Method and system for scenario-based forwarding of multi-source seismic operational data

Abstract

This invention discloses a scenario-based forwarding method and system for multi-source seismic operational data, relating to the field of earthquake monitoring technology. The method includes: using an earthquake operational management platform, transforming multi-source seismic operational data into target information products for early warning terminals in different scenarios based on scenario attributes; constructing a network topology model including forwarding nodes and early warning terminals on the earthquake operational management platform, and collecting a real-time state parameter matrix of the current network links based on the network topology model; using the African Vulture optimization algorithm based on the real-time state parameter matrix to iteratively optimize the forwarding strategy of the target information products to obtain the optimal forwarding strategy; and using the earthquake operational management platform to send the target information products to the corresponding early warning terminals according to the optimal forwarding strategy and the scenario of the target information products. This invention solves the problems of difficulty in multi-source data fusion, lack of scenario-based differentiated services, and low network forwarding efficiency in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of earthquake monitoring technology, and in particular to a scenario-based forwarding method and system for multi-source seismic operational data. Background Technology

[0002] Earthquake early warning and rapid reporting systems are crucial for mitigating earthquake disaster losses. With the improvement of earthquake monitoring networks, the sources of operational earthquake data have become increasingly diversified, including earthquake early warning systems, rapid reporting systems, manual rapid reporting systems, and disaster assessment systems. However, existing earthquake data forwarding methods typically suffer from the following problems:

[0003] 1) Difficulty in fusion of multi-source data: Data formats, update frequencies and confidence levels of different data sources are different, often resulting in parameter conflicts, making it difficult to form unified and high-precision global seismic event parameters.

[0004] 2) Lack of scenario-based differentiated services: Different application scenarios (such as schools, hospitals, chemical industrial parks, and families) have huge differences in their needs for earthquake information warning timeliness, display content, and response strategies. The traditional "one-size-fits-all" push method cannot meet the needs of refined emergency avoidance.

[0005] 3) Low network forwarding efficiency: At the moment an earthquake occurs, a massive number of early warning terminals receive data concurrently, which can easily cause network congestion. Traditional static routing or simple load balancing strategies are unable to cope with the complex and real-time changing network conditions, resulting in delays or loss of critical early warning information.

[0006] Therefore, there is an urgent need for a technical solution that can integrate multi-source data, combine terminal scenario attributes, and perform intelligent optimization and forwarding based on real-time network status. Summary of the Invention

[0007] This invention provides a scenario-based forwarding method and system for multi-source seismic operational data, which solves the problems of difficulty in multi-source data fusion, lack of scenario-based differentiated services, and low network forwarding efficiency in existing technologies.

[0008] In a first aspect, embodiments of the present invention provide a scenario-based forwarding method for multi-source seismic operational data, the method comprising:

[0009] The earthquake business management platform receives multi-source earthquake business data from different data sources and transforms the multi-source earthquake business data into target information products for early warning terminals in different scenarios according to scenario attributes.

[0010] In the earthquake business management platform, a network topology model including forwarding nodes and early warning terminals is constructed, and based on the network topology model, a real-time status parameter matrix of the current network links is collected.

[0011] Based on the real-time state parameter matrix, the African vulture optimization algorithm is used to iteratively optimize the forwarding strategy of the target information product to obtain the optimal forwarding strategy.

[0012] Based on the optimal forwarding strategy and the scenario of the target information product, the earthquake service management platform is used to send the target information product to the corresponding early warning terminal.

[0013] The technical solution provided in this application has at least the following beneficial effects:

[0014] By parsing and extracting key fields from multi-source seismic operational data and storing them in a unified object format, and combining dynamic weights and active event lists to resolve and dynamically fuse multi-source data conflicts, a global seismic event parameter with an incrementing version number is generated. This effectively solves the problems of differences and conflicts in format, frequency, and confidence levels among different data sources, achieving a high-precision and unified description of seismic event parameters and improving the accuracy and reliability of seismic event determination. Furthermore, by introducing scene attributes, a three-dimensional decision matrix containing scene, intensity, and stage dimensions is constructed, and differentiated target information products are generated accordingly. This allows for customized early warning timeliness and display to meet the actual needs of different application scenarios. The system displays content and handling strategies, changing the traditional "one-size-fits-all" approach to push notifications. It achieves refined and scenario-based emergency response services, significantly improving the practicality and relevance of early warning information in different scenarios. By constructing a network topology model and collecting real-time state parameter matrices, the system uses an improved African vulture optimization algorithm to iteratively optimize the forwarding strategy, obtaining the optimal forwarding strategy. Combined with scenario priority, it implements forwarding, effectively coping with network congestion caused by massive concurrent data reception by early warning terminals during an earthquake. It dynamically plans the optimal transmission path based on real-time network status, avoiding delays and loss of critical early warning information, and ensuring efficient and reliable transmission of high-priority early warning data in complex network environments.

[0015] In one optional implementation, an earthquake service management platform is used to receive multi-source earthquake service data from different data sources and, based on scenario attributes, transform the multi-source earthquake service data into target information products for early warning terminals in different scenarios, including:

[0016] Connect the earthquake business management platform to the earthquake business data server, and monitor and access several data sources in the earthquake business data server;

[0017] The earthquake service management platform is used to receive multi-source earthquake service data from different data sources.

[0018] Based on the type identifier in the message header, the corresponding parser is invoked, and the parser is used to extract the key fields of the multi-source earthquake business data from the corresponding data source;

[0019] The extracted key fields are mapped to unified earthquake event objects within the earthquake business management platform, timestamped, and stored in the real-time database.

[0020] Multi-source data conflict resolution and dynamic fusion are performed on several seismic event objects stored in the real-time database to obtain global seismic event parameters;

[0021] Based on global earthquake event parameters and the scene attributes of the early warning terminal, target information products corresponding to the early warning terminal are generated.

[0022] In one optional implementation, the data source includes an earthquake early warning system, an earthquake rapid reporting system, a manual rapid reporting system, and a disaster assessment system;

[0023] The multi-source earthquake operational data includes earthquake early warning data, earthquake rapid reporting data, manual rapid reporting data, and disaster assessment data.

[0024] In one optional implementation, multi-source data conflict resolution and dynamic fusion are performed on several seismic event objects stored in the real-time database to obtain global seismic event parameters, including:

[0025] A list of active seismic events is maintained in a real-time database, which is used to store existing seismic event objects in different time windows;

[0026] For several earthquake event objects stored in real time, obtain the epicenter location and time of each earthquake event object and the distance between it and all existing earthquake event objects in the active earthquake event list;

[0027] If the distance is less than the preset distance threshold and the timestamp difference is less than the preset time window, then the earthquake event object is classified into the corresponding existing earthquake event object.

[0028] Based on the preset dynamic weights of different data sources, parameter fusion calculations are performed on several earthquake event objects stored in the real-time database to obtain global earthquake event parameters, and a state machine is maintained for each earthquake event object.

[0029] Based on the state machine, when a seismic event object from a data source with higher dynamic weight is received, causing a significant jump in the global seismic event parameters, a correction event of the state machine is triggered, generating global seismic event parameters with an incrementing version number.

[0030] In one optional implementation, based on global seismic event parameters and the scene attributes of the early warning terminal, a target information product corresponding to the early warning terminal is generated, including:

[0031] Using the earthquake business management platform, the registration information of several early warning terminals is read from the terminal database, and the scene attributes in the registration information are extracted. The scene attributes include a unique identifier ID, latitude and longitude coordinates, scene type, and disaster type.

[0032] The global seismic event parameters are input into the preset seismic motion attenuation equation to calculate the estimated seismic intensity of each early warning terminal and to calculate the theoretical countdown time for the seismic wave to reach the early warning terminal.

[0033] Based on a three-dimensional decision matrix, three-dimensional decision information corresponding to each early warning terminal is generated according to scene attributes, estimated seismic intensity, and theoretical countdown time. The three-dimensional decision matrix includes scene dimension, intensity dimension, and stage dimension. The scene dimension is used to store the scene attributes of the early warning terminal, the intensity dimension is used to store the estimated seismic intensity of the early warning terminal, and the stage dimension is used to store stage information divided according to the theoretical countdown time.

[0034] Based on the 3D decision information and the corresponding display strategy package for the early warning terminal, a target information product corresponding to each early warning terminal is generated.

[0035] In one optional implementation, a network topology model including forwarding nodes and early warning terminals is constructed on the earthquake service management platform. Based on the network topology model, a real-time status parameter matrix of the current network links is collected, including:

[0036] In the earthquake service management platform, the network environment of the earthquake service management platform is abstracted into a weighted directed graph to obtain a network topology model. The vertices of the weighted directed graph include the source point abstracted from the earthquake service management platform, the forwarding nodes abstracted from several earthquake precursor network nodes, and the aggregation point abstracted from several early warning terminals. The edges of the weighted directed graph are logical links connecting the source point, the forwarding nodes, and the aggregation point.

[0037] Deploy several network monitoring probes in the network topology model;

[0038] In the earthquake operational management platform, network monitoring probes are used to collect the state parameters of each side and each node in the network topology model, obtaining a real-time state parameter matrix of the current network links. These state parameters include link bandwidth utilization. Link delay Node CPU load Memory load and packet loss rate .

[0039] In one optional implementation, based on the real-time state parameter matrix, the African vulture optimization algorithm is used to iteratively optimize the forwarding strategy of the target information product to obtain the optimal forwarding strategy, including:

[0040] Based on the state parameter indices contained in the real-time state parameter matrix, the fitness function of the African vulture optimization algorithm is set, and the forwarding strategy of the target information product is encoded into the position vector of the African vulture optimization algorithm.

[0041] The chaotic sequence is generated using the Logistic mapping and then mapped to the solution space of the African vulture optimization algorithm to obtain the initial vulture population.

[0042] Based on the real-time state parameter matrix, the fitness function is used to calculate the fitness value of the alternative forwarding strategies corresponding to each initial vulture in the initial vulture population, and the individual with the best fitness is taken as the optimal individual.

[0043] Based on the fitness value, a convergence factor and Cauchy mutation mechanism are introduced to update the position of the initial vulture population, resulting in an updated vulture population.

[0044] Based on the real-time state parameter matrix, the fitness function is used to calculate the fitness value of the alternative forwarding strategies corresponding to each updated vulture in the updated vulture population, and the individual with the best fitness is updated as the best individual.

[0045] Repeat the position update steps until the current iteration count reaches the iteration count threshold or the fitness value of the best individual meets the requirements, then end the position update;

[0046] The optimal forwarding strategy for the target information product is obtained by decoding the location vector of the optimal individual.

[0047] In one alternative implementation, the fitness function is formulated as follows:

[0048]

[0049] In the formula, For vultures X The fitness value of the corresponding alternative forwarding strategies; j This refers to the indicator value of the early warning terminal; M This represents the total number of early warning terminals; For the first j The scene priority weight of the early warning terminal is set according to the scene attributes in the target information product; For the first j The link transmission delay of the early warning terminal is the link delay of each hop on the path in the real-time status parameter matrix. sum; For the first j The queuing delay of the early warning terminal is determined based on the link bandwidth utilization rate in the real-time status parameter matrix. set up; For the firstj The node processing latency of the early warning terminal is determined by the node CPU load of the distributed nodes in the real-time status parameter matrix. and memory load Obtained by linear mapping; This is the congestion penalty coefficient; For vultures X The congestion penalty value for the corresponding alternative forwarding strategy is based on the link bandwidth utilization in the real-time state parameter matrix. Node CPU load and memory load set up; This is a reliability penalty factor; For vultures X The packet loss penalty value for the corresponding alternative forwarding strategy is based on the packet loss rate of all links on the path in the real-time state parameter matrix. set up; X For vulture variables.

[0050] In one optional implementation, based on the optimal forwarding strategy and the scenario of the target information product, the earthquake service management platform is used to send the target information product to the corresponding early warning terminal, including:

[0051] Using the earthquake service management platform, policy parsing and route mapping are performed to convert the optimal forwarding policy into executable network control commands and distribute them to all distribution nodes;

[0052] Based on the hardware limitations and network environment of different early warning terminals, the corresponding target information products are packaged in a differentiated manner to obtain packaged product data;

[0053] Based on the scenario dimension of the target information product, hierarchical QoS transmission guarantee is implemented, and the forwarding priority of the encapsulated product data is set.

[0054] Using the earthquake business management platform, the encapsulated product data with forwarding priority is sent to several corresponding distribution nodes. Based on the forwarding priority and network control instructions, the distribution nodes then send the encapsulated product data to the corresponding early warning terminals.

[0055] Secondly, embodiments of the present invention provide a scenario-based forwarding system for multi-source seismic operational data, used to implement a scenario-based forwarding method, the apparatus comprising:

[0056] The multi-source data acquisition unit is used to receive multi-source earthquake business data from different data sources using the earthquake business management platform, and to transform the multi-source earthquake business data into target information products for early warning terminals in different scenarios according to scenario attributes.

[0057] The status parameter acquisition unit is used to construct a network topology model containing forwarding nodes and early warning terminals on the earthquake business management platform, and to acquire the real-time status parameter matrix of the current network links based on the network topology model.

[0058] The forwarding strategy optimization unit is used to iteratively optimize the forwarding strategy of the target information product based on the real-time state parameter matrix and using the African vulture optimization algorithm to obtain the optimal forwarding strategy.

[0059] The scenario-based forwarding unit is used to send the target information product to the corresponding early warning terminal using the earthquake business management platform, based on the optimal forwarding strategy and the scenario of the target information product.

[0060] A third aspect of this invention provides an electronic device, which includes:

[0061] At least one processor; and a memory communicatively connected to the at least one processor; wherein,

[0062] The memory stores instructions that can be executed by at least one processor, such that the at least one processor can perform the method proposed in the first aspect of the present invention.

[0063] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in the first aspect of the present invention. Attached Figure Description

[0064] Figure 1 This is a schematic diagram of the electronic device structure of the hardware operating environment involved in the embodiments of the present invention;

[0065] Figure 2 This is a flowchart illustrating the steps of a scenario-based forwarding method for multi-source seismic operational data provided in an embodiment of the present invention.

[0066] Figure 3 This is a schematic diagram of the functional units of a scenario-based forwarding system for multi-source seismic operational data provided in an embodiment of the present invention. Detailed Implementation

[0067] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0068] The present invention will be further described below with reference to the accompanying drawings.

[0069] Reference Figure 1 , Figure 1 This is a schematic diagram of the electronic device structure of the hardware operating environment involved in the embodiments of the present invention.

[0070] like Figure 1 As shown, the electronic device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. Alternatively, the memory 1005 may be a storage device independent of the aforementioned processor 1001.

[0071] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0072] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a data storage module, a network communication module, a user interface module, and an electronic program for a scenario-based forwarding system of multi-source earthquake business data.

[0073] exist Figure 1 In the electronic device shown, the network interface 1004 is mainly used for contextual forwarding with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the electronic device of the present invention can be set in the electronic device. The electronic device calls the electronic program of the contextual forwarding system of multi-source seismic service data stored in the memory 1005 through the processor 1001, and executes the contextual forwarding method of multi-source seismic service data provided in the embodiment of the present invention.

[0074] Reference Figure 2The present invention provides a scenario-based forwarding method for multi-source seismic operational data, the method comprising:

[0075] S201: Using the earthquake business management platform, receive multi-source earthquake business data from different data sources, and transform the multi-source earthquake business data into target information products for early warning terminals in different scenarios according to scenario attributes.

[0076] S202: On the earthquake business management platform, construct a network topology model that includes forwarding nodes and early warning terminals, and collect the real-time status parameter matrix of the current network links based on the network topology model;

[0077] S203: Based on the real-time state parameter matrix, the African vulture optimization algorithm is used to iteratively optimize the forwarding strategy of the target information product to obtain the optimal forwarding strategy;

[0078] S204: Based on the optimal forwarding strategy and the scenario of the target information product, the earthquake service management platform is used to send the target information product to the corresponding early warning terminal.

[0079] The technical solution provided in this application has at least the following beneficial effects:

[0080] By parsing and extracting key fields from multi-source seismic operational data and storing them in a unified object format, and combining dynamic weights and active event lists to resolve and dynamically fuse multi-source data conflicts, a global seismic event parameter with an incrementing version number is generated. This effectively solves the problems of differences and conflicts in format, frequency, and confidence levels among different data sources, achieving a high-precision and unified description of seismic event parameters and improving the accuracy and reliability of seismic event determination. Furthermore, by introducing scene attributes, a three-dimensional decision matrix containing scene, intensity, and stage dimensions is constructed, and differentiated target information products are generated accordingly. This allows for customized early warning timeliness and display to meet the actual needs of different application scenarios. The system displays content and handling strategies, changing the traditional "one-size-fits-all" approach to push notifications. It achieves refined and scenario-based emergency response services, significantly improving the practicality and relevance of early warning information in different scenarios. By constructing a network topology model and collecting real-time state parameter matrices, the system uses an improved African vulture optimization algorithm to iteratively optimize the forwarding strategy, obtaining the optimal forwarding strategy. Combined with scenario priority, it implements forwarding, effectively coping with network congestion caused by massive concurrent data reception by early warning terminals during an earthquake. It dynamically plans the optimal transmission path based on real-time network status, avoiding delays and loss of critical early warning information, and ensuring efficient and reliable transmission of high-priority early warning data in complex network environments.

[0081] In one optional implementation, an earthquake service management platform is used to receive multi-source earthquake service data from different data sources and, based on scenario attributes, transform the multi-source earthquake service data into target information products for early warning terminals in different scenarios, including:

[0082] S2011: Connect the earthquake business management platform to the earthquake business data server, and monitor and access several data sources in the earthquake business data server;

[0083] In this embodiment, the access monitoring is performed as follows: The earthquake business management platform establishes long connections to monitor multiple data sources by configuring a high-concurrency message queue middleware (such as Kafka or RabbitMQ); and the platform loads different protocol adapters to address the protocol differences between different data sources (such as earthquake early warning systems typically using UDP / TCP binary streams, while rapid reporting systems use JSON / XML text).

[0084] The data sources include earthquake early warning systems, earthquake rapid reporting systems, manual rapid reporting systems, and disaster assessment systems;

[0085] The multi-source earthquake operational data includes earthquake early warning data, earthquake rapid reporting data, manual rapid reporting data, and disaster assessment data;

[0086] S2012: Use the earthquake service management platform to receive multi-source earthquake service data from different data sources;

[0087] S2013: Based on the type identifier in the message header, call the corresponding parser and use the parser to extract the key fields of the multi-source earthquake business data from the corresponding data source.

[0088] In this embodiment, key field extraction: the parser distributes messages based on the header identifier (e.g., MsgType: 0x01 represents a warning, 0x02 represents a rapid report).

[0089] For earthquake early warning data, the extracted fields include: event ID, earthquake occurrence time, epicenter latitude and longitude, magnitude and depth, number of reference stations, and P-wave arrival time;

[0090] For earthquake rapid reporting data and manual rapid reporting data, the extracted fields include: automatic magnitude, positioning accuracy, epicenter location, and preliminary results of focal mechanism solution;

[0091] For disaster assessment data, the extracted fields include: number of casualties, building collapse rate, and vector data of the affected area;

[0092] S2014: Map the extracted key fields to a unified earthquake event object within the earthquake business management platform, add a timestamp, and store it in the real-time database;

[0093] In this embodiment, the extracted key fields are injected into a unified EarthquakeEvent Java object (or C++ structure) within the platform; this object contains standardized fields: EventID (event ID), OriginTime (earthquake time), Latitude / Longitude (epicenter latitude and longitude), Depth (depth), Magnitude (magnitude), SourceList (source list), and Confidence (confidence level); all objects are tagged with an IngestTimestamp (database entry timestamp) with nanosecond precision.

[0094] S2015: Perform multi-source data conflict resolution and dynamic fusion on several seismic event objects stored in the real-time database to obtain global seismic event parameters;

[0095] S2016: Generate target information products corresponding to the early warning terminal based on global earthquake event parameters and scene attributes of the early warning terminal.

[0096] In one optional implementation, multi-source data conflict resolution and dynamic fusion are performed on several seismic event objects stored in the real-time database to obtain global seismic event parameters, including:

[0097] S20151: Maintain a list of active seismic events in a real-time database, the list of active seismic events being used to store existing seismic event objects for different time windows;

[0098] In this embodiment, the aim is to solve the problem of inconsistent measurement parameters for the same seismic event by different systems;

[0099] Active event list maintenance: A sliding window list is maintained in memory, with a default window length of 60 seconds (configurable); each entry in the list represents a hypothetical earthquake event that is being processed.

[0100] S20152: For several earthquake event objects stored in real time, obtain the epicenter location and time of each earthquake event object and the distance between it and all existing earthquake event objects in the active earthquake event list;

[0101] In this embodiment, when a new earthquake event object arrives, the Euclidean distance (in kilometers) between its epicenter and all events in the active list is calculated, and the timestamp difference is also calculated.

[0102] S20153: If the distance is less than the preset distance threshold and the timestamp difference is less than the preset time window, then the earthquake event object is classified into the corresponding existing earthquake event object.

[0103] In this embodiment, if the Euclidean distance is less than 30km and the timestamp difference is less than 20s, it is determined to be the same earthquake event, and it is attached to the active event; otherwise, a new active event is created.

[0104] S20154: Based on the preset dynamic weights of different data sources, perform parameter fusion calculation on several earthquake event objects stored in the real-time database to obtain global earthquake event parameters, and maintain a state machine for each earthquake event object;

[0105] In this embodiment, a weighting function that changes over time is preset for different data sources:

[0106] T0 phase (0-30 seconds after the earthquake): The earthquake early warning system has the highest weight (W=0.7W=0.7) because it is the fastest; manual rapid reports have not yet been generated;

[0107] T1 phase (30-120 seconds after the earthquake): The weight of the earthquake rapid reporting system increases (W=0.6), while the weight of the earthquake early warning system decreases;

[0108] T2 phase (120+ seconds after the earthquake): The manual rapid reporting system takes precedence (W=0.8W=0.8) and serves as the final correction result;

[0109] S20155: Based on a state machine, when a seismic event object from a data source with higher dynamic weight is received, causing a significant jump in the global seismic event parameters, a correction event of the state machine is triggered, generating global seismic event parameters with an incrementing version number.

[0110] In this embodiment, smooth fusion is performed as follows: For the epicenter location, a weighted centroid algorithm is used to calculate the global coordinates; for the magnitude, a weighted average or maximum value logic is used (depending on the early warning strategy).

[0111] State machine triggering: Each global event maintains a state machine; the state includes INIT (initialization), UPDATING (updating), and FINAL (final determination); when a high-weight data source (such as a manual report) arrives, and its magnitude parameter differs from the current global parameter by more than a threshold (such as 0.5), the state machine triggers a correction event; at this time, the global event parameter is updated, and the Version number is incremented by 1 (e.g., v1 - v2), while pushing an "update" flag downstream, instructing the terminal to refresh the displayed data.

[0112] In one optional implementation, based on global seismic event parameters and the scene attributes of the early warning terminal, a target information product corresponding to the early warning terminal is generated, including:

[0113] S20161: Using the earthquake business management platform, read the registration information of several early warning terminals in the terminal database and extract the scene attributes from the registration information. The scene attributes include a unique identifier ID, latitude and longitude coordinates, scene type (school, hospital, institution, chemical industrial park, home terminal), and disaster type.

[0114] S20162: Input global earthquake event parameters into the preset ground motion attenuation equation, calculate the estimated ground motion intensity of each early warning terminal, and calculate the theoretical countdown time for the earthquake wave to reach the early warning terminal.

[0115] In this embodiment, the seismic motion attenuation equation (such as the attenuation relationship recommended by the seismic motion parameter zoning map) is used to input global earthquake parameters (magnitude, depth) and combine the terminal latitude and longitude to calculate the estimated seismic intensity at that location and the theoretical countdown to the arrival of the S wave.

[0116] S20163: Based on a three-dimensional decision matrix, generate three-dimensional decision information corresponding to each early warning terminal according to scene attributes, estimated seismic intensity and theoretical countdown time. The three-dimensional decision matrix includes scene dimension, intensity dimension and stage dimension. The scene dimension is used to store the scene attributes of the early warning terminal, the intensity dimension is used to store the estimated seismic intensity of the early warning terminal, and the stage dimension is used to store the stage information divided according to the theoretical countdown time.

[0117] In this embodiment, the scenario dimension is determined by matching the terminal type and the text style (e.g., "emergency evacuation" for schools, "emergency stop" for chemical industrial parks).

[0118] Intensity level: The alarm level is determined based on the estimated intensity (blue - safe, yellow - dangerous, orange - urgent, red - very urgent).

[0119] Stage Dimension:

[0120] If the theoretical countdown time is greater than 10 seconds: the stage is "early warning countdown", which displays the countdown number and the estimated intensity;

[0121] If 0s < theoretical countdown time ≤ 10s: the stage is "early earthquake", which will display high-frequency flashing and rapid beeping;

[0122] If the theoretical countdown time is ≤0s: the phase is "continuous vibration", indicating a need to maintain risk avoidance;

[0123] S20164: Based on the three-dimensional decision information and the corresponding display strategy package of the early warning terminal, generate the target information product corresponding to each early warning terminal;

[0124] In this embodiment, the target information product is assembled based on the three-dimensional decision information and the corresponding display strategy package of the early warning terminal. The product format can be a binary instruction package (controlling hardware switches) or a structured data package (JSON displayed on the APP), containing: {cmd: "ALARM", level: "RED", text: "Expected intensity 8 degrees, countdown 5 seconds", duration:30}.

[0125] In one optional implementation, a network topology model including forwarding nodes and early warning terminals is constructed on the earthquake service management platform. Based on the network topology model, a real-time status parameter matrix of the current network links is collected, including:

[0126] S2021: In the earthquake business management platform, the network environment of the earthquake business management platform is abstracted into a weighted directed graph to obtain a network topology model. The vertices of the weighted directed graph include the source point abstracted from the earthquake business management platform, the forwarding nodes abstracted from several earthquake precursor network nodes, and the aggregation point abstracted from several early warning terminals. The edges of the weighted directed graph are logical links connecting the source point, the forwarding nodes, and the aggregation point.

[0127] In this embodiment, node abstraction:

[0128] Source: The core switch egress IP address of the earthquake service management platform;

[0129] Relay Node: The central router of the earthquake precursor network in each province and city, CDN edge node, or core backbone node of the operator;

[0130] Sink Node: The IP address of the local area network gateway where the early warning terminal is located or the 4G / 5G base station directly connected to it;

[0131] Topology discovery: Automatically discovers network device connectivity using simple network management protocols or link-layer discovery protocols, generating an adjacency matrix as the basis for the search space of optimization algorithms;

[0132] S2022: Deploy several network monitoring probes in the network topology model;

[0133] In this embodiment, probe deployment: software or hardware probes are deployed at each forwarding node and critical link ingress;

[0134] S2023: On the earthquake operational management platform, network monitoring probes are used to collect the state parameters of each side and each node in the network topology model, obtaining the real-time state parameter matrix of the current network link. These state parameters include link bandwidth utilization. Link delay Node CPU load Memory load and packet loss rate ;

[0135] In this embodiment, the following status parameters are collected by the probe at a period of 1 second or 100 milliseconds to form a real-time status parameter matrix:

[0136] Link bandwidth utilization :unit:%;

[0137] Link Delay Unit: ms, collected via ICMP Echo or TWAMP;

[0138] Packet loss rate :unit:‰;

[0139] Node load: CPU load of forwarding nodes and memory load ;

[0140] Matrix structure: The rows of the matrix correspond to different network paths (candidate paths from the source to a certain terminal), and the columns correspond to different status indicators.

[0141] In one optional implementation, based on the real-time state parameter matrix, the African vulture optimization algorithm is used to iteratively optimize the forwarding strategy of the target information product to obtain the optimal forwarding strategy, including:

[0142] S2031: Based on the state parameter indices contained in the real-time state parameter matrix, set the fitness function of the African vulture optimization algorithm, and encode the forwarding strategy of the target information product into the position vector of the African vulture optimization algorithm;

[0143] In this embodiment, each "vulture" represents a complete forwarding strategy, assuming there are... M There are 1 early warning terminal, and each early warning terminal has 1 K Optional paths, vulture's position vector X It is M dimensional vector, X =[ ],in, For the first The path ID selected by each early warning terminal This refers to the indicator value of the early warning terminal;

[0144] S2032: Use Logistic mapping to generate chaotic sequences, and map the chaotic sequences to the solution space of the African vulture optimization algorithm to obtain the initial vulture population;

[0145] The formula is:

[0146]

[0147] In the formula, For the first n+ 1. n One chaotic variable; The stability coefficient is typically 4. This sequence is ergodic and random, which ensures that the initial vulture population is uniformly distributed in the solution space, avoiding getting trapped in local optima, and is superior to traditional random initialization. n For chaotic variable indicators;

[0148]

[0149] In the formula, The first in the initial vulture population i The initial vulture; For the first i One chaotic variable; These are the upper and lower bounds of the search space; For vulture indicator quantity;

[0150] S2033: Based on the real-time state parameter matrix, using the fitness function, calculate the fitness value of the candidate forwarding strategy corresponding to each initial vulture in the initial vulture population, and take the individual with the best fitness as the optimal individual.

[0151] S2034: Based on the fitness value, a convergence factor and Cauchy mutation mechanism are introduced to update the position of the initial vulture population, resulting in an updated vulture population.

[0152] The starvation rate corresponding to the current iteration number is calculated using the following formula:

[0153]

[0154] In the formula, Number of iterations t The hunger rate; The convergence factor; t This represents the current iteration number; T This is the threshold for the number of iterations; The first and second random numbers are in the range [0,1]. This is the hunger rate fluctuation coefficient;

[0155]

[0156] In the formula, These are the maximum and minimum values ​​of the convergence factor;

[0157] like Entering the exploration phase, random exploration numbers are generated. ,like To conduct long-distance flights to the initial vulture population, among which, To explore the threshold, the formula is:

[0158]

[0159] In the formula, Number of iterations t+ 1 ,t The i A newer vulture; Number of iterations t The i A newer vulture following the vulture; Number of iterations t The i An updated distance factor for the vulture; W This is the distance scaling factor; The third random number is [0,1].

[0160] like A random walk is performed on the initial vulture population, using the following formula:

[0161]

[0162] In the formula, The fourth and fifth random numbers are in the range [0,1].

[0163] like Entering the first development phase, random numbers for the first development phase are generated. ,like They performed circling flights over the initial vulture swarm, among which... The first development threshold is defined by the following formula:

[0164]

[0165] In the formula, The seventh and eighth random numbers are in the range [0,1]. The best and second-best individuals;

[0166] like The initial vulture population is besieged and contested using the following formula:

[0167]

[0168] In the formula, The eighth random number in the range [0,1];

[0169] like Entering the second development phase, random numbers for the second development phase are generated. ,like The initial vulture population exhibits aggregation behavior, in which... The second development threshold is given by the following formula:

[0170]

[0171] In the formula, The ninth and tenth random numbers are in the range [0,1].

[0172] like The formula for launching an attack on the initial vulture population is:

[0173]

[0174] In the formula, The eleventh random number in the range [0,1];

[0175] If the best individual does not improve for several consecutive generations, Cauchy mutation is performed on the best individual in the current iteration, and the resulting mutated vulture is added to the updated vulture population. The formula is as follows:

[0176]

[0177] In the formula, Number of iterations t+ 1. A mutated vulture; These are random numbers distributed according to the standard Cauchy distribution. The Cauchy variation scale parameter;

[0178] S2035: Based on the real-time state parameter matrix, using the fitness function, calculate the fitness value of the alternative forwarding strategies corresponding to each updated vulture in the updated vulture population, and update the individual with the best fitness as the best individual;

[0179] S2036: Repeat the position update step until the current iteration count reaches the iteration count threshold or the fitness value of the best individual meets the requirements, then end the position update;

[0180] S2037: Decode the location vector of the optimal individual to obtain the optimal forwarding strategy for the target information product.

[0181] In one alternative implementation, the fitness function is formulated as follows:

[0182]

[0183] In the formula, For vultures X The fitness value of the corresponding alternative forwarding strategies; j This refers to the indicator value of the early warning terminal; MThis represents the total number of early warning terminals; For the first j The scene priority weight of the early warning terminal is set according to the scene attributes in the target information product; For the first j The link transmission delay of the early warning terminal is the link delay of each hop on the path in the real-time status parameter matrix. sum; For the first j The queuing delay of the early warning terminal is determined based on the link bandwidth utilization rate in the real-time status parameter matrix. Settings, when When it approaches 100%, It is rising exponentially; For the first j The node processing latency of the early warning terminal is determined by the node CPU load of the distributed nodes in the real-time status parameter matrix. and memory load Obtained by linear mapping; The congestion penalty coefficient (a positive number, such as...) =1000); For vultures X The congestion penalty value for the corresponding alternative forwarding strategy is based on the link bandwidth utilization in the real-time state parameter matrix. Node CPU load and memory load Settings, if vultures X Among the corresponding alternative forwarding strategies, there is a bandwidth utilization rate for any link. If the bandwidth utilization threshold (e.g., 90%) is reached, or if the CPU / memory load of any node exceeds the safety threshold, then... =1, otherwise 0; Reliability penalty coefficient (a positive number, such as...) =2000); For vultures X The packet loss penalty value for the corresponding alternative forwarding strategy is based on the packet loss rate of all links on the path in the real-time state parameter matrix. If the total packet loss rate of the path exceeds a preset threshold (e.g., 10), the setting will be applied. −3 ),but =1, otherwise 0; X For vulture variables.

[0184] In one optional implementation, based on the optimal forwarding strategy and the scenario of the target information product, the earthquake service management platform is used to send the target information product to the corresponding early warning terminal, including:

[0185] S2041: Using the earthquake service management platform, perform policy parsing and route mapping, convert the optimal forwarding policy into executable network control instructions, and distribute them to all distribution nodes;

[0186] In this embodiment, the earthquake service management platform generates network control commands based on the optimal forwarding strategy. If an SDN (Software Defined Networking) architecture is adopted, an OpenFlow flow table is generated and distributed to the switches of the forwarding nodes. If a traditional IP network is adopted, an OSPF / BGP routing policy or a static routing configuration script is generated and distributed to forwarding nodes at all levels.

[0187] S2042: Based on the hardware limitations and network environment of different early warning terminals, the corresponding target information products are packaged in a differentiated manner to obtain packaged product data;

[0188] In this embodiment, data is trimmed and packaged according to the hardware capabilities of the early warning terminal:

[0189] High-end terminals (smart TVs, PCs): packaged as a complete JSON package, including epicenter map images, detailed waveform diagrams, and evacuation video guidance;

[0190] Low-end terminals (industrial controllers, LED screens): packaged as extremely simple binary protocols or short messages (such as EARTHQUAKE:8,5s) to reduce data volume and parsing time;

[0191] S2043: Based on the scenario dimension of the target information product, perform hierarchical QoS transmission protection and set the forwarding priority of the encapsulated product data;

[0192] In this embodiment, QoS priority is set based on the "scene dimension" and "three-dimensional decision information" in step S016:

[0193] Extremely high priority (EF level): hospitals, schools, nuclear power plants, command centers; ensure low latency and low packet loss;

[0194] High priority (AF4 level): large communities, commercial centers;

[0195] Normal priority (AF1 level): Push notifications to general public mobile apps;

[0196] When scheduling data packets in a queue, network devices prioritize forwarding packets from high-priority queues and discard low-priority packets even when the network is congested.

[0197] S2044: Using the earthquake business management platform, the encapsulated product data with forwarding priority is sent to several corresponding distribution nodes, and according to the forwarding priority and network control instructions, the distribution nodes are used to send the encapsulated product data to the corresponding early warning terminal.

[0198] In this embodiment, the distribution node pushes data packets to the physical address (IP or MAC) of the final end at high speed and accurately according to the preset flow table, QoS queue and network control instructions. After receiving the data, the warning terminal immediately parses it and executes an audible and visual alarm.

[0199] This invention also provides a scenario-based forwarding system for multi-source seismic operational data, referring to... Figure 3 The device may include the following units:

[0200] The multi-source data acquisition unit 301 is used to receive multi-source earthquake business data from different data sources using the earthquake business management platform, and to transform the multi-source earthquake business data into target information products for early warning terminals in different scenarios according to scenario attributes.

[0201] The status parameter acquisition unit 302 is used to construct a network topology model containing forwarding nodes and early warning terminals on the earthquake business management platform, and to acquire the real-time status parameter matrix of the current network link based on the network topology model.

[0202] The forwarding strategy optimization unit 303 is used to iteratively optimize the forwarding strategy of the target information product based on the real-time state parameter matrix and using the African vulture optimization algorithm to obtain the optimal forwarding strategy.

[0203] The scenario-based forwarding unit 304 is used to send the target information product to the corresponding early warning terminal using the earthquake service management platform, based on the optimal forwarding strategy and the scenario of the target information product.

[0204] Based on the same inventive concept, another embodiment of the present invention provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus.

[0205] Memory, used to store computer programs;

[0206] The processor, when executing the program stored in the memory, implements the scenario-based forwarding method for multi-source seismic service data of the present invention.

[0207] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus. The communication interface is used for communication between the aforementioned terminal and other devices. The memory can include Random Access Memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory can also be at least one storage device located remotely from the aforementioned processor.

[0208] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0209] Furthermore, to achieve the above objectives, embodiments of the present invention also propose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the scenario-based forwarding method for multi-source seismic operational data according to embodiments of the present invention.

[0210] 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 hardware devices (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0211] The embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (apparatus), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and 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 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0212] 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.

[0213] 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.

[0214] 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. "And / or" indicates that either one or both can be chosen. 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 the element.

[0215] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A scenario-based forwarding method for multi-source seismic operational data, characterized in that, The method includes: The earthquake business management platform receives multi-source earthquake business data from different data sources and transforms the multi-source earthquake business data into target information products for early warning terminals in different scenarios according to scenario attributes. The scenario attributes include the unique identifier ID of the early warning terminal, latitude and longitude coordinates, scenario type, and disaster type. In the earthquake business management platform, a network topology model including forwarding nodes and early warning terminals is constructed, and based on the network topology model, a real-time status parameter matrix of the current network links is collected. Based on the real-time state parameter matrix, the African vulture optimization algorithm is used to iteratively optimize the forwarding strategy of the target information product to obtain the optimal forwarding strategy, including: Based on the state parameter indices contained in the real-time state parameter matrix, the fitness function of the African vulture optimization algorithm is set, and the forwarding strategy of the target information product is encoded into the position vector of the African vulture optimization algorithm. The formula for the fitness function is: In the formula, For vultures X The fitness value of the corresponding alternative forwarding strategies; j This refers to the indicator value of the early warning terminal; M This represents the total number of early warning terminals; For the first j The scene priority weight of the early warning terminal is set according to the scene attributes in the target information product; For the first j The link transmission delay of the early warning terminal is the link delay of each hop on the path in the real-time status parameter matrix. sum; For the first j The queuing delay of the early warning terminal is determined based on the link bandwidth utilization rate in the real-time status parameter matrix. set up; For the first j The node processing latency of the early warning terminal is determined by the node CPU load of the distributed nodes in the real-time status parameter matrix. and memory load Obtained by linear mapping; This is the congestion penalty coefficient; For vultures X The congestion penalty value for the corresponding alternative forwarding strategy is based on the link bandwidth utilization in the real-time state parameter matrix. Node CPU load and memory load set up; This is a reliability penalty factor; For vultures X The packet loss penalty value for the corresponding alternative forwarding strategy is based on the packet loss rate of all links on the path in the real-time state parameter matrix. set up; X For vulture variables; The chaotic sequence is generated using the Logistic mapping and then mapped to the solution space of the African vulture optimization algorithm to obtain the initial vulture population. Based on the real-time state parameter matrix, the fitness function is used to calculate the fitness value of the alternative forwarding strategies corresponding to each initial vulture in the initial vulture population, and the individual with the best fitness is taken as the optimal individual. Based on the fitness value, a convergence factor and Cauchy mutation mechanism are introduced to update the position of the initial vulture population, resulting in an updated vulture population. Based on the real-time state parameter matrix, the fitness function is used to calculate the fitness value of the alternative forwarding strategies corresponding to each updated vulture in the updated vulture population, and the individual with the best fitness is updated as the best individual. Repeat the position update steps until the current iteration count reaches the iteration count threshold or the fitness value of the best individual meets the requirements, then end the position update; The optimal forwarding strategy for the target information product is obtained by decoding the location vector of the optimal individual. Based on the optimal forwarding strategy and the scenario of the target information product, the earthquake service management platform is used to send the target information product to the corresponding early warning terminal.

2. The scenario-based forwarding method for multi-source seismic operational data according to claim 1, characterized in that, The earthquake service management platform receives multi-source earthquake service data from different data sources and, based on scenario attributes, transforms this data into target information products for early warning terminals in different scenarios, including: Connect the earthquake business management platform to the earthquake business data server, and monitor and access several data sources in the earthquake business data server; The earthquake service management platform is used to receive multi-source earthquake service data from different data sources. Based on the type identifier in the message header, the corresponding parser is invoked, and the parser is used to extract the key fields of the multi-source earthquake business data from the corresponding data source; The extracted key fields are mapped to unified earthquake event objects within the earthquake business management platform, timestamped, and stored in the real-time database. Multi-source data conflict resolution and dynamic fusion are performed on several seismic event objects stored in the real-time database to obtain global seismic event parameters; Based on global earthquake event parameters and the scene attributes of the early warning terminal, target information products corresponding to the early warning terminal are generated.

3. The scenario-based forwarding method for multi-source seismic operational data according to claim 2, characterized in that, The data sources include earthquake early warning systems, earthquake rapid reporting systems, manual rapid reporting systems, and disaster assessment systems; The multi-source earthquake operational data includes earthquake early warning data, earthquake rapid reporting data, manual rapid reporting data, and disaster assessment data.

4. The scenario-based forwarding method for multi-source seismic operational data according to claim 3, characterized in that, Multi-source data conflict resolution and dynamic fusion are performed on several seismic event objects stored in the real-time database to obtain global seismic event parameters, including: A list of active seismic events is maintained in a real-time database, which is used to store existing seismic event objects in different time windows; For several earthquake event objects stored in real time, obtain the epicenter location and time of each earthquake event object and the distance between it and all existing earthquake event objects in the active earthquake event list; If the distance is less than the preset distance threshold and the timestamp difference is less than the preset time window, then the earthquake event object is classified into the corresponding existing earthquake event object. Based on the preset dynamic weights of different data sources, parameter fusion calculations are performed on several earthquake event objects stored in the real-time database to obtain global earthquake event parameters, and a state machine is maintained for each earthquake event object. Based on the state machine, when a seismic event object from a data source with higher dynamic weight is received, causing a significant jump in the global seismic event parameters, a correction event of the state machine is triggered, generating global seismic event parameters with an incrementing version number.

5. The scenario-based forwarding method for multi-source seismic operational data according to claim 4, characterized in that, Based on global seismic event parameters and the scene attributes of the early warning terminal, target information products corresponding to the early warning terminal are generated, including: Using the earthquake business management platform, the registration information of several early warning terminals is read from the terminal database, and the scene attributes in the registration information are extracted. The scene attributes include a unique identifier ID, latitude and longitude coordinates, scene type, and disaster type. The global seismic event parameters are input into the preset seismic motion attenuation equation to calculate the estimated seismic intensity of each early warning terminal and to calculate the theoretical countdown time for the seismic wave to reach the early warning terminal. Based on a three-dimensional decision matrix, three-dimensional decision information corresponding to each early warning terminal is generated according to scene attributes, estimated seismic intensity, and theoretical countdown time. The three-dimensional decision matrix includes scene dimension, intensity dimension, and stage dimension. The scene dimension is used to store the scene attributes of the early warning terminal, the intensity dimension is used to store the estimated seismic intensity of the early warning terminal, and the stage dimension is used to store stage information divided according to the theoretical countdown time. Based on the 3D decision information and the corresponding display strategy package for the early warning terminal, a target information product corresponding to each early warning terminal is generated.

6. The scenario-based forwarding method for multi-source seismic operational data according to claim 5, characterized in that, In the earthquake operational management platform, a network topology model including forwarding nodes and early warning terminals is constructed. Based on the network topology model, a real-time status parameter matrix of the current network links is collected, including: In the earthquake service management platform, the network environment of the earthquake service management platform is abstracted into a weighted directed graph to obtain a network topology model. The vertices of the weighted directed graph include the source point abstracted from the earthquake service management platform, the forwarding nodes abstracted from several earthquake precursor network nodes, and the aggregation point abstracted from several early warning terminals. The edges of the weighted directed graph are logical links connecting the source point, the forwarding nodes, and the aggregation point. Deploy several network monitoring probes in the network topology model; In the earthquake operational management platform, network monitoring probes are used to collect the state parameters of each side and each node in the network topology model, obtaining a real-time state parameter matrix of the current network links. These state parameters include link bandwidth utilization. Link delay Node CPU load Memory load and packet loss rate .

7. The scenario-based forwarding method for multi-source seismic operational data according to claim 6, characterized in that, Based on the optimal forwarding strategy and the scenario of the target information product, the earthquake service management platform is used to send the target information product to the corresponding early warning terminal, including: Using the earthquake service management platform, policy parsing and route mapping are performed to convert the optimal forwarding policy into executable network control commands and distribute them to all distribution nodes; Based on the hardware limitations and network environment of different early warning terminals, the corresponding target information products are packaged in a differentiated manner to obtain packaged product data; Based on the scenario dimension of the target information product, hierarchical QoS transmission guarantee is implemented, and the forwarding priority of the encapsulated product data is set. Using the earthquake business management platform, the encapsulated product data with forwarding priority is sent to several corresponding distribution nodes. Based on the forwarding priority and network control instructions, the distribution nodes then send the encapsulated product data to the corresponding early warning terminals.

8. A scenario-based forwarding system for multi-source seismic operational data, used to implement the scenario-based forwarding method as described in any one of claims 1-7, characterized in that, The system includes: The multi-source data acquisition unit is used to receive multi-source earthquake business data from different data sources using the earthquake business management platform, and to transform the multi-source earthquake business data into target information products for early warning terminals in different scenarios according to scenario attributes. The status parameter acquisition unit is used to construct a network topology model containing forwarding nodes and early warning terminals on the earthquake business management platform, and to acquire the real-time status parameter matrix of the current network links based on the network topology model. The forwarding strategy optimization unit is used to iteratively optimize the forwarding strategy of the target information product based on the real-time state parameter matrix and using the African vulture optimization algorithm to obtain the optimal forwarding strategy. The scenario-based forwarding unit is used to send the target information product to the corresponding early warning terminal using the earthquake business management platform, based on the optimal forwarding strategy and the scenario of the target information product.

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