action is processed by value function calculation to obtain the room bandwidth allocation strategy decision sequence. Perform QoS parameter configuration processing on each room according to the bandwidth quota in the room bandwidth allocation strategy decision sequence to obtain a set of personalized service quality parameters for the room; The room personalized service quality parameter set and network load feedback information are evaluated by reward function to obtain strategy optimization adjustment instructions; The policy optimization and adjustment instructions are configured and packaged to obtain a room-level QoS policy configuration set.

[0041] Specifically, the association mapping process multiplies each room's quality score in the FTTR link quality assessment matrix by the corresponding priority weight in the room function identification tag library. Priority weights are preset based on room function type: conference room weights are 0.9, office weights are 0.7, public area weights are 0.5, and server room weights are 0.8. The mapping calculation divides the room quality score by 100 and multiplies the weight by the priority weight to obtain a normalized room importance index, which reflects the room's priority in network resource allocation. The room bandwidth demand state vector combines parameters such as each room's importance index, historical peak bandwidth usage, current service load, and expected bandwidth demand into a multidimensional vector. Each dimension of the vector represents a key factor influencing bandwidth allocation decisions. The vector length is equal to the total number of rooms multiplied by the number of parameter dimensions, forming a complete data structure describing the overall network bandwidth demand state. The reinforcement learning environment state space construction process builds a decision-making environment model based on the room bandwidth demand state vector. The state space incorporates environmental variables such as the current total network bandwidth capacity, real-time bandwidth usage by each room, service type distribution, and network congestion level. The value function calculation process uses the core concept of the Q-learning algorithm to quantify the long-term benefits of bandwidth allocation actions. The action space is defined as a combination of schemes for allocating specific bandwidth quotas to each room, and each allocation scheme corresponds to a Q value. The Q value is determined by evaluating the impact of the allocation scheme on the overall network performance, including multiple evaluation dimensions such as user satisfaction, network utilization, and service quality compliance. The higher the Q value, the better the overall effect of the allocation scheme. The room bandwidth allocation strategy decision sequence records the optimal allocation scheme selected by the algorithm. Each element in the sequence contains information such as the room identifier, allocated bandwidth value, allocation priority, and execution time. The decision sequence is sorted by room priority to ensure that the bandwidth needs of critical rooms are met first.

[0042] The QoS parameter configuration process sets corresponding quality of service parameters for each room based on the bandwidth quota determined in the room bandwidth allocation policy decision sequence. Configuration parameters include minimum guaranteed bandwidth, maximum allowed bandwidth, packet priority, latency tolerance, and packet loss retransmission mechanism. The minimum guaranteed bandwidth is set based on the basic requirements of the room's functional type: 80% of the allocated bandwidth for conference rooms, 60% for offices, and 40% for public areas, ensuring basic service quality for critical services. Packet priority is coded using a hierarchical approach: packets in high-priority rooms are marked as urgent, those in medium-priority rooms as important, and those in low-priority rooms as normal. Network devices handle packets differently based on priority tags. The personalized room quality of service parameter set stores all room QoS configuration parameters in a structured manner according to room number, forming a complete quality of service configuration database. The database supports multiple search methods, including querying by room, by parameter type, and by priority.

[0043] The reward function evaluation process comprehensively analyzes the actual performance of the room's personalized service quality parameter set against network load feedback, which includes real-time data such as actual bandwidth usage, service quality compliance, and user experience evaluation. The reward function evaluates the quality of policy execution by calculating the deviation between expected and actual performance. Positive rewards are awarded when actual bandwidth usage approaches the allocated value and service quality indicators meet standards, while negative rewards are awarded when bandwidth is wasted or service quality falls short. Policy optimization and adjustment instructions generate specific adjustment recommendations based on the reward function evaluation results. These recommendations include increasing or decreasing bandwidth quotas for specific rooms, adjusting priority settings, and modifying QoS parameters. The priority of these adjustment instructions is determined by the severity and scope of the issue. Configuration integration merges and updates the policy optimization and adjustment instructions with the existing room's personalized service quality parameters. This integration process utilizes a version control mechanism to record the time, reason, and scope of each configuration change, ensuring traceability and rollback. Policy encapsulation packages the updated configuration parameters in a standardized format, including a configuration header, parameter data area, and checksum, to ensure the integrity and accuracy of the configuration data. The room-level QoS policy configuration set integrates the final configuration parameters of all rooms to form a complete network service quality management solution. The configuration set supports a hot update mechanism, allowing dynamic adjustment of network parameters without interrupting business, meeting the real-time management needs in the FTTR network environment.

[0044] In a specific embodiment, the process of executing step S105 may specifically include the following steps: Serialize and encapsulate the policy parameters in the room-level QoS policy configuration set in JSON format to obtain an MQTT message payload data packet; A building network topic subscription mechanism is built based on the MQTT message payload data packet, and room configuration update messages are published and subscribed to obtain a building data interactive communication link; Based on the building data interactive communication link, room-level policy configuration information is synchronized with the building management center in real time to obtain gateway configuration status feedback data; Perform consistency check on the gateway configuration status feedback data and the room-level QoS policy configuration set to obtain the policy execution status verification result; The results of the policy execution status verification are processed for solution integration and management strategy generation to obtain a comprehensive management solution for FTTR gateway services.

[0045] Specifically, the JSON format serialization and encapsulation process converts the various policy parameters in the room-level QoS policy configuration set into a standard JSON data format. The encapsulation process first extracts key information such as the room identifier, bandwidth quota, priority setting, and quality of service parameters in the configuration set, and then constructs a nested data structure according to the JSON syntax specification. The configuration information of each room forms a JSON object. The object contains a roomId field to store the room number, a bandwidth field to store the allocated bandwidth value, a priority field to store the priority level, and a qosParams field to store a detailed array of quality of service parameters. All room objects are organized into a JSON array, and message header information including metadata such as timestamp, version number, and configuration type is added before the array. The MQTT message payload data packet uses the configuration data in JSON format as the message payload, and adds the message header required by the MQTT protocol. The message header contains control fields such as the topic name, quality of service level, reservation flag, and repeat flag. The payload data is converted into a byte stream format through UTF-8 encoding to meet the transmission requirements of the MQTT protocol.

[0046] The building network's topic subscription mechanism establishes a hierarchical topic structure based on MQTT message payload data packets. Topic naming uses a hierarchical format such as "building / floor / room / config" to represent configuration information at different levels. Gateway devices act as publishers, sending configuration update messages to specific topics, and the building management center, as a subscriber, listens for message changes in related topics. Publish-subscribe processing implements message routing and forwarding through an MQTT proxy server. The proxy server maintains a topic subscription list, recording the topics and quality of service requirements subscribed to by each client. When the gateway publishes a message, the proxy server pushes the message to the corresponding subscriber based on topic matching rules. The building data interaction communication link establishes a bidirectional communication channel between the gateway and the management center. The communication link uses TCP as the underlying transport protocol to ensure reliable message transmission. The link supports a heartbeat detection mechanism to monitor the connection status and automatically reconnects when a connection anomaly is detected.

[0047] Real-time synchronization processing is based on the building data interactive communication link to bidirectionally synchronize the gateway's room-level policy configuration information with the database of the building management center. The synchronization process uses a version control mechanism to handle concurrent updates and conflict resolution. The gateway device regularly sends configuration snapshots to the management center. The snapshot contains the current configuration status and version number of all rooms. After receiving the snapshot, the management center compares it with the local database, identifies configuration differences, and generates synchronization instructions. The gateway configuration status feedback data contains feedback information such as configuration execution results, error messages, device status, performance indicators, etc. The feedback data is encoded in a structured format, including fields such as status code, message description, timestamp, and impact range. The management center updates the device status record and configuration execution log based on the feedback data.

[0048] The consistency check verifies the correctness and completeness of the configuration by comparing the gateway configuration status feedback data against the room-level QoS policy configuration set. The verification algorithm uses a hash value comparison method, calculating an MD5 hash value for each room's configuration parameters and then comparing the hash values ​​on the gateway and the management center to ensure consistency. If a hash value mismatch is found, the verification process further analyzes the specific parameter differences to locate the inconsistent configuration items and the content of the discrepancies. The policy execution status verification results record all issues discovered during the verification process, including anomalies such as missing configurations, incorrect parameters, version conflicts, and insufficient permissions. It also records the number of configuration items that passed the verification and the overall consistency level.

[0049] The solution integration process merges and optimizes the policy execution status verification results with the existing network management policies. The integration process categorizes the problems according to the severity of the verification results, uses an automatic correction mechanism for minor configuration deviations, and generates alarm information and requires manual intervention for serious configuration errors. The management policy generation process formulates a complete network management plan based on the integration results. The plan includes room-level configuration policies, network monitoring policies, fault handling policies, performance optimization policies, and other aspects. The FTTR gateway service integrated management solution integrates all policy components into a unified management framework. The framework supports dynamic loading and hot updates of policies, allowing management policies to be adjusted without interrupting business. It also provides policy execution monitoring and effect evaluation functions to ensure continuous optimization and improvement of the management plan.

[0050] The above describes the gateway service integrated management method based on FTTR requirements in the embodiment of the present application. The following describes the gateway service integrated management system based on FTTR requirements in the embodiment of the present application. Figure 2 In the embodiment of the present application, an embodiment of the gateway service integrated management system based on FTTR requirements includes: The scanning module is used to perform topology scanning on the optical ports of each room using the optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table; An extraction module is used to perform feature extraction processing on the service traffic of each room in the room-level FTTR topology mapping table according to deep packet inspection to obtain a room function identification label library; A compensation module is used to perform attenuation compensation processing on the optical port of the room corresponding to the room function identification tag library by the optical power meter to obtain an FTTR link quality evaluation matrix; an allocation module, configured to perform bandwidth allocation processing on each room according to the FTTR link quality evaluation matrix through a reinforcement learning algorithm to obtain a room-level QoS policy configuration set; The interaction module is used to perform building data interaction processing on the room-level QoS policy configuration set based on the MQTT protocol to obtain a comprehensive management solution for FTTR gateway services.

[0051] above Figure 2 The gateway service integrated management system based on FTTR requirements in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The gateway service integrated management device based on FTTR requirements in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0052] Reference Figure 3 In the embodiment of the present invention, a gateway service integrated management device based on FTTR requirements is also provided. The gateway service integrated management device based on FTTR requirements can be a server, and its internal structure can be as follows: Figure 3 As shown. The gateway service integrated management device based on FTTR demand includes a processor, memory, display screen, input device, network interface and database connected through a system bus. Among them, the computer-designed processor is used to provide computing and control capabilities. The memory of the gateway service integrated management device based on FTTR demand includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the gateway service integrated management device based on FTTR demand is used to store the corresponding data in this embodiment. The network interface of the gateway service integrated management device based on FTTR demand is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0053] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the gateway service integrated management device based on FTTR requirements to which the solution of the present invention is applied.

[0054] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions. When the instructions are executed on a computer, the computer executes the steps of the gateway service integrated management method based on FTTR requirements.

[0055] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0056] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a gateway service integrated management device (which can be a personal computer, server, or network device, etc.) based on FTTR requirements to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0057] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A gateway service integrated management method based on FTTR requirements, characterized in that: The method comprises: The optical ports in each room are topologically scanned using the optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table; Perform feature extraction processing on the service traffic of each room in the room-level FTTR topology mapping table according to deep packet inspection to obtain a room function identification label library; Using an optical power meter to perform attenuation compensation processing on the optical port of the room corresponding to the room function identification tag library to obtain an FTTR link quality evaluation matrix; Bandwidth allocation is performed on each room according to the FTTR link quality evaluation matrix using a reinforcement learning algorithm to obtain a room-level QoS policy configuration set; Based on the MQTT protocol, the room-level QoS policy configuration set is processed for building data interaction to obtain a comprehensive management solution for FTTR gateway services.

2. The method for comprehensive management of gateway services based on FTTR requirements according to claim 1, characterized in that: The optical ports of each room are topologically scanned using the optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table, including: Send optical pulse test signals to the optical ports of each room, detect the reflection delay and reflection intensity parameters of the optical signal, and obtain the optical fiber physical link parameter set; Calculate the optical fiber length and transmission distance according to the reflection delay parameter in the optical fiber physical link parameter set, and obtain a room optical fiber link length data table; Performing geographic location mapping processing on each room based on the transmission distance in the room optical fiber link length data table to obtain a room space distribution coordinate matrix; Associating and binding the room space distribution coordinate matrix with the optical port identifier to obtain a port-room mapping relationship database; A topology structure construction process is performed on the port-room mapping relationship database to obtain a room-level FTTR topology mapping table.

3. The method for comprehensive management of gateway services based on FTTR requirements according to claim 1, characterized in that: The feature extraction process is performed on the service traffic of each room in the room-level FTTR topology mapping table according to deep packet inspection to obtain a room function identification tag library, including: Performing protocol parsing and application layer payload extraction on the network data packets of each room in the room-level FTTR topology mapping table to obtain a set of room service flow feature vectors; Performing statistical analysis based on the traffic type distribution and bandwidth occupancy pattern in the room service traffic feature vector set to obtain room network usage behavior pattern data; Performing clustering calculation based on the time window flow change curve in the room network usage behavior pattern data to obtain a room function type classification result; Matching and mapping the room function type classification result with a preset function label dictionary to obtain a room function identification label sequence; The room function identification tag sequence is subjected to tag library construction and index establishment processing to obtain a room function identification tag library.

4. The method for comprehensive management of gateway services based on FTTR requirements according to claim 1, characterized in that: The optical power meter performs attenuation compensation processing on the optical port of the room corresponding to the room function identification tag library to obtain an FTTR link quality evaluation matrix, including: Based on the function label of each room in the room function identification label library, real-time detection and processing of the optical power level of the corresponding optical port are performed to obtain a room optical port power monitoring data set; Performing deviation calculation based on the received optical power value in the room optical port power monitoring data set and the standard optical power threshold to obtain an optical power deviation parameter table; Automatically adjust the optical transmission power gain of the deviation values ​​exceeding the preset range in the optical power deviation parameter table to obtain the link parameters after optical power compensation; Performing a comprehensive quality score calculation on the link parameters after optical power compensation in combination with optical fiber insertion loss and transmission loss to obtain room optical port quality score data; Matrix arrangement and index construction processing are performed based on the room optical port quality score data to obtain an FTTR link quality evaluation matrix.

5. The method for comprehensive management of gateway services based on FTTR requirements according to claim 4, characterized in that: The step of automatically adjusting the optical transmission power gain of the deviation values ​​exceeding the preset range in the optical power deviation parameter table to obtain the link parameters after optical power compensation includes: Performing numerical comparison processing on the deviation values ​​in the optical power deviation parameter table and a preset optical power deviation threshold range to obtain a list of excessive deviation value marks; Calculating the optical transmission power gain compensation amount according to the deviation degree of each room in the over-limit deviation value mark list to obtain a room-level power gain adjustment parameter; Inputting the room-level power gain adjustment parameter into the optical transmitter to dynamically adjust the power output level to obtain a compensated optical transmission power value; Re-measuring the signal transmission quality of the optical port in each room based on the compensated optical transmission power value to obtain the optical link transmission parameters after power compensation; Parameter integration and data structuring processing are performed on the power-compensated optical link transmission parameters to obtain link parameters after optical power compensation.

6. The method for comprehensive management of gateway services based on FTTR requirements according to claim 1, characterized in that: The reinforcement learning algorithm is used to perform bandwidth allocation processing on each room according to the FTTR link quality evaluation matrix to obtain a room-level QoS policy configuration set, including: Performing an association mapping process on the room quality score in the FTTR link quality evaluation matrix and the priority weight in the room function identification tag library to obtain a room bandwidth demand state vector; Constructing a reinforcement learning environment state space based on the room bandwidth demand state vector, performing value function calculation on the bandwidth allocation action, and obtaining a room bandwidth allocation strategy decision sequence; Performing QoS parameter configuration processing on each room according to the bandwidth quota in the room bandwidth allocation strategy decision sequence to obtain a set of personalized service quality parameters for the room; Performing reward function evaluation on the room personalized service quality parameter set and network load feedback information to obtain a strategy optimization adjustment instruction; The policy optimization and adjustment instructions are subjected to configuration integration and policy encapsulation processing to obtain a room-level QoS policy configuration set.

7. The method for comprehensive management of gateway services based on FTTR requirements according to claim 1, characterized in that: The room-level QoS policy configuration set is subjected to building data interaction processing based on the MQTT protocol to obtain a comprehensive FTTR gateway service management solution, including: Serializing and encapsulating the policy parameters in the room-level QoS policy configuration set in JSON format to obtain an MQTT message payload data packet; Building a building network topic subscription mechanism based on the MQTT message payload data packet, performing publish-subscribe processing on the room configuration update message, and obtaining a building data interactive communication link; Based on the building data interactive communication link, the room-level policy configuration information is synchronized with the building management center in real time to obtain gateway configuration status feedback data; Performing consistency check on the gateway configuration status feedback data and the room-level QoS policy configuration set to obtain a policy execution status verification result; The strategy execution status verification result is subjected to solution integration and management strategy generation processing to obtain a comprehensive management solution for FTTR gateway services.

8. A gateway service integrated management system based on FTTR requirements, characterized in that: Used to implement the gateway service integrated management method based on FTTR demand according to any one of claims 1 to 7, the gateway service integrated management system based on FTTR demand includes: The scanning module is used to perform topology scanning on the optical ports of each room using the optical time domain reflectometer test signal to obtain a room-level FTTR topology mapping table; An extraction module is used to perform feature extraction processing on the service traffic of each room in the room-level FTTR topology mapping table according to deep packet inspection to obtain a room function identification label library; A compensation module is used to perform attenuation compensation processing on the optical port of the room corresponding to the room function identification tag library by the optical power meter to obtain an FTTR link quality evaluation matrix; an allocation module, configured to perform bandwidth allocation processing on each room according to the FTTR link quality evaluation matrix through a reinforcement learning algorithm to obtain a room-level QoS policy configuration set; The interaction module is used to perform building data interaction processing on the room-level QoS policy configuration set based on the MQTT protocol to obtain a comprehensive management solution for FTTR gateway services.

9. A gateway service integrated management device based on FTTR requirements, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the method for integrated management of gateway services based on FTTR requirements according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the processor is enabled to execute the gateway service integrated management method based on FTTR requirements according to any one of claims 1 to 7.

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