Method and apparatus for adjusting device configuration based on fibre channel zoning state information

Abstract

This disclosure presents a method and apparatus for adjusting device configuration based on Fibre Channel partition status information. One specific implementation of the method includes: acquiring user partition input information and user peer port input information; generating partition port query information and peer port query information; classifying the acquired partition device port identifier information set and switch peer port identifier information set into device statuses to obtain a port identifier classification information set; determining Fibre Channel partition status information; generating Fibre Channel partition alarm information; performing alarm root cause location on the historical partition status information set and port identifier classification information set to obtain alarm root cause information; and adjusting the device configuration. This implementation can improve the accuracy of Zone-level alarms for different securities business partitions, achieve real-time monitoring of the communication effectiveness of Fibre Channel partitions, improve the accuracy and efficiency of root cause location, improve the accuracy of adjustments, and enhance the security and stability of the device.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the field of computer technology, and specifically to a method and apparatus for adjusting device configuration based on Fibre Channel partition status information. Background Technology

[0002] Fibre Channel Storage Area Network (FC-SAN) is a core infrastructure of enterprise-level storage systems, widely used in critical business scenarios such as finance, telecommunications, and government. SAN storage is suitable for the needs of securities companies for high-concurrency read / write and efficient data access. Furthermore, when storage devices storing securities data fail, large-scale data migration is unnecessary, making fault maintenance more convenient and meeting the requirements of securities companies for minute-level fault recovery. In an FC-SAN network, a Zone is an important security isolation mechanism, suitable for isolated storage for different securities businesses within a securities company. Zone configuration controls the communication between servers and storage devices. Therefore, monitoring the status of devices within a Zone ensures the security of business scenarios and data. For device configuration adjustments based on Fibre Channel partition status information, the common approach is to: perform port status detection using device heartbeat or polling methods to obtain the physical link status information set of each device within the zone; then, determine the valid status information set of each device using the physical link status information set; finally, generate device alarm information based on the valid status information set, and perform root cause detection based on the device alarm information to adjust the device configuration of each device.

[0003] However, in practice, it has been found that when adjusting device configurations based on Fibre Channel partition status information using the above method, the following technical problems often arise: Since only port online status detection is performed without considering the correctness of Zone configuration, it is impossible to provide early warnings of service interruption risks, which does not meet the requirements of securities companies regarding fault operation and maintenance. This results in a large number of securities transactions being unable to proceed, causing serious cost losses. Furthermore, port status detection needs to be performed manually, resulting in low detection efficiency and a high error rate. Simultaneously, the generation of alarm information for devices lacks Zone-level status aggregation and judgment, making it difficult to effectively utilize the topology structure and quickly locate high-risk Zones, increasing the device damage rate and reducing device security.

[0004] The information disclosed in this background section is only intended to enhance the understanding of the background of the present disclosure concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0006] Some embodiments of this disclosure propose a device configuration adjustment method and apparatus based on Fibre Channel partition status information applicable to the securities field, in order to solve one or more of the technical problems mentioned in the background section above.

[0007] In a first aspect, some embodiments of this disclosure provide a device configuration adjustment method based on Fibre Channel partition status information, comprising: in response to detecting successful login to each Fibre Channel switch included in the Fibre Channel network topology diagram, acquiring user partition input information and user peer port input information; generating partition port query information and peer port query information based on the user partition input information and the user peer port input information; acquiring a partition device port identifier information set and a switch peer port identifier information set based on the partition port query information and the peer port query information; performing device status division processing on the partition device port identifier information set and the switch peer port identifier information set to obtain a port identifier division information set; determining the Fibre Channel partition status information of the Fibre Channel partition corresponding to the partition device port identifier information set based on the port identifier division information set; generating Fibre Channel partition alarm information based on the Fibre Channel partition status information; performing alarm root cause location on the acquired historical partition status information set and the port identifier division information set based on the Fibre Channel partition alarm information to obtain alarm root cause information; and adjusting the device configuration of each device included in the Fibre Channel network topology diagram based on the alarm root cause information.

[0008] Secondly, some embodiments of this disclosure provide a device configuration adjustment apparatus based on Fibre Channel partition status information, comprising: a first acquisition unit configured to acquire user partition input information and user peer port input information in response to detecting successful login to each Fibre Channel switch included in the Fibre Channel switching network topology map; a first generation unit configured to generate partition port query information and peer port query information based on the user partition input information and the user peer port input information; a second acquisition unit configured to acquire a partition device port identifier information set and a switch peer port identifier information set based on the partition port query information and the peer port query information; and a device status division unit configured to classify the partition device port identifiers. The information set and the aforementioned switch peer port identification information set are processed for device status partitioning to obtain a port identification partitioning information set; a determination unit is configured to determine the fiber optic partition status information of the fiber channel partition corresponding to the aforementioned partition device port identification information set based on the aforementioned port identification partitioning information set; a second generation unit is configured to generate fiber optic partition alarm information based on the aforementioned fiber optic partition status information; an alarm root cause location unit is configured to perform alarm root cause location on the acquired historical partition status information set and the aforementioned port identification partitioning information set based on the fiber optic partition alarm information to obtain alarm root cause information; and a device configuration adjustment unit is configured to adjust the device configuration of each device included in the aforementioned fiber optic switching network topology based on the aforementioned alarm root cause information.

[0009] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, such that when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any implementation of the first aspect.

[0010] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method as described in any implementation of the first aspect.

[0011] The above embodiments of this disclosure have the following beneficial effects: The device configuration adjustment method based on Fibre Channel partition status information in some embodiments of this disclosure can improve the accuracy of Zone-level alarms for different securities business partitions, realize real-time monitoring of the communication effectiveness of Fibre Channel partitions, improve the accuracy and efficiency of root cause localization, improve the accuracy of adjustment, and improve the security and stability of the device. Specifically, the reasons for the inability to provide early warnings, the increase in device damage rate, and the reduction in device security are as follows: Since only port online status detection is performed without considering the correctness of Zone configuration, it is impossible to provide early warnings of business interruption risks, which does not meet the requirements of securities companies for fault operation and maintenance, resulting in a large number of securities transactions being unable to be carried out, causing serious cost losses. Furthermore, port status detection needs to be performed manually, resulting in low detection efficiency and a high detection error rate. At the same time, the generation of alarm information for the device lacks Zone-level status aggregation judgment, making it difficult to effectively utilize the topology structure and quickly locate high-risk Zones, increasing the device damage rate and reducing device security. Based on this, the device configuration adjustment method based on Fibre Channel partition status information in some embodiments of this disclosure can first, in response to the detection of successful login to the Fibre Channel switching network topology map including each Fibre Channel switch, obtain user partition input information and user peer port input information. Here, user partition input information and user peer port input information are used to generate different types of query information, namely CLI (Command-line Interface) query statements, to obtain device identification information of each device included in the fiber optic switching network topology. Secondly, based on the aforementioned user partition input information and user peer port input information, partition port query information and peer port query information are generated. This improves the accuracy of the generated query information regarding Zone configuration and current port status, reduces user learning difficulty, and enhances user experience. Thirdly, based on the aforementioned partition port query information and peer port query information, a set of partition device port identification information and a set of switch peer port identification information are obtained. Here, the CLI query statement can simultaneously obtain the partition terminal identification information representing the correctness of the Zone configuration and the set of switch peer port identification information representing the online status of the device ports, facilitating early detection of offline devices for early warning, reducing the risk of service interruption, and improving detection efficiency and accuracy. Finally, the aforementioned set of partition device port identification information and the aforementioned set of switch peer port identification information are processed to classify device status, resulting in a port identification classification information set. Here, the device status segmentation process can accurately classify whether each device is online or offline, and subsequently confirm the status at the partition area level. Then, based on the aforementioned port identifier segmentation information set, the fiber optic partition status information of the Fibre Channel partition corresponding to the aforementioned partitioned device port identifier information set is determined.Here, classifying information sets by port identifiers improves the determination of device validity at the Zone level, facilitating subsequent area-level alarms. Next, based on the aforementioned fiber optic zone status information, fiber optic zone alarm information is generated. Generating area-level alarm information improves the accuracy and conciseness of alarm data, facilitating overall root cause analysis and improving its efficiency. Then, based on the fiber optic zone alarm information, alarm root cause analysis is performed on the acquired historical zone status information set and the aforementioned port identifier classification information set to obtain the alarm root cause information. Here, area-level alarm root cause analysis effectively utilizes the topology to quickly locate high-risk Zones, improving the efficiency and accuracy of root cause analysis, enhancing device security and stability, and reducing device failure rates. Finally, based on the aforementioned alarm root cause information, device configuration adjustments are made to each device included in the aforementioned fiber optic switching network topology. This improves the accuracy and efficiency of device configuration adjustments, reduces the time of device failures, and enhances the stability of the Fibre Channel storage area network corresponding to the fiber optic switching network topology. Therefore, this device configuration adjustment method based on Fibre Channel partition status information can improve the accuracy of Zone-level alarms in different securities business partitions, realize real-time monitoring of the communication effectiveness of Fibre Channel partitions, improve the accuracy and efficiency of root cause location, improve the accuracy of adjustment, and improve the security and stability of the equipment. Attached Figure Description

[0012] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0013] Figure 1 This is a flowchart of some embodiments of the device configuration adjustment method based on Fibre Channel partition status information according to the present disclosure; Figure 2 This is a schematic diagram of the structure of some embodiments of the device configuration adjustment apparatus based on Fibre Channel partition status information according to the present disclosure; Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0014] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0015] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0016] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0017] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0018] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0019] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] Figure 1 A flowchart 100 is shown illustrating some embodiments of a device configuration adjustment method based on Fibre Channel partition status information according to this disclosure. This device configuration adjustment method based on Fibre Channel partition status information includes the following steps: Step 101: In response to detecting successful login to the various Fibre Channel switches included in the Fibre Channel network topology diagram, obtain user partition input information and user peer port input information.

[0021] In some embodiments, the execution entity (e.g., an electronic device) of the above-described device configuration adjustment method based on Fibre Channel partition status information can, in response to detecting successful login to the various Fibre Channel switches included in the Fibre Channel switching network topology, acquire user partition input information and user peer port input information. The aforementioned Fibre Channel switching network topology can be a Fabric, a switched network structure used to connect multiple securities servers and securities data storage devices. The aforementioned Fibre Channel switch can be a high-speed network switching device (FC) designed for the Fibre Channel protocol. The aforementioned user partition input information can be input information used by the user to query the device port information of the partition device set included in the Zone configuration database. The aforementioned Zone configuration database can be configuration information used by the user in the Fibre Channel switch to achieve access control and fault isolation of securities business data of various securities data storage devices by logically dividing device groups. The aforementioned configuration information can indicate that the various securities data storage devices included in the same Zone can communicate with each other, that different Zones are isolated from each other, and that there is a hierarchy configuration between devices, Fibre Channel switches, and Zones. A Zone can include one or more Fibre Channel switches and various devices connected in communication. The aforementioned partition device set can be a set of devices authorized to communicate with each other within a Fibre Channel network on the Fibre Channel switching network topology. This partition device set can include: devices acting as initiators / hosts (e.g., server hosts, application servers), devices acting as destinations / storages (e.g., storage area network arrays, tape libraries), and FC switches. The aforementioned user peer port input information can be input information used by the user to query all port information of the various Fibre Channel switches included in the Fabric. These various Fibre Channel switches can be at least two Fibre Channel switches. The aforementioned user partition input information and user peer port input information can be natural language information of the CLI query statement describing the query information, or information from an incomplete CLI query statement.

[0022] Step 102: Generate partition port query information and peer port query information based on user partition input information and user peer port input information.

[0023] In some embodiments, the execution entity can generate partition port query information and peer port query information based on the user partition input information and the user peer port input information. The partition port query information can be a query code used to query the WWPN (World Wide Port Name) of all partition devices within a Zone. For example, the partition port query information can be "zoneshow Zone_Zone01", where Zone_Zone01 can be the zone name. The peer port query information can be a query code used to query the WWPN of peer devices for all FC switch ports in a Fabric. For example, the peer port query information can be "portshow".

[0024] As an example, the aforementioned execution entity can input the user partition input information and the user peer port input information into a large language model to obtain initial generated partition port query information and initial peer port query information. The aforementioned large language model can be, but is not limited to, at least one of the following: DeepSeek model, ChatGPT (Chat Generative Pre-trained Transformer), or NExT-GPT model. Then, the initial generated partition port query information and the initial peer port query information are manually verified to obtain the generated partition port query information and peer port query information.

[0025] In the process of adopting technical solutions to address the technical problems mentioned above, the following technical issues often arise in the application scenario: the scenario of completing the query statement for the status of optical fiber communication within the same zone of a securities company, including securities trading equipment, which involves root cause localization. Securities companies often use optical fiber switches from different manufacturers. Due to significant differences in zone configuration syntax among these manufacturers, and the existence of numerous custom securities equipment and zone names, spelling errors in zones can easily lead to information isolation failures between different business units within the securities company, failing to meet industry requirements. Furthermore, securities companies need to process massive amounts of trading data, especially during market opening hours, and have zero tolerance for zone failures. They need to quickly locate and collect data from each zone for judgment. However, the Seq2Seq model suffers from gradient vanishing when the query statement sequence to be completed is long, consuming significant computational resources. Moreover, error accumulation occurs during multi-step prediction, resulting in low accuracy of the generated completed query statement, increased waste of memory resources, low completion efficiency, and prolonged data acquisition time. To address the following requirements of this application scenario: adapting to word pair concatenation and combination of attribute values, adapting to the embedding of tree structure features in the query statement, adapting to query statement completion, and adapting to long-distance dependencies in the query statement to be completed, we have decided to adopt the following solution: In some optional implementations of certain embodiments, generating partition port query information and peer port query information based on the user partition input information and the user peer port input information may include the following steps: The first step, for the user partition input information mentioned above, is to perform the following generation steps: Sub-step 1 involves extracting contextual features from the aforementioned user partition input information to obtain the query feature vector to be completed for the partition port query information. This query feature vector represents the semantic intent information of the user partition input information. The contextual feature extraction can be performed using a lightweight BERT (Bidirectional Encoder Representations from Transformers) model.

[0026] Sub-step 2 involves generating a target variable-length word sequence based on a preset query corpus and the aforementioned user partition input information. The preset query corpus can be an offline-built database composed of query attribute values ​​from historical query statements, conforming to the query requirements defined by various switch manufacturers. These query attribute values ​​may include, but are not limited to, at least one of the following: the name of the securities business zone, the name of the fabric, and the names of the devices storing securities trading data within the zone. The target variable-length word sequence can be a word sequence formed by combining words from the preset query corpus, or it can be a single word from the preset query corpus. In practice, the executing entity can first, in response to determining that the current word to be completed in the user partition input information does not exist in the preset query corpus, use a greedy algorithm to segment the current word to be completed using the preset query corpus to obtain the target variable-length word sequence. For example, the current word to be completed could be "Server_Web", and the target variable-length word sequence could include: "Ser", "ver", "_", "Web", " / w". Then, in response to determining that the current word to be completed exists in the preset query corpus, the word matching the current word to be completed is queried in the preset query corpus as the target variable-length word sequence.

[0027] The aforementioned preset query corpus is obtained through the following steps: The first sub-step involves character splitting of the historical query statement set, including the historical query attribute value set, to obtain an initial word list. The historical query statements in the aforementioned historical query statement set can be all CLI query statements entered by the user before the current time. The historical query attribute values ​​in the aforementioned historical query attribute value set can be attribute values ​​corresponding to fields in the CLI query statements. For example, the aforementioned historical query attribute values ​​can be the name of a Zone. The aforementioned initial word list also includes reserved words and the terminator " / w". The aforementioned reserved words can be query keywords in the CLI query statements. For example, the aforementioned reserved words can include, but are not limited to, at least one of the following: zoneshow, zone, portshow. The aforementioned character splitting can be performed on a character-by-character basis, and reserved words are not split.

[0028] The second sub-step involves iteratively merging character pairs in the initial word list to obtain the target word list, which serves as the preset query corpus. The target word list can be a word list containing a fixed number of words. This fixed number of words can be a pre-set quantity, and its specific value can be determined based on specific circumstances; no limitation is made here. In practice, the executing entity can first determine the frequency of occurrence of character pairs formed by adjacent words in the initial word list using the historical query statement set, obtaining a character pair frequency set. Next, it concatenates and merges the adjacent word pairs corresponding to the character pair with the highest frequency value in the character pair frequency set, obtaining a concatenated word. Then, it adds the concatenated word to the initial word list, obtaining an added word list, and removes the word pairs corresponding to the concatenated word from the added word list, obtaining the target word list. Finally, in response to determining that the number of target words in the target word list is greater than or equal to the fixed number of words, the target word list is determined as the preset query corpus. In response to the determination that the number of target words included in the target word list is less than the fixed number of words, the corresponding steps from first to then are executed again until the condition of being greater than or equal to the fixed number of words is met.

[0029] Sub-step 3 involves mapping and aggregating the target variable-length word sequence to obtain the feature vector of the query node to be completed. This feature vector can be a word embedding vector representing the semantic information of the current word to be completed corresponding to the user partition input information. In practice, the execution entity can first determine the multi-dimensional word vectors corresponding to the target variable-length word sequence through a table lookup operation, obtaining a word vector set. Then, a max-pooling layer is used to pool, aggregate, and compress the word vector set, obtaining pooled word vectors. Finally, word embedding is performed on the field type of the query statement corresponding to the current word to be completed, obtaining a field type word embedding vector. This field type can be the node type of the abstract syntax tree corresponding to the current word to be completed in the CLI statement. The field type can be Zone_Name. Finally, the field type word embedding and the pooled word vector are concatenated to obtain the feature vector of the query node to be completed.

[0030] Sub-step 4: Based on the feature vectors of the query nodes to be completed, perform vector embedding processing on each query node in the abstract syntax tree corresponding to the user partition input information to obtain a set of query node feature vectors. The query node includes: the node type of the query node and the attribute value corresponding to the query node. The query node can be a statement word and its corresponding attribute value in the partition port query information. When the query statement node does not have an attribute value, the attribute value is set to empty. For example, the partition port query information can be zoneshow Zone_Zone01. The query statement node can be zoneshow and empty, or Zone_name and Zone_Zone01. The abstract syntax tree can be a syntax tree that represents the parent-child hierarchical and subordinate relationships between the various words included in the partition port query information in a tree structure. Each node in the abstract syntax tree can be a semantic unit, i.e., each word. The abstract syntax tree can be a syntax tree obtained by inputting the user partition input information into a constructed fixed syntax tree template. In practice, the execution entity can first input the user partition input information into the abstract syntax tree template to obtain the abstract syntax tree. Then, through a table lookup operation, vector embedding is performed on each query node in the abstract syntax tree after removing the query node corresponding to the current word to be completed, to obtain the target query node feature vector set. Finally, the target query node feature vector set and the query node feature vectors to be completed are determined as the query node feature vector set.

[0031] Sub-step 5 involves inputting the aforementioned query node feature vector set into the query completion encoder included in the query completion model to obtain the query completion hidden feature vector set. The query completion model further includes a query completion decoder. The query completion model can be a deep neural network model that predicts the current input information from the input query node feature vector set and outputs partition port query information. The query completion encoder can be an encoder that propagates features along the edges of the abstract syntax tree using the message passing mechanism of a gated graph neural network (GGNN) to obtain the structure-aware feature vectors of the query nodes. The query completion hidden feature vector set can be feature vectors that capture the dependency relationship between the parent query node and the missing attribute value node, i.e., the child node.

[0032] Sub-step 6 involves fusing the hidden feature vector set for query completion and the query feature vector to be completed, then inputting the fused features into the query completion decoder to obtain the partition port query information. The network structure of the query completion decoder can be a two-layer GRU model and a regression / classification layer decoder. The regression / classification layer can be a fully connected layer including a Softmax activation function, and the query completion decoder can be a Transformer model decoder. The feature fusion can be feature concatenation or cross-attention calculation.

[0033] The second step is to determine the above-mentioned user peer port input information as user partition input information, and to execute the above-mentioned generation steps to obtain peer port query information, and to execute the above-mentioned partition port query information and the above-mentioned peer port query information to obtain the partition device port identification information set and the switch peer port identification information set.

[0034] The above-mentioned technical solution and related content, as an inventive point of this disclosure, solve the technical problem of "low accuracy of the generated completed query statement, increased waste of memory resources, low completion efficiency, and prolonged data acquisition time". The factors leading to low accuracy of the generated completed query statement, increased waste of memory resources, low completion efficiency, and prolonged data acquisition time are often as follows: Securities companies often use fiber optic switches from different manufacturers. Due to significant differences in the Zone configuration syntax of each manufacturer, and the existence of a large number of custom securities equipment and Zone names, spelling errors in Zones can easily cause information isolation failures between different businesses of the securities company, which does not meet the requirements of the securities industry. Furthermore, securities companies need to process massive amounts of transaction data, especially during opening hours, and have zero tolerance for Zone failures. They need to quickly locate and collect data from each Zone for judgment. However, the Seq2Seq model suffers from the gradient vanishing problem when the query statement sequence to be completed is long, requiring a large amount of computational resources. Moreover, there is an error accumulation problem during multi-step prediction, resulting in low accuracy of the generated completed query statement, increased waste of memory resources, low completion efficiency, and prolonged data acquisition time. Solving the above factors can improve the accuracy of the generated completed query statement, reduce memory waste, improve completion efficiency, and shorten data acquisition time. To achieve this effect, this disclosure first extracts contextual features from the user partition input information. Based on the preset query corpus and user partition input information, a target indefinite-length sub-word sequence is generated. Contextual feature extraction can accurately identify the overall intent and contextual information of the user query, providing global semantic guidance for subsequent query statement completion. By iteratively generating a general vocabulary and target indefinite-length sub-sequence through historical query statements from various vendors, adapting to the syntax rules of various vendors can accommodate the differences in syntax between different vendors, reduce the isolation problem between securities businesses caused by splicing errors, effectively alleviate the OOV (Out-Of-Vocabulary) problem caused by custom attribute values, and at the same time take into account known vocabulary, reducing the workload of encoding words that have not appeared before. By merging high-frequency sub-word pairs, the length of the target indefinite-length sub-sequence can be shortened, reducing the computational workload of subsequent completion encoding and reducing the consumption of computing resources. Secondly, the initial word list is iteratively merged character pairs to compress and merge sub-word sequences of varying lengths into fixed-dimensional feature vectors. This meets the input requirements of the subsequent query completion model, reduces the sequence length and the amount of data processed for intermediate word vector representations, and reduces the waste of computing resources.Then, the query statement node feature vector set is sequentially input into the query completion encoder included in the query completion model. In the abstract syntax tree, regardless of the length of the query statement sequence to be completed, the distance from the root node to the leaf node is fixed, i.e., the depth of the tree. The query completion encoder can pass the syntactic constraints of the root node to the leaf node to be completed through graph message passing, which can effectively model long-distance dependencies and effectively reduce the gradient vanishing problem of the long short-term memory neural network model. Afterwards, the query completion hidden feature vector set and the query feature vector to be completed are fused and input into the query completion decoder. The syntactic constraints and restricted decoding of the query completion decoder can make selections within a very small range of query combination attribute value sets generated from the input information set to be completed. The candidate space is greatly compressed, which can effectively avoid the problem of error divergence caused by garbled characters and illegal characters. Finally, partition port query information and peer port query information are generated. Based on historical query statements, each query term is automatically completed, reducing the generation of erroneous queries and achieving full traceability, meeting the securities industry's requirements for verification and record-keeping. This improves the accuracy of each predicted query term set, increases the accuracy of query statements, reduces redundant calculations, and improves completion efficiency. Finally, based on the partition port query information and peer port query information, the partition device port identifier information set and the switch peer port identifier information set are obtained, improving the accuracy of query results and shortening data acquisition time, meeting the securities company's requirements for zero tolerance for faults and rapid, low-latency data collection and querying.

[0035] Step 103: Based on the partition port query information and the peer port query information, obtain the partition device port identification information set and the switch peer port identification information set.

[0036] In some embodiments, the execution entity can obtain a set of partition device port identifiers and a set of switch peer port identifiers based on the partition port query information and the peer port query information. The partition device port identifiers in the partition device port identifiers set can be the WWPN information of the partition device set. For example, the partition device port identifiers can be "21:00:00:24:ff:12:34:56". The switch peer port identifiers in the switch peer port identifiers set can be the WWPN information of the peer devices of all FC switches in the Fabric. For example, the switch peer port identifiers can be "21:00:00:24:ff:12:34:56".

[0037] In some optional implementations of certain embodiments, obtaining the partition device port identifier information set and the switch peer port identifier information set based on the partition port query information and the peer port query information may include the following steps: The first step is to execute the aforementioned partition port query to obtain the partition query results. These results can be the WWPN information of all devices within the Zone returned by the query. For example, the partition query results could be: zone name: Zone_Zone01 members:21:00:00:24:ff:12:34:56 21:00:00:24:ff:12:34:57 50:0a:09:81:ab:cd:ef:01 50:0a:09:81:ab:cd:ef:02. In practice, the executing entity can first remotely log in to the various Fibre Channel switches within the Zone via SSH (Secure Shell), or connect to the Console interface of each Fibre Channel switch within the Zone via a physical serial interface. This physical serial interface can be an RS-232 (Asynchronous Transfer Standard) interface. Then, in response to successful login, the above partition port query information is executed to obtain the partition query result information.

[0038] The second step is to extract data from the above partition query results to obtain the partition device port identifier information set. In practice, the executing entity can first extract data from the above partition query results using regular expressions based on securities-standard hard-coded regular expressions to obtain the partition device port identifier information set. The reason for using regular expressions based on securities-standard hard-coded regular expressions is that device aliases in the securities field typically follow strict naming conventions, and general, broad regular expressions cannot be used; instead, regular expressions based on securities-standard hard-coded regular expressions are preferred. For example, the above regular expression based on securities-standard hard-coded regular expressions could be "^(Site)-(Biz)-(App)-(Role)-(Seq)$".

[0039] The third step is to execute the aforementioned peer port query to obtain the peer port query results. These results can be information about the peer devices connected to the ports of each Fibre Channel switch. In practice, the executing entity can first remotely log in to the various Fibre Channel switches included in the Fabric via SSH (Secure Shell), or connect to the Console interface of each Fibre Channel switch in the Fabric via a physical serial interface. This physical serial interface can be an RS-232 (Asynchronous Transfer Standard) interface. Then, in response to successful login, the peer port query is executed to obtain the peer port query results.

[0040] The fourth step is to extract the target fields from the above peer port query results to obtain the switch peer port identification information set. In practice, the above execution entity can use regular expressions to extract the target fields of the above peer port query results in a key-value pair structure to obtain the switch peer port identification information set. The target field in the above target field extraction can be the WWPN field of the peer device's port. For example, the target field could be "portWwn" in "portWwn ofdevice(s) connected: 21:00:00:24:ff:12:34:56".

[0041] Step 104: Perform device status partitioning processing on the partition device port identifier information set and the switch peer port identifier information set to obtain the port identifier partitioning information set.

[0042] In some embodiments, the executing entity may perform device status segmentation processing on the partitioned device port identifier information set and the switch peer port identifier information set to obtain a port identifier segmentation information set. The port identifier segmentation information set may be a grouped set obtained by grouping the port identifier information sets according to the online and offline status of the device sets corresponding to the partitioned device port identifier information set and the switch peer port identifier information set. The port identifier segmentation information set may include: a port identifier information set corresponding to an online device set and a port identifier information set corresponding to an offline device set.

[0043] In some optional implementations of certain embodiments, the above-mentioned device state partitioning process for the partitioned device port identifier information set and the switch peer port identifier information set to obtain a port identifier partitioning information set may include the following steps: The first step involves converting the aforementioned set of port identifiers for the partitioned devices and the aforementioned set of port identifiers for the peer switches to their case values, resulting in converted sets of port identifiers for the partitioned devices and the peer switches. The converted port identifiers for the partitioned devices in the converted set can be either entirely uppercase or entirely lowercase. Similarly, the converted port identifiers for the peer switches in the converted set can also be either entirely uppercase or entirely lowercase. Both sets of port identifiers for the partitioned devices and the peer switches have the same representation: all uppercase characters are represented in uppercase, and all lowercase characters are represented in lowercase.

[0044] The second step is to determine the difference between the converted partition device port identification information set and the converted switch peer port identification information set, which will be used as the offline device identification information set.

[0045] The third step is to determine the intersection of the converted partition device port identification information set and the converted switch peer port identification information set, which will be used as the online device identification information set.

[0046] The fourth step involves extracting fields from the partition port query information and the peer port query information corresponding to the above-mentioned partition query results and peer port query results to obtain the first device type information and the second device type information. The first device type information can be the device type information located at the initiating end. The second device type information can be the device type information located at the target end.

[0047] Fifth, from the aforementioned offline device identifier information set and the aforementioned online device identifier information set, respectively, filter out device identifier information with device type first device type information and device type second device type information to obtain the first online device identifier information set, the second online device identifier information set, the first offline device identifier information set, and the second offline device identifier information set. Specifically, the first online device identifier information in the first online device identifier information set can be device information where the device is located at the initiating end and its status is online. The second online device identifier information in the aforementioned second online device identifier information set can be device information where the device is located at the target end and its status is online. The first offline device identifier information in the first offline device identifier information set can be device information where the device is located at the initiating end and its status is offline. The second offline device identifier information in the second offline device identifier information set can be device information where the device is located at the target end and its status is offline.

[0048] The sixth step is to determine the first online device identification information set, the second online device identification information set, the first offline device identification information set, and the second offline device identification information set as the port identification partitioning information set.

[0049] Step 105: Based on the port identifier, divide the information set and determine the fiber optic partition status information of the fiber channel partition corresponding to the port identifier information set of the partition device.

[0050] In some embodiments, the execution entity can determine the fiber channel status information of the Fibre Channel partition corresponding to the port identifier information set of the partitioned device based on the port identifier partitioning information set. The Fibre Channel partition can be a Zone obtained by configuring the fiber switching network topology. The fiber channel status information can characterize the overall validity status of the Fibre Channel partition. As an example, the execution entity can first determine the number of port identifiers corresponding to the offline device sets included in the port identifier partitioning information set, as the number of offline devices. Then, it can determine the number of partition device port identifiers included in the partitioned device port identifier information set, as the number of partitioned devices. Next, it can determine the ratio of the number of offline devices to the number of partitioned devices, as the validity value. Finally, it can determine the fiber channel status information corresponding to the validity value through a status validity mapping table. The status validity mapping table can be a form recording the mapping relationship between validity values ​​and partition validity status information. For example, the above-mentioned state validity mapping table may include: when the validity value is 0, the fully valid state information is used as the fiber partition state information; when the validity value is in the range of (0, 50%), the downgraded valid state information is used as the fiber partition state information; when the validity value is in the range of [50%, 100%], the invalid state information is used as the fiber partition state information.

[0051] In some optional implementations of certain embodiments, determining the fiber optic partition status information of the Fibre Channel partition corresponding to the partitioned device port identifier information set based on the aforementioned port identifier partitioning information set may include the following steps: The first step is to determine the device identifier weight of each online device identifier in the aforementioned partitioned device port identifier information set and the corresponding online device identifier information set in the aforementioned port identifier partitioning information set, thus obtaining a device identifier weight set. The device identifier weight in this set can be the weight information of the type of securities business executed by the online device corresponding to the online device identifier in the securities device corresponding to the securities device in the fiber optic switching network topology. For example, the aforementioned securities business type can be a business type undertaking the main business of securities trading (e.g., matching trading, order placement trading, core clearing, etc.) or the operation of key services (e.g., risk control, third-party securities custody, margin trading, etc.), with the highest device priority for the key type, then the device identifier weight can be 1.0. The aforementioned business type can be a business type undertaking general business services or support business services (e.g., internal enterprise reporting services, email system services, parallel testing services, disaster recovery standby services), with the device priority second only to the key type, then the device identifier weight can be 0.8. The aforementioned business type can be a business type used for securities data testing or backup, then the device identifier weight can be 0.5. The above service type can be a service type where a physical HBA (Host Bus Adapter) port registers multiple different port identification information on a Fibre Channel switch, in which case the device identification weight can be 0.3.

[0052] The second step is to determine the sum of the device identifier weight sets corresponding to the above-mentioned partition device port identifier information sets, to obtain the partition weight sum, and to determine the sum of the device identifier weight sets corresponding to the above-mentioned online device identifier information sets, to obtain the online weight sum.

[0053] The third step is to determine the product of the ratio of the above-mentioned online weight sum to the above-mentioned partition weight sum and a preset value, which is used as the partition status value of the above-mentioned fiber channel partition. The preset value can be a pre-defined value. For example, the preset value can be 60.

[0054] The fourth step is to determine the device redundancy penalty and device stability penalty for the offline device identifier information set corresponding to the aforementioned port identifier partitioning information set. The device redundancy penalty can be determined by whether the device corresponding to the offline device identifier information set still has an online communication path, i.e., whether it is a single point of failure. If not, 15 is deducted from the partition status value; if so, a penalty is applied. The device stability penalty can be determined by the number of times the device corresponding to the aforementioned partition device port identifier information set transitions between offline and online states within a historical preset time period. If the number of state transitions is greater than or equal to 3, 15 is deducted from the partition status value; if it is less than 3, no penalty is applied. The aforementioned historical preset time period can be a pre-set duration, such as 1 hour.

[0055] The fifth step is to determine the difference between the aforementioned partition status value and the aforementioned device redundancy penalty item and device stability penalty item to obtain the partition target status value. The aforementioned partition target status value can be the difference between the partition status value and the aforementioned device redundancy penalty item, or the difference between the device stability penalty item and the partition target status value.

[0056] Step 6: Divide the target state values ​​of the aforementioned partitions into states to obtain fiber optic partition state information. In practice, the executing entity can use a state value mapping table to divide the target state values ​​of the aforementioned partitions into states to obtain fiber optic partition state information. This state value mapping table can be a form recording the mapping relationship between the target state values ​​of the partitions and the fiber optic partition state information. For example, if the target state value in the state value mapping table is in the range of [90, 100], then the fiber optic partition state information can be a fully valid state where all devices in the Zone are online. If the target state value in the state value mapping table is in the range of [60, 89], then the fiber optic partition state information can be the first degraded state information during the single-controller maintenance period where non-core devices in the Zone are offline and core devices are all online. If the target state value in the state value mapping table is in the range of [30, 59], then the fiber optic partition state information can be the second degraded state information where core devices in the Zone are offline but services are not completely blocked. The records in the above state value mapping table can be partition target state values ​​within the range of [0, 29], then the fiber optic partition state information can be invalid partition state information.

[0057] Optionally, the above method may further include the following steps: The first step is to determine that the first online device identifier information set included in the above port identifier partitioning information set is an empty set, and then determine the partition invalid status information as the fiber optic partition status information of the fiber channel partition.

[0058] The second step is to determine that the second online device identification information set included in the above port identification partitioning information set is an empty set, and to determine the partition invalid status information as the fiber optic partition status information of the fiber channel partition.

[0059] Step 106: Generate fiber optic partition alarm information based on fiber optic partition status information.

[0060] In some embodiments, the aforementioned execution entity can generate fiber optic partition alarm information based on the aforementioned fiber optic partition status information. This fiber optic partition alarm information can be an alarm message indicating that the fiber optic partition status information has transitioned from a valid state to a downgraded valid state or a partition invalid state, and is sent to the management user terminal (e.g., computer, mobile phone) via various transmission methods. Alternatively, it can be an alarm message containing the operating status information of each device within the Zone when it is in a downgraded valid state or a partition invalid state, and sent to the management user terminal. These various transmission methods may include, but are not limited to, at least one of the following: email, SMS, or an event-driven notification mechanism based on the SNMP (Simple Network Management Protocol) trap. In practice, the aforementioned execution entity can, in response to determining that the fiber optic partition status information has downgraded compared to the previous period, add the partition status downgrade and the operating status of each device within the Zone to the alarm template to obtain the fiber optic partition alarm information. The aforementioned alarm template can be a pre-set template used for alarms. In response to determining that the above fiber optic partition status information is either downgraded valid status information or partition invalid status information, the operating status information set of each device and the fiber optic partition status information are input into the alarm template to obtain fiber optic partition alarm information.

[0061] Step 107: Based on the fiber optic partition alarm information, perform alarm root cause location on the acquired historical partition status information set and port identifier partition information set to obtain alarm root cause information.

[0062] In some embodiments, the aforementioned execution entity can perform alarm root cause localization on the acquired historical partition status information set and the aforementioned port identifier partitioning information set based on the fiber optic partition alarm information to obtain alarm root cause information. The historical partition status information in the aforementioned historical partition status information set can be the overall validity status information of the acquired Zone area prior to the current time. The aforementioned alarm root cause information can be the fundamental reason why the aforementioned fiber optic partition alarm information appears in the Zone area, i.e., information tracing back to the abnormal device or the abnormal performance of the device.

[0063] In some optional implementations of certain embodiments, the above-mentioned method of locating the root cause of alarms based on the acquired historical partition status information set and the aforementioned port identifier partitioning information set, to obtain the root cause information of the alarms, may include the following steps: The first step involves generating a port anomaly communication topology graph based on the port identifier partitioning information set, in response to the aforementioned fiber optic partitioning alarm information indicating an invalid partition state. This port anomaly communication topology graph can be a sub-graph of the topology graph containing anomaly communication, constructed using the lines connecting the device port identifiers of the initiating device and the device port identifiers of the destination device as edges, and the devices included in the Zone as nodes. In practice, the port information communication relationships and anomaly information are extracted from the aforementioned port identifier partitioning information set and the aforementioned fiber optic partitioning alarm information to obtain a port anomaly information set. Then, this port anomaly information set is input into a graph database to obtain the port anomaly communication topology graph.

[0064] The second step involves performing multidimensional root cause matching on the aforementioned port identifier partitioning information set to obtain an initial multidimensional root cause information set. This initial multidimensional root cause information can be derived from root cause analysis across three dimensions: offline device identification and root cause analysis, communication link connectivity tracing and root cause analysis, and Fabric-level dependency correlation analysis, identifying the root causes of the invalid Zone partition state. In practice, the executing entity can use a Zone root cause analysis rule engine managing different securities businesses (e.g., proprietary trading, brokerage, credit reporting) to perform multidimensional root cause matching on the aforementioned port identifier partitioning information set to obtain the initial multidimensional root cause information set. This Zone root cause analysis rule engine can be a rule engine formed by inputting root cause analysis rules determined by securities experts based on their experience into the ARMS (Application Real-Time Monitoring Service) platform.

[0065] The third step involves performing anomaly propagation root cause reasoning on the port anomaly communication topology graph based on the initial multidimensional root cause information set and the historical partition state information set, to obtain the partition root cause information set. The partition root cause information in this set can be obtained by modifying and expanding the initial multidimensional root cause information set. In practice, the executing entity can first perform anomaly co-occurrence frequency statistics between nodes on the historical partition state information set to obtain the edge weights of the port anomaly communication topology graph, resulting in a weighted port anomaly communication topology graph. Then, using a second-order random walk algorithm, anomaly propagation root cause reasoning is performed on the weighted port anomaly communication topology graph to obtain the walk root cause information set. Finally, the initial multidimensional root cause information set and the walk root cause information set are fused and deduplicated to obtain the partition root cause information set.

[0066] The fourth step involves sorting and filtering the aforementioned partition root cause information set to obtain the alarm root cause information set. This alarm root cause information set can be the top three partition root cause information most likely to cause Zone anomaly alarms, selected from the sorted set. In practice, the executing entity can first determine the root cause weight of each partition root cause information in the aforementioned set, obtaining a root cause weight set. This root cause weight can be a weighted sum of the confidence level of the rule engine matching in the multi-dimensional root cause matching process, the random walk association probability in the anomaly propagation root cause inference, and the historical anomaly occurrence frequency. The weights in this weighted sum can be pre-set values, such as 0.3, 0.3, and 0.4. Then, the partition root cause information set is sorted from largest to smallest using the root cause weight set to obtain a partition root cause information sequence. Finally, the partition root cause information at the first position in the sequence is selected to obtain the alarm root cause information.

[0067] In addressing the aforementioned technical challenges in implementing technical solutions, the following technical issues arise in the application scenario: root cause analysis of device alarms in a securities company's Fibre Channel storage area network (FSA). These issues stem from the fact that root cause analysis of alarm information in a FSA scenario involves numerous multi-level root cause analysis rules with diverse data formats. This necessitates a full match between the port identifier partitioning information set and every rule in the rule engine, resulting in low matching efficiency and accuracy, prolonged matching time, and failing to meet the securities company's requirement for minute-level root cause analysis. This also reduces the security and stability of various devices in the FSA scenario, increasing the device failure rate. Considering the following requirements for this application scenario: adaptability to high-complexity configuration rules and large data volumes, adaptability to high-precision rule matching, adaptability to collaborative matching across multiple networks, adaptability to fuzzy dynamic matching, adaptability to triplet structured processing, and adaptability to low-latency, high-concurrency scenarios in the securities industry, we have decided to adopt the following solution: Optionally, the above-mentioned method of locating the root cause of alarms by analyzing the acquired historical partition status information set and the port identifier partition information set based on the fiber optic partition alarm information, and adjusting the device configuration of each device included in the fiber optic switching network topology based on the alarm root cause information, may include the following steps: The first step involves structuring the aforementioned port identifier partitioning information set and the root cause localization rule information set included in the port multidimensional root cause localization rule engine to obtain a device status triplet set and a root cause localization triplet set. The port multidimensional root cause localization rule engine can be a rule engine formed by inputting root cause analysis rules determined by the user based on their own experience into the ARMS (Application Real-Time Monitoring Service) platform. The aforementioned root cause localization rule information set can be root cause analysis rule information determined by the user based on their own experience. The device status triplets in the aforementioned device status triplet set can be represented as triples of the port identifier partitioning information set in the form of device port identifier information, association relationships, and device port identifier information. The root cause localization triplets in the aforementioned root cause localization triplet set can be triples representing configuration rule information in the form of root cause localization rule antecedents, antecedent-precedence association relationships, and root cause localization rule consequents, based on the root cause localization rule information set.

[0068] The second step involves generating a matching condition sharing model based on the aforementioned root cause localization triplet set. This model can be a mathematical model used to quantify the sharing degree of each root cause localization triplet located in the antecedent within the root cause localization rule information set, and to guide the sorting of the root cause localization triplet set. By sorting the Alpha nodes (single input nodes) and placing those with higher sharing degrees at higher levels, the matching condition sharing model reduces redundant computation. In practice, the executing entity can calculate the antecedent triplet sharing degree by calculating the ratio of the number of times each root cause localization triplet located in the antecedent within the aforementioned root cause localization rule information set appears to the number of root cause localization rule information items included in the root cause localization rule information set. Then, using the obtained antecedent triplet sharing degrees, the aforementioned root cause localization triplet set is sorted to obtain a root cause localization triplet sequence, which serves as the matching condition sharing model.

[0069] The third step involves constructing a first-port root cause matching network based on the aforementioned matching condition sharing model. This first-port root cause matching network can be an Alpha network where the root cause localization triplet with the highest sharing degree in the antecedent triplet set is used as the top-level node, and the triplet with the second-highest sharing degree in the antecedent triplet set is used as the lower-level node. This hierarchical storage of the antecedent root cause localization triplets reduces redundant matching operations. Each node in the first-port root cause matching network stores its corresponding root cause localization triplet and initializes Alpha memory to cache successfully matched root cause localization triplet instances. In practice, the execution entity utilizes the Alpha network construction method in the Rete algorithm to construct the first-port root cause matching network based on the aforementioned matching condition sharing model.

[0070] The fourth step is to determine the root cause matching fitness function for the root cause matching network of the first port mentioned above. The root cause matching fitness function can be a multi-objective fitness function that balances rule matching efficiency (rule matching time) and rule matching accuracy (the proportion of effective matching rules), or a fitness function obtained by weighted fusion of multi-objective fitness functions.

[0071] Fifth, based on the aforementioned root cause matching fitness function, perform a network heuristic update on the first port root cause matching network to obtain the port root cause update matching network. This port root cause update matching network can be an optimized update of the node sequence of the first port root cause matching network. This network heuristic update can compensate for the shortcomings of insufficient search accuracy and susceptibility to local optima in sorting by the occurrence frequency of root cause location triples in the matching condition sharing model, and can search for the Alpha order that achieves the highest rule matching efficiency. In practice, the execution entity can use a genetic algorithm to perform a network heuristic update on the first port root cause matching network based on the aforementioned root cause matching fitness function to obtain the port root cause update matching network. The initialization parameters of the genetic algorithm can include: a code length of 20, a population size of 130, a crossover probability of 75%, a mutation probability of 6%, using the root cause location triple sequence sorted by the matching condition sharing model as the initial population individuals, and the root cause matching fitness function as the fitness function. The aforementioned port root cause update matching network can effectively solve the problem of the first port root cause matching network easily getting trapped in local optima. Therefore, the root cause matching fitness function simultaneously considers time consumption, matching accuracy, and weighted fusion, and updates the network through heuristic updates. This enables automatic strategy adjustment (e.g., prioritizing low latency and high accuracy during the opening period, and allowing for slower but more comprehensive root cause analysis during the clearing period) at different times in a securities company (e.g., opening, closing, and clearing) to automatically optimize the network structure and quantify the impact of different sorting orders.

[0072] Step 6: Based on the aforementioned port root cause update matching network and the aforementioned root cause localization rule information set, a second port root cause matching network is generated. This second port root cause matching network can be a Beta network used to process and correlate multiple facts output by the aforementioned port root cause update matching network to determine whether the conditions for complete root cause localization rule information are met. In practice, the executing entity can utilize the Beta network construction method in the Rete algorithm to generate the second port root cause matching network based on the aforementioned port root cause update matching network and the aforementioned root cause localization rule information set.

[0073] Step 7: Construct node indexes for the aforementioned port root cause update matching network and the aforementioned second port root cause matching network to obtain a matching node index information set and a root cause matching cost model. The matching node index information in the aforementioned matching node index information set can be a structured index relationship established on single-input nodes and Beta nodes (i.e., dual-input nodes). This index information forms a fast location link between nodes by binding keyword identifiers to nodes, i.e., a fast retrieval directory for nodes. The aforementioned keyword identifier can be an identifier combining the matching port identifier information and the association relationship of the root cause location triple. The aforementioned link can be formed by connecting similar nodes according to the keyword identifier, creating a mapping relationship between index keyword identifiers and node sets, while recording the parent-child association relationships between nodes to form a complete index link. The aforementioned root cause matching cost model can be an evaluation function used to quantify the resource consumption and time cost of performing matching operations through nodes, thereby quantifying the node matching cost. The aforementioned root cause matching cost model can quantify the time and resource consumption of node matching, adjust the order and optimize the index for nodes with high cost and low pass rate, and the construction of the node index can form a fast location link. In practice, the aforementioned execution entity can first determine, through the matching node index information set, the sum of the matching costs and node matching consumption costs of the left and right nodes of each node included in the aforementioned port root cause update matching network and the aforementioned second port root cause matching network, as the first configured matching cost function. Here, the node matching consumption cost can characterize the time and resource consumption cost of node matching. The matching costs of the left and right nodes can be obtained through recursive calculation. For example, if the left or right node is a leaf node, the matching cost is a preset basic cost representing the node's own overhead. The preset basic cost can be a pre-set cost, which can be determined according to the specific situation based on the weights and is not limited here. If the left or right node is a non-leaf node, the matching cost is the sum of the matching costs of all its corresponding child nodes. Secondly, the sum of the product of the single-input node memory consumption cost of the left node and the double-input node memory consumption cost of the right node, and the product of the single-input node memory consumption cost of the right node and the double-input node memory consumption cost of the left node, is determined as the node matching consumption cost. The memory consumption costs for single-input nodes and dual-input nodes mentioned above can be obtained by collecting real-time node memory usage data. Next, the product of the dual-input node memory consumption cost for the left and right nodes and the node matching success rate is determined as the second configuration matching cost function. Then, the product of the node matching cost and the node matching success rate is determined as the target single-input node memory consumption cost function. The node matching success rate can be obtained through historical node statistics, representing the ratio of the number of successfully matched node instances to the total number of incoming node instances.Finally, the first configuration matching cost function, the node matching cost, the second configuration matching cost function, and the target single-input node memory consumption cost function are determined as the configuration matching cost model.

[0074] Step 8: Based on the aforementioned historical partition state information set, the root cause localization triplet set is fuzzy-processed to generate a fuzzy root cause localization triplet set and a fuzzy matching threshold. The fuzzy root cause localization triplets in the fuzzy root cause localization triplet set can characterize the importance of the root cause localization triplets. The fuzzy matching threshold can be a critical value used to determine whether a match is successful. In practice, the executing entity uses a fuzzy C-means clustering algorithm to generate the fuzzy root cause localization triplet set based on the aforementioned historical partition state information set. Then, the data missing rate of the aforementioned root cause localization rule information set is evaluated to obtain the rule data missing values. Finally, the sum of the products of the preset matching threshold, the difference between 1 and the rule data missing values, and the weight set corresponding to the root cause localization triplet set is determined as the fuzzy matching threshold. The preset matching threshold can be a pre-set matching value, and its value can be determined according to specific circumstances, and is not limited here.

[0075] Step 9: Based on the aforementioned root cause matching cost model, the aforementioned fuzzy root cause location triplet set, and the aforementioned fuzzy matching threshold, root cause matching processing is performed on the aforementioned device status triplet set to obtain alarm root cause information. Based on the aforementioned alarm root cause information, device configuration adjustments are made for each device included in the aforementioned fiber optic switching network topology. In practice, the aforementioned execution entity can first input the aforementioned fuzzy root cause location triplet set to the single-input node corresponding to the first port root cause matching network for single-input node matching, and perform priority cost matching through the root cause matching cost model during the matching process to obtain a matching weight set. Secondly, the aforementioned matching weight set is input to the second port root cause matching network to perform multi-mode joint matching according to combinational logic to obtain a node cumulative weight set. Then, in response to determining that there is a node set in the node cumulative weight set that is greater than or equal to the fuzzy matching threshold, the root cause location triplet set corresponding to the node set located in the subsequent event is determined as the initial alarm root cause information set, and the sum of the weights corresponding to the node cumulative weight set and the root cause location triplet set located in the subsequent event is determined as the sorting weight value set. Next, the initial alarm root cause information set is sorted from largest to smallest according to the sorting weight value set, and the initial alarm root cause information located at the initial position is extracted as the alarm root cause information. Finally, based on the above alarm root cause information, the device configuration of each device included in the above fiber optic switching network topology is adjusted.

[0076] The above-described technical solution and its related content, as an inventive point of this disclosure, solve the technical problem of "low matching efficiency and accuracy, prolonged matching time, reduced security and stability of various devices, and increased device failure rate." The factors leading to low matching efficiency and accuracy, prolonged matching time, reduced security and stability of various devices, and increased device failure rate are often as follows: Because the root cause analysis of alarm information in a securities company's Fibre Channel storage area network scenario involves a large number of multi-level root cause analysis rules with diverse data formats, the port identifier partitioning information set needs to be fully matched with each rule in the rule engine. This results in low matching efficiency and accuracy, prolonged matching time, which does not meet the securities company's requirement for minute-level root cause analysis, reduces the security and stability of various devices in the Fibre Channel storage area network scenario, and increases the device failure rate. Solving these factors can improve matching efficiency and accuracy, shorten matching time, improve the security and stability of various devices, and reduce the device failure rate. To achieve this effect, this disclosure firstly structures the port identifier partitioning information set to eliminate data heterogeneity. Secondly, it performs ternary structuring on the root cause localization rule information set to achieve atomic splitting, providing foundational data for subsequent network-based matching and adapting to port and zone attribution issues in securities scenarios. Furthermore, the Fibre Channel storage area itself is suitable for triple representation, effectively distinguishing different securities businesses and avoiding the risk of information isolation through firewalls. Thirdly, a first port root cause matching network is constructed using the generated matching condition sharing degree model. This model quantifies the degree of condition sharing and ranks conditions accordingly, reducing invalid and repetitive single-condition matching operations. Furthermore, the first-port root cause matching network is heuristically updated using the generated root cause matching fitness function, and a second-port root cause matching network is generated. The root cause matching fitness function achieves multi-objective evaluation by balancing matching efficiency and matching accuracy, improving the comprehensiveness of subsequent matching. The heuristic update can effectively solve the local optimum problem of static networks through global search capabilities. The node layout of the first-port root cause matching network is more suitable for enterprise-level Fibre Channel storage area network scenarios, improving the quality of the port root cause update matching network. The port root cause update matching network can cover the situation where multiple antecedents are satisfied simultaneously, achieving complete rule matching. Moreover, receiving the output of the efficient port root cause update matching network can avoid processing a large number of invalid matching results, further improving the joint matching efficiency.Next, a node index and a root cause matching cost model are constructed. The node index creates a fast location link between nodes, avoiding a full network traversal and significantly improving node retrieval efficiency. The matching cost model is configured through multi-dimensional matching evaluation, quantifying the resource consumption and time cost of each node's matching operation, avoiding entry into cost nodes to shorten overall matching time. The combined use of the matching condition sharing model, the root cause matching cost model, and the node index allows for faster matching of relevant rules during massive alarms or port status changes, meeting the securities industry's requirement for 5-minute root cause localization and providing better compression and focusing capabilities for massive alarms during high-concurrency periods in the securities industry. Subsequently, fuzzy root cause localization triples and fuzzy matching thresholds are generated. Fuzzy C-means clustering guides subsequent matching to focus on core rules, weakening the influence of secondary rules. Replacing hard matching with weighted soft matching effectively avoids matching failures caused by data missing rates in the port identifier partitioning information set. Finally, the matching and sorting process obtains alarm root cause information and adjusts the device configuration of each device included in the fiber optic switching network topology. This can improve matching efficiency and accuracy, shorten matching time, improve the security and stability of each device, and reduce the device damage rate.

[0077] Step 108: Based on the alarm root cause information, adjust the device configuration of each device included in the fiber optic switching network topology diagram.

[0078] In some embodiments, the aforementioned execution entity can adjust the device configuration of each device included in the aforementioned fiber optic switching network topology based on the aforementioned alarm root cause information. Specifically, when the alarm root cause information is a physical link anomaly, optical module failure, or port anomaly, the device configuration adjustment may be path switching or logical port reset. When the alarm root cause information is a port identification information mismatch, missing configuration, or drift, the configuration of the partition device port identification information set and the switch peer port identification information set may be rolled back, or the port identification information and Zone may be decoupled and reassembled. When the alarm root cause information is an inconsistency in cross-Fibre Channel switch configurations, the aforementioned device configuration adjustment may be to forcibly synchronize the latest Zone configuration database to all Fibre Channel switches to eliminate the problem of inconsistent Fibre Channel switch version numbers.

[0079] The above embodiments of this disclosure have the following beneficial effects: The device configuration adjustment method based on Fibre Channel partition status information in some embodiments of this disclosure can improve the accuracy of Zone-level alarms for different securities business partitions, realize real-time monitoring of the communication effectiveness of Fibre Channel partitions, improve the accuracy and efficiency of root cause localization, improve the accuracy of adjustment, and improve the security and stability of the device. Specifically, the reasons for the inability to provide early warnings, the increase in device damage rate, and the reduction in device security are as follows: Since only port online status detection is performed without considering the correctness of Zone configuration, it is impossible to provide early warnings of business interruption risks, which does not meet the requirements of securities companies for fault operation and maintenance, resulting in a large number of securities transactions being unable to be carried out, causing serious cost losses. Furthermore, port status detection needs to be performed manually, resulting in low detection efficiency and a high detection error rate. At the same time, the generation of alarm information for the device lacks Zone-level status aggregation judgment, making it difficult to effectively utilize the topology structure and quickly locate high-risk Zones, increasing the device damage rate and reducing device security. Based on this, the device configuration adjustment method based on Fibre Channel partition status information in some embodiments of this disclosure can first, in response to the detection of successful login to the Fibre Channel switching network topology map including each Fibre Channel switch, obtain user partition input information and user peer port input information. Here, user partition input information and user peer port input information are used to generate different types of query information, namely CLI (Command-line Interface) query statements, to obtain device identification information of each device included in the fiber optic switching network topology. Secondly, based on the aforementioned user partition input information and user peer port input information, partition port query information and peer port query information are generated. This improves the accuracy of the generated query information regarding Zone configuration and current port status, reduces user learning difficulty, and enhances user experience. Thirdly, based on the aforementioned partition port query information and peer port query information, a set of partition device port identification information and a set of switch peer port identification information are obtained. Here, the CLI query statement can simultaneously obtain the partition terminal identification information representing the correctness of the Zone configuration and the set of switch peer port identification information representing the online status of the device ports, facilitating early detection of offline devices for early warning, reducing the risk of service interruption, and improving detection efficiency and accuracy. Finally, the aforementioned set of partition device port identification information and the aforementioned set of switch peer port identification information are processed to classify device status, resulting in a port identification classification information set. Here, the device status segmentation process can accurately classify whether each device is online or offline, and subsequently confirm the status at the partition area level. Then, based on the aforementioned port identifier segmentation information set, the fiber optic partition status information of the Fibre Channel partition corresponding to the aforementioned partitioned device port identifier information set is determined.Here, classifying information sets by port identifiers improves the determination of device validity at the Zone level, facilitating subsequent area-level alarms. Next, based on the aforementioned fiber optic zone status information, fiber optic zone alarm information is generated. Generating area-level alarm information improves the accuracy and conciseness of alarm data, facilitating overall root cause analysis and improving its efficiency. Then, based on the fiber optic zone alarm information, alarm root cause analysis is performed on the acquired historical zone status information set and the aforementioned port identifier classification information set to obtain the alarm root cause information. Here, area-level alarm root cause analysis effectively utilizes the topology to quickly locate high-risk Zones, improving the efficiency and accuracy of root cause analysis, enhancing device security and stability, and reducing device failure rates. Finally, based on the aforementioned alarm root cause information, device configuration adjustments are made to each device included in the aforementioned fiber optic switching network topology. This improves the accuracy and efficiency of device configuration adjustments, reduces the time of device failures, and enhances the stability of the Fibre Channel storage area network corresponding to the fiber optic switching network topology. Therefore, this device configuration adjustment method based on Fibre Channel partition status information can improve the accuracy of Zone-level alarms in different securities business partitions, realize real-time monitoring of the communication effectiveness of Fibre Channel partitions, improve the accuracy and efficiency of root cause location, improve the accuracy of adjustment, and improve the security and stability of the equipment.

[0080] Further reference Figure 2 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a device configuration adjustment apparatus based on Fibre Channel partition status information. These apparatus embodiments are similar to... Figure 1 Corresponding to the method embodiments shown, this device configuration adjustment device based on Fibre Channel partition status information can be specifically applied to various electronic devices.

[0081] like Figure 2As shown, a device configuration adjustment device 200 based on Fibre Channel partition status information includes: a first acquisition unit 201, a first generation unit 202, a second acquisition unit 203, a device status division unit 204, a determination unit 205, a second generation unit 206, an alarm root cause location unit 207, and a device configuration adjustment unit 208. The first acquisition unit 201 is configured to: acquire user partition input information and user peer port input information in response to detecting successful login to each Fibre Channel switch included in the Fibre Channel network topology map. The first generation unit 202 is configured to: generate partition port query information and peer port query information based on the aforementioned user partition input information and user peer port input information. The second acquisition unit 203 is configured to: acquire a partition device port identifier information set and a switch peer port identifier information set based on the aforementioned partition port query information and peer port query information. The device status division unit 204 is configured to: perform device status division processing on the aforementioned partition device port identifier information set and the aforementioned switch peer port identifier information set to obtain a port identifier division information set. The determining unit 205 is configured to: determine the fiber optic partition status information of the fiber channel partition corresponding to the aforementioned port identifier partitioning information set. The second generating unit 206 is configured to: generate fiber optic partition alarm information based on the aforementioned fiber optic partition status information. The alarm root cause location unit 207 is configured to: locate the alarm root cause by analyzing the acquired historical partition status information set and the aforementioned port identifier partitioning information set based on the fiber optic partition alarm information, thereby obtaining alarm root cause information. The device configuration adjustment unit 208 is configured to: adjust the device configuration of each device included in the aforementioned fiber optic switching network topology based on the aforementioned alarm root cause information.

[0082] It is understandable that the units described in the device configuration adjustment device 200 based on Fibre Channel partition status information are related to the reference. Figure 1 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to the device configuration adjustment device 200 and its constituent units based on Fibre Channel partition status information, and will not be repeated here.

[0083] The following is for reference. Figure 3 It shows a schematic diagram of the structure of an electronic device (e.g., an electronic device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0084] like Figure 3As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0085] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.

[0086] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from storage device 308, or installed from ROM 302. When the computer program is executed by processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.

[0087] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0088] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0089] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: in response to detecting successful login to the various Fibre Channel switches included in the fiber optic switching network topology, acquire user partition input information and user peer port input information; generate partition port query information and peer port query information based on the aforementioned user partition input information and user peer port input information; acquire a partition device port identifier information set and a switch peer port identifier information set based on the aforementioned partition port query information and peer port query information; perform device status classification processing on the aforementioned partition device port identifier information set and the aforementioned switch peer port identifier information set to obtain a port identifier classification information set; determine the fiber optic partition status information of the Fibre Channel partition corresponding to the aforementioned partition device port identifier information set based on the aforementioned port identifier classification information set; generate fiber optic partition alarm information based on the aforementioned fiber optic partition status information; perform alarm root cause location on the acquired historical partition status information set and the aforementioned port identifier classification information set based on the fiber optic partition alarm information to obtain alarm root cause information; and adjust the device configuration of each device included in the aforementioned fiber optic switching network topology based on the aforementioned alarm root cause information.

[0090] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0091] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0092] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including a first acquisition unit, a first generation unit, a second acquisition unit, a device state division unit, a determination unit, a second generation unit, an alarm root cause location unit, and a device configuration adjustment unit. The names of these units do not necessarily limit the specific unit; for example, the first acquisition unit may also be described as "a unit that acquires user partition input information and user peer port input information in response to detecting successful login to the fiber optic switching network topology map including each Fibre Channel switch".

[0093] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0094] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for adjusting device configuration based on Fibre Channel partition status information, comprising: In response to the detection of successful login to the various Fibre Channel switches included in the Fibre Channel network topology, user partition input information and user peer port input information are obtained; Based on the user partition input information and the user peer port input information, generate partition port query information and peer port query information; Based on the partition port query information and the peer port query information, obtain the partition device port identifier information set and the switch peer port identifier information set; The port identifier information set of the partitioned device and the port identifier information set of the switch peer end are processed by device status division to obtain the port identifier division information set; Based on the port identifier partitioning information set, determine the fiber optic partitioning status information of the fiber channel partition corresponding to the partitioning device port identifier information set; Based on the fiber optic partition status information, generate fiber optic partition alarm information; Based on the fiber optic partition alarm information, alarm root cause location is performed on the acquired historical partition status information set and the port identifier partition information set to obtain alarm root cause information; Based on the alarm root cause information, the device configuration of each device included in the fiber optic switching network topology is adjusted.

2. The method of claim 1, wherein, The step of obtaining the partition device port identification information set and the switch peer port identification information set of each Fibre Channel switch based on the partition port query information and the peer port query information includes: Execute the partition port query information to obtain the partition query result information; Data extraction is performed on the partition query results to obtain a set of partition device port identifier information; Execute the peer port query information to obtain the peer port query result information; The target fields are extracted from the query results of the peer port to obtain the peer port identification information set of the switch.

3. The method of claim 1, wherein, The process of performing device status partitioning on the partitioned device port identifier information set and the switch peer port identifier information set to obtain a port identifier partitioning information set includes: The port identification information set of the partition device and the port identification information set of the switch peer are converted to uppercase and lowercase respectively to obtain the converted port identification information set of the partition device and the converted port identification information set of the switch peer. The difference between the converted partition device port identification information set and the converted switch peer port identification information set is determined as the offline device identification information set; The intersection of the converted partition device port identification information set and the converted switch peer port identification information set is determined as the online device identification information set; Fields are extracted from the partition port query information and the peer port query information corresponding to the partition query result information and the peer port query result information to obtain the first device type information and the second device type information; Device identifiers with device type of first device type information and second device type information are filtered from the offline device identifier information set and the online device identifier information set, respectively, to obtain the first online device identifier information set, the second online device identifier information set, the first offline device identifier information set, and the second offline device identifier information set; The first online device identification information set, the second online device identification information set, the first offline device identification information set, and the second offline device identification information set are determined as the port identification partitioning information set.

4. The method of claim 1, wherein, The step of determining the fiber optic partition status information of the fiber channel partition corresponding to the port identifier information set of the partitioning device based on the port identifier partition information set includes: Determine the device identifier weight of each online device identifier in the online device identifier information set corresponding to the partitioned device port identifier information set and the port identifier partitioning information set, respectively, to obtain the device identifier weight set; The cumulative sum of the device identifier weight sets corresponding to the partition device port identifier information set is determined to obtain the partition weight cumulative sum, and the cumulative sum of the device identifier weight sets corresponding to the online device identifier information set is determined to obtain the online weight cumulative sum. The product of the ratio of the online weight summation to the partition weight summation and a preset value is determined as the partition status value of the fiber channel partition. Determine the device redundancy penalty item and device stability penalty item of the offline device identification information set corresponding to the port identification partitioning information set; The difference between the partition status value and the device redundancy penalty item and the device stability penalty item is determined to obtain the partition target status value; The target state values ​​of the partition are divided into states to obtain fiber optic partition state information.

5. The method of claim 4, wherein, The method further includes: In response to determining that the first online device identifier information set included in the port identifier partitioning information set is an empty set, the partition invalid status information is determined as the fiber optic partition status information of the fiber channel partition; In response to determining that the second online device identification information set included in the port identification partitioning information set is an empty set, the partition invalid status information is determined as the fiber optic partition status information of the fiber channel partition.

6. The method of claim 1, wherein, The step of performing alarm root cause location on the acquired historical partition status information set and the port identifier partition information set based on the fiber optic partition alarm information to obtain alarm root cause information includes: In response to the alarm information that indicates the invalid state of the fiber optic partition alarm information, the information set is divided according to the port identifier, and an abnormal communication topology map of the port is generated. The port identifier partitioning information set is subjected to multidimensional root cause matching processing to obtain an initial multidimensional root cause information set; Based on the initial multidimensional root cause information set and the historical partition status information set, abnormal propagation root cause inference is performed on the port abnormal communication topology to obtain the partition root cause information set. The root cause information set of the partition is sorted and filtered to obtain alarm root cause information.

7. A device configuration adjustment apparatus based on Fibre Channel partition status information, comprising: The first acquisition unit is configured to acquire user partition input information and user peer port input information in response to detecting successful login to each Fibre Channel switch included in the Fibre Channel network topology map; The first generation unit is configured to generate partition port query information and peer port query information based on the user partition input information and the user peer port input information. The second acquisition unit is configured to acquire a set of partition device port identifier information and a set of switch peer port identifier information based on the partition port query information and the peer port query information. The device status division unit is configured to perform device status division processing on the partitioned device port identification information set and the switch peer port identification information set to obtain a port identification division information set. The determining unit is configured to determine the fiber optic partition status information of the fiber channel partition corresponding to the partition device port identifier information set based on the port identifier partition information set. The second generation unit is configured to generate fiber optic partition alarm information based on the fiber optic partition status information. The alarm root cause localization unit is configured to perform alarm root cause localization on the acquired historical partition status information set and the port identifier partition information set based on the fiber optic partition alarm information, and obtain alarm root cause information. The device configuration adjustment unit is configured to adjust the device configuration of each device included in the fiber optic switching network topology based on the alarm root cause information.

8. An electronic device, comprising: One or more processors; Storage device, on which one or more programs are stored, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-6.

9. A computer readable medium having stored thereon a computer program, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-6.

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