Concurrent data processing method, rail train integrated monitoring system and storage medium

Abstract

The application discloses a concurrent data processing method, an integrated monitoring system of a rail train and a storage medium, and the concurrent data processing method comprises the following steps: acquiring messages in a message queue, wherein the content of the messages comprises point state values of detection points; screening the messages in the message queue to screen out effective messages; determining target effective messages in the effective messages which will trigger actions of linkage devices; and distributing the target effective messages which will trigger the actions of the linkage devices to corresponding target linkage devices. The concurrent data processing method can process high-concurrent messages at high speed and reliably, can quickly process a large number of messages and ensure the real-time performance of the messages.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a concurrent data processing method, a comprehensive monitoring system for rail trains, and a storage medium. Background Technology

[0002] The Industrial Internet of Things (IIoT) technology is developing rapidly, and existing IoT platforms, scheduling systems, and monitoring systems are already quite comprehensive. In particular, the interaction between systems and devices is becoming increasingly complex, and the number of devices monitored by systems is growing. With limited server resources, it is impossible to process large volumes of messages instantaneously while maintaining strong real-time performance. Therefore, a faster and more reliable high-concurrency message processing solution is urgently needed. Summary of the Invention

[0003] The present invention aims to at least solve one of the technical problems existing in the prior art. To this end, the first objective of the present invention is to propose a concurrent data processing method that can process high-concurrency messages quickly and reliably, and can process a large number of messages rapidly while ensuring message real-time performance.

[0004] The second objective of this invention is to propose a comprehensive monitoring system for rail trains.

[0005] A third objective of this invention is to provide a computer-readable storage medium.

[0006] To achieve the above objectives, the concurrent data processing method proposed in the first aspect of the present invention includes: acquiring messages in a message queue, the content of which includes the status value of a detection point; filtering the messages in the message queue to select valid messages; determining a target valid message among the valid messages that will trigger the action of a linkage device; and distributing the target valid message that will trigger the action of the linkage device to the corresponding target linkage device.

[0007] According to the concurrent data processing method proposed in this embodiment of the invention, during the message filtering process in the message queue, invalid messages can be quickly filtered out, and valid messages can be quickly and accurately selected. This improves message consumption speed, avoids message queue congestion, and ensures strong real-time performance of messages. Furthermore, by setting a filtering mechanism, after determining that a valid message will trigger an action on a linked device, the valid message that will trigger the device action can be quickly distributed to the corresponding linked device, avoiding a large backlog in the message queue, ensuring message real-time performance, and avoiding the consumption of excessive server resources.

[0008] In some embodiments of the present invention, filtering messages in the message queue to select valid messages includes: obtaining a list of linkage rules for all detection points; if a message in the message queue satisfies a linkage rule in the list of linkage rules, then the message is determined to be a valid message.

[0009] In some embodiments of the present invention, determining the target valid message that will trigger the action of the linkage device in the valid message includes: obtaining the linkage rules satisfied by the messages in the message queue as pre-selected linkage rules; obtaining the real-time point status values ​​of all detection points; and obtaining the target valid message according to the pre-selected linkage rules and the real-time point status values ​​of all detection points.

[0010] In some embodiments of the present invention, obtaining the target valid message according to the pre-selected linkage rules and the real-time position status values ​​of all detection points includes: logically combining the real-time position status values ​​of all detection points according to the pre-selected linkage rules; obtaining the logical combination result of the position status values ​​of all detection points; if the logical combination result satisfies the linkage triggering condition corresponding to the pre-selected linkage rules, then the valid message corresponding to the real-time position status value whose logical result satisfies the linkage triggering condition is the target valid message.

[0011] In some embodiments, obtaining the real-time status values ​​of all detection points includes: reading the real-time status values ​​of all detection points from the Redis database.

[0012] In some embodiments, after filtering out the valid messages, the concurrent data processing method further includes saving the valid messages to a thread queue.

[0013] In some embodiments, distributing the target valid message that will trigger the action of the linked device to the corresponding target linked device includes: distributing the target valid message to the target linked device in the form of a message queue.

[0014] In some embodiments of the present invention, the concurrent data processing method further includes: acquiring feedback data of the target linkage device on the target's effective information; and storing the feedback data in an underlying database.

[0015] In some embodiments, obtaining a list of linkage rules for all detection points includes: reading the list of linkage rules for all detection points from a local cache.

[0016] In some embodiments of the present invention, the concurrent data processing method further includes: detecting changes in the linkage rules through a distributed key-value storage monitoring mechanism; and updating the list of linkage rules stored in the local cache according to the changed linkage rules.

[0017] In some embodiments of the present invention, the underlying database includes a MongoDB database, and the message queue is a Kafka message queue.

[0018] To achieve the above objectives, a second aspect of the present invention provides a comprehensive monitoring system for rail trains, comprising: a processor; a memory communicatively connected to the processor; the memory storing a computer program executable by the processor, wherein the computer program, when executed by the processor, implements the concurrent data processing method described above.

[0019] According to the integrated monitoring system for rail trains proposed in the embodiments of the present invention, when the processor executes the computer program stored in the memory, it can greatly improve the message consumption speed, avoid message queue congestion, and ensure the strong real-time performance of messages by executing the concurrent data processing method of the above embodiments. Furthermore, the synchronous caching scheme adopted in the embodiments of the present invention can save a lot of time and performance and ensure the real-time performance of the cache.

[0020] In some embodiments of the present invention, the processor is configured with a local cache, a high-availability database, and a low-level database, wherein the local cache is used to store a list of linkage rules for all detection points; the high-availability database is used to store the real-time point status values ​​of all detection points; and the low-level database is used to store feedback data from the target linkage device for effective information about the target.

[0021] To achieve the above objectives, a third aspect of the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer-readable storage medium, when executed by a processor, implements the concurrent data processing method described in any of the preceding claims.

[0022] According to the computer-readable storage medium proposed in the embodiments of the present invention, when the stored computer program is executed by a processor, it can implement the concurrent data processing method described above, which can greatly improve the message consumption speed, avoid message queue congestion, and ensure the strong real-time performance of messages. Furthermore, the synchronous caching scheme adopted in the embodiments of the present invention can save a lot of time and performance and ensure the real-time performance of the cache.

[0023] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0024] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0025] Figure 1 A flowchart of a concurrent data processing method according to an embodiment of the present invention;

[0026] Figure 2 A flowchart of a concurrent data processing method according to another embodiment of the present invention;

[0027] Figure 3 This is a schematic diagram of a three-layer screening mechanism according to an embodiment of the present invention;

[0028] Figure 4 This is a flowchart of a concurrent data processing method according to yet another embodiment of the present invention;

[0029] Figure 5 This is a flowchart of a concurrent data processing method according to yet another embodiment of the present invention;

[0030] Figure 6 This is a schematic diagram of a concurrent data processing method according to an embodiment of the present invention;

[0031] Figure 7 This is a schematic diagram of concurrent data processing according to an embodiment of the present invention;

[0032] Figure 8 This is a block diagram of a comprehensive monitoring system for rail trains according to an embodiment of the present invention;

[0033] Figure 9 This is a block diagram of a comprehensive monitoring system for rail trains according to another embodiment of the present invention;

[0034] Figure 10 This is a schematic diagram of a three-level data storage structure according to an embodiment of the present invention.

[0035] Figure label:

[0036] Rail Transit Integrated Monitoring System 10;

[0037] Processor 1, Memory 2;

[0038] Local cache 11, high availability database 12, underlying database 13. Detailed Implementation

[0039] The embodiments of the present invention are described in detail below. The embodiments described with reference to the accompanying drawings are exemplary. The embodiments of the present invention are described in detail below.

[0040] The content of current IoT platforms and various scheduling and monitoring systems is becoming increasingly rich, the interaction between systems and devices is becoming more complex, and the number of devices monitored by the systems is increasing. For example, taking a subway real-time monitoring system as an example, suppose the system of a hub station needs to connect to 50,000 to 100,000 device detection points. This means that at the moment the system starts, there will be as many as 100,000 concurrent messages. After processing these messages at high speed, subsequent logical processing of the system's interconnected devices is required, and finally the system receives feedback messages from each device. Throughout the entire system's interconnection process, it is necessary to ensure strong real-time message transmission and prevent messages in the queue from waiting for too long.

[0041] Existing high-concurrency message solutions typically optimize data storage and message processing mechanisms to improve message processing speed and performance. However, for a large volume of instantaneous high-concurrency messages, processing speed cannot be guaranteed, and real-time performance and reliability need improvement. To address this, this invention proposes a concurrent data processing method, a comprehensive rail train monitoring system, and a storage medium that can improve the speed and effectiveness of concurrent data processing, save time and performance, and ensure the real-time performance of caching. (See below for reference.) Figures 1-7 A concurrent data processing method according to an embodiment of the present invention is described.

[0042] In some embodiments of the present invention, such as Figure 1 The diagram shown is a flowchart of a concurrent data processing method according to an embodiment of the present invention, wherein the concurrent data processing method includes at least steps S1-S4, as detailed below.

[0043] Specifically, it can be combined with Figure 1 and Figure 2 Understanding the concurrent data processing method of this invention's embodiments, Figure 2 This is a schematic diagram of a concurrent data processing method according to an embodiment of the present invention.

[0044] S1, retrieve the message from the message queue. The message content includes the point status value of the detection point.

[0045] Specifically, in a real-time monitoring system for rail transit such as a subway, the status values ​​of the detected points are converted into corresponding message entities and sent to a message queue for processing. The monitoring system, as a consumer of the message queue, retrieves messages from the message queue. When the system receives a large number of messages, the content of the message includes the status values ​​of the detected points. In other words, the status values ​​of the detected points are placed into the message queue as message content and await processing by the monitoring system.

[0046] S2 filters messages in the message queue to select valid messages.

[0047] Among them, a valid message can be a message that may trigger the action of the linked device.

[0048] In this embodiment, valid messages can be filtered out using preset rules. The filtering can be performed once or multiple times as needed. Filtering can remove invalid messages, such as those not intended to trigger actions on linked devices.

[0049] Taking a three-layer message filtering mechanism as an example, valid messages can be selected from the message queue through each layer of filtering. These valid messages are those that may trigger subsequent actions. By filtering through each layer, invalid messages in the message queue can be filtered out, improving the speed of message consumption, avoiding message queue congestion, and ensuring strong real-time performance of messages.

[0050] S3, determine the target valid message in the valid message that will trigger the action of the linkage device.

[0051] Among them, preset trigger conditions can be set as needed. When it is determined that the selected valid message meets the preset trigger conditions, it is considered that the valid message can trigger the action of the linkage device, and the valid message is the target valid message.

[0052] S4, Distribute the target valid message that will trigger the action of the linked device to the corresponding target linked device.

[0053] Specifically, the defined target valid messages can be distributed to various business function modules. After a series of logical processing, the business modules will transform the messages into specific device action commands to achieve a complete linkage process.

[0054] The concurrent data processing method proposed in this embodiment of the invention filters messages in the message queue to obtain valid messages. It can quickly filter out invalid messages and rapidly and accurately select valid messages, improving message consumption speed, avoiding message queue congestion, and ensuring strong real-time performance. Furthermore, by setting a filtering mechanism, when it is determined that a valid message will trigger an action on a linked device, the valid message that will trigger the device action can be quickly distributed to the corresponding linked device, avoiding a large backlog in the message queue, ensuring message real-time performance, and avoiding the consumption of excessive server resources.

[0055] In some embodiments of the present invention, such as Figure 2 The diagram shows a flowchart of a concurrent data processing method according to another embodiment of the present invention, wherein messages in the message queue are filtered to select valid messages, that is, step S2 above includes at least steps S21 and S22, as detailed below.

[0056] S21, obtain a list of linkage rules for all detection points.

[0057] In this embodiment, a list of linkage rules can be preset and saved based on the specific linkage situation of the rail train and safety considerations. This list of linkage rules includes logical rules for the status values ​​of each detection point that triggers the linkage of the equipment.

[0058] In some embodiments, the list of linkage rules can be stored in a local cache, that is, the list of linkage rules for all detection points can be read from the local cache.

[0059] Understandably, for a rail train monitoring system, the entire system includes multiple devices such as multiple running trains. Each device has several detection points. During system operation, the background will simultaneously receive status detection data reported by multiple detection points from multiple devices. This data, as message content, is arranged in a message queue. This mechanism first checks whether the received message needs to be processed by reading the local cache.

[0060] For example, detecting events during train operation, such as fire alarms, requires setting up a series of detection rules. When a fire occurs, the status of relevant detection points may change. When the status values ​​of several detection points meet the pre-set linkage rules, a fire is confirmed. However, real-time monitoring systems generate a large number of messages that do not require logical processing. To quickly retrieve fire-related reports from detection points from the numerous received messages, it is necessary to filter the messages in the message queue, initially selecting those that conform to the fire linkage rules.

[0061] Based on this, technicians can independently set linkage rules as needed. These rules can include the preset status values ​​of all detection points and the conditional rules that all detection points must meet. These linkage rules serve as the core conditions for filtering messages in the queue, guiding the subsequent message pre-selection process. The local cache can include the system's local hard drive, used to store the pre-set linkage rules.

[0062] S22. If a message in the message queue satisfies the linkage rules in the linkage rule list, then the message is determined to be a valid message.

[0063] Specifically, the linkage rule is the rule that the point status value can satisfy to trigger the action of the linkage device. However, one message corresponds to one point status value, but the linkage rule can include the condition of one point status value or the logical combination condition of multiple point status values. Therefore, if the message satisfies the linkage rule, the message may trigger the action of the linkage device, but it may also need to be combined with other point status conditions to trigger it. Therefore, the message is a valid message, that is, a message that may trigger the action of the linkage device.

[0064] Furthermore, in the embodiments, such as Figure 2 As shown, when determining the target valid message that will trigger the action of the linkage device in the valid message, step S3 specifically includes:

[0065] S31, obtain the linkage rules satisfied by the messages in the message queue, and use them as pre-selected linkage rules. The pre-selected linkage rule is that at least one message contains a point state value that satisfies the linkage rule.

[0066] S32, obtain the real-time status values ​​of all detection points;

[0067] S33: Based on the pre-selected linkage rules and the real-time status values ​​of all detection points, obtain the target valid message, that is, obtain the message that will trigger the linkage device to take action.

[0068] For example, in monitoring fire alarm events in a rail train monitoring system, if the preset fire alarm linkage rule requires all three point status values ​​to be "true", and a message in the message queue satisfies the fire alarm linkage rule, then the fire alarm linkage rule is a pre-selected linkage rule. Further, the real-time point status values ​​of all detection points are matched against this fire alarm linkage rule. If a message exists that matches the combination of all point status values ​​in the fire alarm linkage rule, then this message is the target valid message that will trigger the fire alarm linkage device; otherwise, the message will not trigger the fire alarm linkage device to act.

[0069] In this embodiment, to address the issue that existing message consumption sorting processes cannot quickly filter invalid messages, this application addresses this by setting up filtering and matching steps for messages in the message queue. This allows for verification of whether received messages require subsequent processing by reading point status rules from a local cache. Since the local cache is read-only, this process can quickly consume a large number of concurrent messages, rapidly emptying the message queue to prevent message congestion. Furthermore, a pre-selected point status rule list is generated based on the filtered messages, facilitating the subsequent creation of an appropriate number of threads to process messages based on server performance. It is understood that by setting up this filtering process, the goal of quickly filtering invalid messages can be achieved, saving message sorting time.

[0070] In an embodiment of the present invention, the status values ​​of all detection points can be read from the Redis database (high availability database).

[0071] Specifically, for valid messages selected through the filtering mechanism, it is still necessary to determine whether these messages meet the triggering conditions, which requires real-time data. This process is no longer suitable for local caching, but still requires high-performance read and write speeds. Therefore, in this embodiment of the invention, a highly available database is used, such as Redis, as the data caching target. The Redis database cache handles the judgments in the business processing logic. Redis is an open-source non-relational key-value store that stores data in the form of key-value pairs. It has high read and write performance and is suitable for use as a cache. It performs a large number of read and write operations to verify whether messages meet the triggering conditions. The highly available database stores the point status values ​​of all linked devices, that is, the point status values ​​of all detection points.

[0072] In this embodiment, the status values ​​of all linked devices may change when a fire or emergency occurs. These status values ​​should correspond to the messages reported by the relevant detection points. To verify whether the selected valid messages meet the triggering conditions, the pre-selected linkage rules in the pre-selected linkage rule list need to be matched and verified with the status values.

[0073] In some embodiments of the present invention, when obtaining the target valid message according to the pre-selected linkage rules and the real-time point status values ​​of all detection points, the specific steps include: logically combining the real-time point status values ​​of all detection points according to the pre-selected linkage rules; obtaining the logical combination result of the point status values ​​of all detection points; if the logical combination result satisfies the linkage triggering condition corresponding to the pre-selected linkage rules, then the valid message corresponding to the real-time point status value whose logical result satisfies the linkage triggering condition is the target valid message.

[0074] Specifically, the real-time status values ​​of all detection points are combined according to the logic of the pre-selected linkage rules to obtain the result of the logical combination. For example, taking the fire alarm linkage rule as an example, if the status of the three points is 0, 1, and 1 respectively, the result of the logical combination of the three is 0. Only when the status of the three points is 1 will the result of the logical combination be 1. The result of the logical combination is matched with the pre-selected linkage rule. For example, the fire alarm linkage rule requires that the status of the three points be 1 in order to satisfy the fire alarm linkage action. That is, when the status value of the three points is 1, the corresponding message is the target valid message that triggers the fire alarm linkage. Conversely, if the result of the logical combination is 0, it does not match the fire alarm linkage rule and will not trigger the linkage of the fire alarm equipment.

[0075] In some embodiments of the present invention, after filtering out valid messages, the valid messages are saved to a thread queue, that is, the valid messages are further filtered by threads to obtain the target valid messages. An appropriate number of threads can be established to process messages according to the server performance.

[0076] After obtaining a valid target message, a thread can wait for the target business module to process it. However, since the processing by the business module takes a considerable amount of time, if information is not transmitted via a message queue, the thread will be continuously occupied, consuming a large amount of resources. After the linkage message is sent out, the pressure is distributed among the various business modules. Therefore, in some embodiments, using a message queue to distribute the valid target message to the target linkage device can speed up the process of freeing up threads and avoid message backlog.

[0077] Based on the above, regarding the message consumption mechanism, in some embodiments of the present invention, a three-layer filtering mechanism can be adopted, such as... Figure 3 The diagram shown is a schematic diagram of a three-layer screening mechanism according to an embodiment of the present invention.

[0078] The first-level filtering mechanism first selects valid messages from the message queue that meet the pre-selected linkage rules—that is, messages that may trigger the linkage device's action—and transfers them to the thread queue. In some embodiments, this message queue can be a Kafka message queue, and the messages in the Kafka message queue are Kafka messages. The Kafka system is a high-throughput distributed publish-subscribe messaging system. In the second-level filtering mechanism, messages that meet the triggering conditions—that is, target valid messages—are selected by determining whether the messages in the thread queue will trigger subsequent actions. In the third-level filtering mechanism, the target valid messages are distributed to the corresponding business modules through the message queue. The purpose of this operation is to free up threads, because the processing of business modules requires a long waiting time. If information is not transmitted through a message queue, the threads will be occupied indefinitely, consuming a lot of resources. After the linkage messages are sent out, the pressure is distributed to each business module.

[0079] Furthermore, in a real-time monitoring system, feedback messages from target linked devices are continuously received while messages are being sent. If the messages in the queue cannot be processed and updated in the data cache in a timely manner, the real-time performance of the messages will be severely affected. Embodiments of this invention can address this by setting a three-layer filtering mechanism, for example… Figure 3 As shown, it can quickly filter invalid messages, greatly improve message consumption speed, avoid message queue blockage, and ensure strong real-time performance.

[0080] In some embodiments of the present invention, such as Figure 4 The diagram shown is a flowchart of a concurrent data processing method according to another embodiment of the present invention, wherein the concurrent data processing method further includes steps S5 and S6, as detailed below.

[0081] S5, obtain feedback data from the target linkage device regarding the effective information of the target.

[0082] Understandably, after a series of logical processes, the business module transforms the valid message into a specific device action command and sends it to the target linked device. The target linked device then executes the command to complete the linkage process. Simultaneously, while the business module sends the message, the system continuously receives feedback data from the target linked device indicating that it has completed the corresponding command; this feedback data corresponds to the valid information.

[0083] S6 stores the feedback data in the underlying database.

[0084] In some embodiments, the underlying database may include a MongoDB database. MongoDB is a distributed storage database that, as an underlying database, has read-only and storable characteristics, and can be used for data persistence when business modules process messages. After the business module interacts with the device, the data is persisted in the MongoDB database, and feedback data is also stored in the MongoDB database. The underlying database may have page display functionality, allowing feedback data stored in the underlying database to be directly displayed to backend staff, facilitating the backend staff to modify or adjust the location status rules based on the feedback data.

[0085] In some embodiments of the present invention, such as Figure 5 The diagram shown is a flowchart of a concurrent data processing method according to another embodiment of the present invention, wherein the concurrent data processing method further includes steps S7 and S8, as detailed below.

[0086] S7 detects changes in the linkage rules through a distributed key-value storage monitoring mechanism.

[0087] Existing technologies typically create global entities by calling remote interfaces and sending and receiving messages. However, remote interfaces are time-consuming and unstable, and forwarding entity information using messages is cumbersome and consumes significant message queue server resources. This invention employs a distributed key-value storage monitoring mechanism to listen for changes in linkage rules. Specifically, this distributed key-value storage monitoring mechanism can be the ETCD monitoring mechanism, an open-source, distributed key-value data storage system. When backend personnel modify or adjust point status rules based on feedback data, the ETCD monitoring mechanism can directly detect these changes.

[0088] S8 updates the list of linkage rules stored in the local cache according to the changed linkage rules.

[0089] In this embodiment of the invention, cache synchronization between instances can be achieved through the ETCD listening mechanism. During the process of persisting data in the MongoDB database after the business module interacts with the device, the ETCD listening mechanism will also be triggered to synchronize the monitored changed point status rules to the local cache. The synchronous caching scheme of the present invention can save a lot of time and performance and ensure the real-time performance of the cache.

[0090] Based on the above, in some embodiments, such as Figure 6As shown, the concurrent data processing method of this invention can use a three-level data storage structure and a three-layer message filtering mechanism to filter out target valid messages and distribute them to business modules, thereby realizing the linkage of linked devices. Furthermore, memory synchronization can be achieved through an ETCD monitoring mechanism, involving various databases, multithreading, message queues, and other technologies.

[0091] Specifically, such as Figure 7 The diagram illustrates concurrent data processing according to an embodiment of the present invention. When the receiving system receives a large number of messages, the message receiving module first converts the information in the messages into corresponding message entities and sends them to the message queue. Then, a three-layer message filtering mechanism quickly consumes the messages in the message queue, and finally, the valid messages are distributed to various business function modules. After a series of logical processing, the business modules convert the messages into specific device action commands, realizing a complete linkage process. Furthermore, during the process of persisting data in the underlying database after data interaction between the business modules and the linked devices, the ETCD listening mechanism is also triggered. This invention uses a distributed key-value storage listening mechanism to achieve local cache synchronization, which can save a lot of time and performance, and ensure the real-time performance of the cache.

[0092] Furthermore, the three-layer message filtering mechanism includes a first-layer filtering mechanism, a second-layer filtering mechanism, and a third-layer filtering mechanism, which utilize message queues and multi-threading technologies to process high-concurrency messages at three levels. Different technologies are selected for message queues, business logic judgments, and business data persistence, which can greatly improve message consumption speed, avoid message queue congestion, and ensure strong real-time performance. Moreover, the synchronous caching scheme adopted in this embodiment can save a significant amount of time and performance, ensuring the real-time performance of the cache. The three-level data storage structure employs different technologies for message queues, business logic judgments, and business data persistence, utilizing three different types: local caching, high-availability databases, and underlying databases. This makes the data storage scheme more flexible and has wider business applicability, especially with more significant effects when handling concurrent messages.

[0093] In some embodiments of the present invention, such as Figure 8 The diagram shown is a block diagram of a comprehensive monitoring system for rail trains according to an embodiment of the present invention, wherein the comprehensive monitoring system for rail trains 10 includes a processor 1 and a memory 2.

[0094] The memory 1 is communicatively connected to the processor 2. The memory 2 stores a computer program that can be executed by the processor 1. When the computer program is executed by the processor 1, it implements any of the concurrent data processing methods mentioned above. This can greatly improve the message consumption speed, avoid message queue congestion, and ensure the strong real-time performance of messages. Furthermore, the synchronous caching scheme adopted in this embodiment of the invention can save a lot of time and performance and ensure the real-time performance of the cache.

[0095] In some embodiments of the present invention, such as Figure 9 The diagram shown is a block diagram of a comprehensive monitoring system for rail trains according to another embodiment of the present invention. The processor 1 is configured with a three-level data storage structure, including a local cache 11, a high-availability database 12, and a low-level database 13. This system can be combined with... Figure 9 and Figure 10 Understanding the three-level data storage structure of this invention embodiment, wherein, as... Figure 10 The diagram shown is a schematic diagram of a three-level data storage structure according to an embodiment of the present invention.

[0096] Local cache 11 stores the list of linkage rules for all detection points. It is read-only and can handle high-speed processing of concurrent messages. Local cache 11 also functions as shared memory. During the data persistence process between the business module and the device, if a change in the point status rule is detected by the distributed key-value storage monitoring mechanism, the changed point status rule can be directly synchronized to local cache 11 via the ETCD monitoring mechanism. High-availability database 12 stores the real-time point status values ​​of all detection points. Specifically, high-availability database 12 can utilize Redis, offering read-only and store-only functionality, and can be used for logical judgments in thread queues. Finally, underlying database 13 stores feedback data from the target linkage device regarding the target's valid information in the point status detection data. Specifically, underlying database 13 can utilize MongoDB, offering read-only and store-only functionality, and can be used for data persistence when the business module processes messages.

[0097] In some embodiments of the present invention, a computer-readable storage medium is also proposed, on which a computer program is stored. When the computer-readable storage medium is executed by a processor, it implements any of the concurrent data processing methods mentioned above, which can greatly improve the message consumption speed, avoid message queue congestion, and ensure the strong real-time performance of messages. Furthermore, the synchronous caching scheme adopted in the embodiments of the present invention can save a lot of time and performance and ensure the real-time performance of the cache.

[0098] Other configurations and operations of the train integrated monitoring system 10 according to embodiments of the present invention are known to those skilled in the art and will not be described in detail here.

[0099] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0100] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.

[0101] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A concurrent data processing method, characterized in that, For a rail train monitoring system, multiple detection points are set on the rail train, and the concurrent data processing method includes: Retrieve messages from the message queue, the content of which includes the status values ​​of the detection points; Filtering messages in the message queue to select valid messages includes: obtaining a list of linkage rules for all detection points; if a message in the message queue satisfies a linkage rule in the list of linkage rules, then the message is determined to be a valid message. The linkage rules include linkage triggering conditions that trigger the action of the linkage device when the point status value is satisfied. Determining the target valid message that will trigger the action of the linkage device in the valid messages includes: obtaining the linkage rules satisfied by the messages in the message queue as pre-selected linkage rules; obtaining the real-time point status values ​​of all detection points; logically combining the real-time point status values ​​of all detection points according to the pre-selected linkage rules; obtaining the logical combination result of the point status values ​​of all detection points; if the logical combination result satisfies the linkage triggering condition corresponding to the pre-selected linkage rule, then the valid message corresponding to the real-time point status value that satisfies the linkage triggering condition is the target valid message. Distribute the target valid message to the corresponding target linkage device.

2. The concurrent data processing method according to claim 1, characterized in that, Obtain the real-time status values ​​of all detection points, including: Read the real-time status values ​​of all detection points from the Redis database.

3. The concurrent data processing method according to claim 1 or 2, characterized in that, After filtering out the valid messages, the concurrent data processing method further includes: Save the valid message to the thread queue.

4. The concurrent data processing method according to claim 1 or 2, characterized in that, Distributing the target valid message that triggers the action of the linked device to the corresponding target linked device includes: The target valid message is distributed to the target linked device in the form of a message queue.

5. The concurrent data processing method according to claim 1 or 2, characterized in that, The concurrent data processing method further includes: Obtain feedback data from the target linkage device regarding valid information about the target; The feedback data is stored in the underlying database.

6. The concurrent data processing method according to claim 1, characterized in that, Retrieve a list of linkage rules for all detection points, including: Read the list of linkage rules for all detection points from the local cache.

7. The concurrent data processing method according to claim 6, characterized in that, The concurrent data processing method further includes: The change in the linkage rule was detected through a distributed key-value storage monitoring mechanism. The list of linkage rules stored in the local cache is updated according to the changed linkage rules.

8. The concurrent data processing method according to claim 5, characterized in that, The underlying database includes a MongoDB database, and the message queue is a Kafka message queue.

9. A comprehensive monitoring system for rail trains, characterized in that, include: processor; The memory is communicatively connected to the processor; The memory stores a computer program that can be executed by the processor, and when the computer program is executed by the processor, it implements the concurrent data processing method according to any one of claims 1-8.

10. The integrated monitoring system for rail trains according to claim 9, characterized in that, The processor is equipped with a local cache, a high-availability database, and an underlying database, wherein... The local cache is used to store a list of linkage rules for all detection points; The high-availability database is used to store the real-time status values ​​of all detection points; The underlying database is used to store feedback data from the target linkage device regarding effective information about the target.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer-readable storage medium is executed by a processor, it implements the concurrent data processing method according to any one of claims 1-8.

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