RS485 data prefetching method and device based on optical fiber and electronic equipment

Abstract

The invention relates to an RS485 data prefetching method and device based on an optical fiber and electronic equipment, and the method comprises the steps: obtaining RS485 communication data, and carrying out the cleaning and formatting of the data; predicting a future data demand based on the cleaned and formatted data, and outputting a prediction result; and in response to a prediction result, triggering a prefetching condition, obtaining to-be-prestored data from the data source, and caching the data into a rapid storage medium. According to the RS485 data prefetching method and device based on the optical fiber and the electronic equipment, data which is possibly needed in the future is predicted and cached in advance, so that signal delay is reduced, the real-time performance, reliability and efficiency of a communication system are improved, user experience is improved, technical support is provided for stable operation of the communication system, and meanwhile the data prefetching method and device based on the optical fiber and the electronic equipment have good application prospects. The delay can be reduced without increasing the transmission rate or optimizing the signal processing algorithm, and the cost is saved.

Description

Technical Field

[0001] The invention relates to the field of communication data pre-fetching, and in particular to a data pre-fetching method, device and electronic equipment of RS485 based on optical fiber. Background Art

[0002] The current fiber-based RS485 communication system has a signal delay problem, which is mainly caused by factors such as long data transmission distance, signal attenuation during transmission, and delay in system data processing. Traditional technologies usually use increased transmission rate or optimized signal processing algorithms to reduce delays, but these methods are often costly and have limited effects. In addition, with the increase in the amount of communication data, the signal delay problem becomes more serious, affecting the real-time performance and reliability of the system. Therefore, it needs to be improved. Summary of the invention

[0003] Based on this, it is necessary to provide a data pre-fetching method, device and electronic device for RS485 based on optical fiber, in order to reduce the delay by increasing the transmission rate or optimizing the signal processing algorithm, which is costly and has limited effect. Moreover, as the amount of communication data increases, the signal delay problem becomes more serious, affecting the real-time and reliability of the system.

[0004] The present invention provides a data pre-fetching method of RS485 based on optical fiber, the method comprising: Get RS485 communication data, clean and format the data; Based on the cleaned and formatted data, predict future data needs and output the prediction results; In response to the prediction result triggering the pre-fetching condition, the data to be pre-stored is obtained from the data source, and the data is cached in a fast storage medium.

[0005] In one embodiment, the obtaining of RS485 communication data and cleaning and formatting of the data include: Based on the RS485 communication interface, obtain the status data collected by the data acquisition module on the device; Identify and remove outliers and noise in the data based on statistical methods and filtering algorithms to generate cleaned data; Convert the cleaned data into a unified format.

[0006] In one embodiment, predicting future data demand based on the cleaned and formatted data and outputting the prediction result includes: Get the cleaned and formatted data; The data is input into an autoregressive model and a prediction result is output. The autoregressive model is based on a time series prediction algorithm and is trained using historical data samples and prediction result samples as training data.

[0007] In one of the embodiments, in response to the prediction result triggering the pre-fetching condition, acquiring the data to be pre-stored from the data source, and caching the data into a fast storage medium, comprises: Integrate pre-fetch conditions into the rule engine; In response to the prediction result triggering the pre-fetching condition, the prediction result is parsed according to the rule engine; Get the data to be stored from the data source and cache the data in a fast storage medium.

[0008] In one embodiment, obtaining the data to be pre-stored from the data source and caching the data in a fast storage medium includes: Obtain the data to be stored from the data source; According to the Redis cluster, use the shard key to distribute data to different nodes; Call Celery asynchronous tasks to cache data in fast storage media.

[0009] In one embodiment, the acquiring data from the data source and caching the data in a fast storage medium further includes: In response to the data cache time being greater than the expiration time, the cached data is cleared.

[0010] In one of the embodiments, the pre-fetching condition is that the predicted value exceeds a threshold value, and / or at every preset time interval.

[0011] The present invention also provides a data pre-fetching device of RS485 based on optical fiber, comprising: The acquisition module is used to obtain RS485 communication data and clean and format the data; The prediction module is used to predict future data demand based on the cleaned and formatted data and output the prediction results; The response module is used to trigger the pre-fetching condition in response to the prediction result, obtain the data to be pre-stored from the data source, and cache the data in a fast storage medium.

[0012] The present invention also provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the optical fiber-based RS485 data pre-fetching method described in any one of the above is implemented.

[0013] The present invention also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the optical fiber-based RS485 data pre-fetching method described above is implemented.

[0014] The above-mentioned optical fiber-based RS485 data pre-fetching method, device and electronic device reduce signal delay by predicting and caching data that may be needed in the future in advance, thereby improving the real-time, reliability and efficiency of the communication system, improving user experience, and providing technical support for the stable operation of the communication system. At the same time, there is no need to reduce delay by increasing the transmission rate or optimizing the signal processing algorithm, thereby saving costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 The present invention is a flow chart of a method for pre-fetching data based on RS485 of an optical fiber in an embodiment; Figure 2 A schematic diagram of a data processing flow in one embodiment; Figure 3 A schematic diagram of a data flow for predicting the future in an embodiment; Figure 4 A schematic diagram of an integrated rule engine flow in one embodiment; Figure 5 A schematic diagram of a data cache process in one embodiment; Figure 6 It is a structural schematic diagram of a data pre-fetching device based on optical fiber RS485 in one embodiment; Figure 7 FIG. 4 is a diagram showing the internal structure of an electronic device in one embodiment. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Combine the following Figure 1-Figure 7The present invention describes the data pre-fetching method, device and electronic equipment of RS485 based on optical fiber.

[0019] like Figure 1 As shown, in one embodiment, a data pre-fetching method based on RS485 of optical fiber comprises the following steps: Step S100, obtaining RS485 communication data, and cleaning and formatting the data.

[0020] By collecting RS485 communication data, cleaning and formatting the data, it is convenient to provide a high-quality data foundation for subsequent prediction model training.

[0021] Step S200, based on the cleaned and formatted data, predict future data demand and output the prediction result.

[0022] By building a forecasting module, you can automatically perform forecasts to obtain data that may be needed in the future.

[0023] Step S300, in response to the prediction result triggering the pre-fetching condition, the data to be pre-stored is obtained from the data source, and the data is cached in a fast storage medium.

[0024] By obtaining and caching data in advance based on prediction results, it is convenient to ensure a quick response when data is needed.

[0025] The fiber-based RS485 data pre-fetching method reduces signal delay by predicting and caching data that may be needed in the future in advance, thereby improving the real-time, reliability and efficiency of the communication system, improving the user experience, and providing technical support for the stable operation of the communication system. At the same time, there is no need to increase the transmission rate or optimize the signal processing algorithm to reduce delay, thus saving costs.

[0026] In this embodiment, see Figure 2 , obtain RS485 communication data, and clean and format the data, including the following steps: Step S110, based on the RS485 communication interface, obtaining status data collected by the data collection module on the device.

[0027] By deploying the data acquisition module on the equipment, the data transmitted via the RS485 communication protocol can be collected in real time.

[0028] Step S120, identifying and removing outliers and noise in the data according to statistical methods and filtering algorithms to generate cleaned data.

[0029] Since the acquired data may contain noise and irrelevant information, data cleaning must be performed to remove these interference items.

[0030] Assuming that the collected data is time series data, the moving average method is used to smooth the data. The formula is as follows: ,in, represents the smoothed data value at time point t; represents the original data value; N is the size of the moving window.

[0031] In this way, it is possible to ensure that the data provided to the predictive model is accurate and reliable, thereby improving the model's predictive accuracy.

[0032] Step S130, converting the cleaned data into a unified format.

[0033] The cleaned data is formatted to ensure data consistency and availability, so that the processed data can be used as input for subsequent predictive model training.

[0034] In this embodiment, see Figure 3 , based on the cleaned and formatted data, predict future data needs and output the prediction results, including the following steps: Step S210, obtaining the cleaned and formatted data.

[0035] The processed data can be used as input for subsequent prediction model training.

[0036] Step S220, inputting data into an autoregressive model and outputting a prediction result. The autoregressive model is based on a time series prediction algorithm and is trained using historical data samples and prediction result samples as training data.

[0037] An autoregressive model is a common time series forecasting method that assumes that future values ​​can be predicted by a linear combination of past values.

[0038] In the autoregressive model, the following formula is used to express the predicted value of the time series: ,in, is the predicted value at time point t; is the actual value at the previous time point; is the input signal at the current time point; a and b are model parameters, which are estimated by minimizing the prediction error, for example, using the least squares method; is the error term.

[0039] The implementation of the prediction module includes the following sub-steps: Data input: Input the preprocessed historical data into the prediction model.

[0040] Parameter training: Use historical data to train model parameters a and b.

[0041] Prediction execution: Based on the trained model parameters, perform the following prediction calculations: , mid-term, is the predicted value at a future time point t.

[0042] Prediction result processing: The prediction results output by the prediction module will be used to guide the formulation of data prefetching strategies.

[0043] During the implementation process, first collect enough historical data, including time series data and corresponding input signals. Then, use this data to train the prediction model and determine the model parameters a and b. Once the model training is completed, it can be used to predict future data needs.

[0044] Suppose you have electricity consumption data from the past month and want to predict electricity consumption for the next month. Input the past data into the prediction module, and after parameter training, the model will output the predicted value of future electricity consumption. In this way, you can obtain data that may be needed in the future in advance, thereby optimizing the entire data management and processing process.

[0045] In this embodiment, see Figure 4 , in response to the prediction result triggering the pre-fetching condition, obtaining the data to be pre-stored from the data source, and caching the data into a fast storage medium, including the following steps: Step S310, integrating the pre-fetching conditions into the rule engine.

[0046] In order to improve the intelligence level of data prefetching, this solution integrates a high-performance rule engine, such as the Drools rule engine. The main responsibility of the rule engine is to parse and execute a series of predefined rules that determine under what conditions the data prefetching operation should be triggered.

[0047] The following are the detailed steps for rule engine integration and its application: 1. Choice of rule engine: In this solution, Drools is selected as the rule engine because it provides powerful rule processing capabilities and can be easily integrated with existing Java applications.

[0048] 2. Rule definition and writing: Based on the business requirements of the system and the data pre-fetching strategy, a series of rules are defined. These rules are written in a way that is easy to understand and maintain, usually using a syntax similar to natural language.

[0049] 3. Integration of rule engine: Integrating Drools rule engine into the system includes the following steps: Configure the environment: Install and configure the Drools rule engine in the system.

[0050] Load rules: Load the written rule file into the rule engine.

[0051] Execution of rules: When the system detects that specific conditions are met, the rule engine automatically executes the relevant pre-fetching rules.

[0052] In this process, the rule engine continuously monitors system events and data, and once the conditions are matched, the corresponding data pre-fetching rules are triggered.

[0053] During the implementation process, we first analyze the business logic of the system to determine which conditions should trigger data prefetching. Then, we write rules based on these conditions and deploy the rules to the Drools rule engine. For example, a rule may be: if the data requested by the user has been accessed more than the threshold number of times in the past hour, prefetch the data. When this rule is loaded into the rule engine, the engine automatically monitors data access and performs prefetching operations when the conditions are met.

[0054] This approach ensures the real-time and accuracy of data prefetching, greatly improving the system's response speed and user experience.

[0055] Step S320, in response to the prediction result triggering the pre-fetching condition, the prediction result is parsed according to the rule engine.

[0056] Prefetch conditions are designed based on the system business logic and the output of the prediction model. These prefetch conditions specify under what conditions the data prefetch operation should be triggered. For example, if the prediction model predicts that a specific data set will be frequently accessed in the near future, the system will load this data into the cache in advance according to the prefetch rules.

[0057] The implementation of prefetch conditions involves the following steps: Event triggering: For event-based prefetching rules, when a specific event is detected, such as a change in user behavior or system status, data prefetching is triggered immediately.

[0058] Time period: For time-based prefetching rules, the system will automatically perform data prefetching operations according to the set time period.

[0059] Once the pre-fetch trigger condition is detected, the rule engine will determine the corresponding pre-fetch rule and execute the pre-fetch operation.

[0060] Step S330, obtaining the data to be pre-stored from the data source, and caching the data in a fast storage medium.

[0061] Based on the results of the predictive model, the system identifies data sets that will be frequently accessed.

[0062] The rule engine determines whether a prefetch operation needs to be performed based on the prefetch rules.

[0063] If necessary, the system will automatically obtain data from the data source and cache it to fast storage media.

[0064] When the data is actually needed, the system can read it directly from the cache, greatly reducing the time for data access.

[0065] In this way, the data prefetching strategy not only optimizes the data loading speed, but also improves the overall system performance and user experience.

[0066] In this embodiment, see Figure 5 , obtaining the data to be pre-stored from the data source and caching the data into a fast storage medium, including the following steps: Step S331, obtaining the data to be pre-stored from the data source.

[0067] This step includes obtaining data from structured data sources, such as relational databases, using SQL queries, and obtaining data from unstructured data sources, such as through API requests.

[0068] Step S332: Distribute data to different nodes using shard keys according to the Redis cluster.

[0069] By using Redis clusters and shard keys to distribute data to different nodes, the performance and scalability of the cache system can be significantly improved.

[0070] Step S333, calling the Celery asynchronous task to cache the data into a fast storage medium.

[0071] The use of Celery asynchronous tasks and fast storage media not only improves system performance and scalability, but also meets real-time and high-concurrency business requirements, providing stable technical support for business growth.

[0072] In this embodiment, obtaining data from a data source and caching the data in a fast storage medium also includes the following steps: Step S334, in response to the data cache time being greater than the expiration time, clearing the cached data.

[0073] By regularly cleaning up cached data, you can effectively prevent invalid or outdated data from being stored in the cache, thereby maintaining the real-time and consistency of the system.

[0074] It should be additionally explained that the pre-fetching condition is that the predicted value exceeds a threshold value and / or at every preset time interval.

[0075] The following is a description of the optical fiber-based RS485 data pre-fetching device provided by the present invention. The optical fiber-based RS485 data pre-fetching device described below and the optical fiber-based RS485 data pre-fetching method described above can be referred to each other.

[0076] like Figure 6 As shown, in one embodiment, a data pre-fetching device based on optical fiber RS485 includes an acquisition module 610 , a prediction module 620 and a response module 630 .

[0077] The acquisition module 610 is used to acquire RS485 communication data and clean and format the data.

[0078] The prediction module 620 is used to predict future data demand based on the cleaned and formatted data, and output the prediction result.

[0079] The response module 630 is used to obtain the data to be pre-stored from the data source in response to the prediction result triggering the pre-fetching condition, and cache the data in a fast storage medium.

[0080] In this embodiment, the acquisition module 610 is specifically used for: Based on the RS485 communication interface, obtain the status data collected by the data acquisition module on the device; Identify and remove outliers and noise in the data based on statistical methods and filtering algorithms to generate cleaned data; Convert the cleaned data into a unified format.

[0081] In this embodiment, the prediction module 620 is specifically used for: Get the cleaned and formatted data; The data is input into the autoregressive model and the prediction result is output. The autoregressive model is based on the time series prediction algorithm and is trained with historical data samples and prediction result samples as training data.

[0082] In this embodiment, the response module 630 is specifically used for: Integrate pre-fetch conditions into the rule engine; In response to the prediction result triggering the pre-fetching condition, the prediction result is parsed according to the rule engine; Get the data to be stored from the data source and cache the data in a fast storage medium.

[0083] In this embodiment, the data to be pre-stored is obtained from the data source, and the data is cached in a fast storage medium, specifically for: Obtain the data to be stored from the data source; According to the Redis cluster, use the shard key to distribute data to different nodes; Call Celery asynchronous tasks to cache data in fast storage media.

[0084] In this embodiment, data is obtained from a data source and cached in a fast storage medium, and is also specifically used for: In response to the data cache time being greater than the expiration time, the cached data is cleared.

[0085] The optical fiber-based RS485 data pre-fetching device reduces signal delay by predicting and caching data that may be needed in the future in advance, thereby improving the real-time, reliability and efficiency of the communication system, improving the user experience, and providing technical support for the stable operation of the communication system. At the same time, there is no need to increase the transmission rate or optimize the signal processing algorithm to reduce delay, thus saving costs.

[0086] Figure 7 An example of a physical structure diagram of an electronic device is shown. The electronic device may be a smart terminal, and its internal structure diagram may be as follows: Figure 7 As shown. The electronic device includes a processor, a memory and a network interface connected via a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a data pre-fetching method based on optical fiber RS485 is implemented, and the method includes: Get RS485 communication data, clean and format the data; Based on the cleaned and formatted data, predict future data needs and output the prediction results; In response to the prediction result triggering the pre-fetching condition, the data to be pre-stored is obtained from the data source, and the data is cached in a fast storage medium.

[0087] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present invention, and does not constitute a limitation on the electronic device to which the scheme of the present invention is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0088] On the other hand, the present invention also provides a computer storage medium storing a computer program, which implements a data pre-fetching method based on optical fiber RS485 when the computer program is executed by a processor, the method comprising: Get RS485 communication data, clean and format the data; Based on the cleaned and formatted data, predict future data needs and output the prediction results; In response to the prediction result triggering the pre-fetching condition, the data to be pre-stored is obtained from the data source, and the data is cached in a fast storage medium.

[0089] In another aspect, a computer program product or a computer program is provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, a method for pre-fetching data of RS485 based on optical fiber is implemented, the method comprising: Get RS485 communication data, clean and format the data; Based on the cleaned and formatted data, predict future data needs and output the prediction results; In response to the prediction result triggering the pre-fetching condition, the data to be pre-stored is obtained from the data source, and the data is cached in a fast storage medium.

[0090] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0091] By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0092] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0093] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A data pre-fetching method of RS485 based on optical fiber, characterized in that, The method comprises: Get RS485 communication data, clean and format the data; Based on the cleaned and formatted data, predict future data needs and output the prediction results; In response to the prediction result triggering the pre-fetching condition, the data to be pre-stored is obtained from the data source, and the data is cached in a fast storage medium.

2. The data pre-fetching method of RS485 based on optical fiber according to claim 1, characterized in that, The RS485 communication data is obtained and the data is cleaned and formatted, including: Based on the RS485 communication interface, obtain the status data collected by the data acquisition module on the device; Identify and remove outliers and noise in the data based on statistical methods and filtering algorithms to generate cleaned data; Convert the cleaned data into a unified format.

3. The data pre-fetching method of RS485 based on optical fiber according to claim 2, characterized in that, The method predicts future data needs based on the cleaned and formatted data and outputs prediction results, including: Get the cleaned and formatted data; The data is input into an autoregressive model and a prediction result is output. The autoregressive model is based on a time series prediction algorithm and is trained using historical data samples and prediction result samples as training data.

4. The data pre-fetching method of RS485 based on optical fiber according to claim 3, characterized in that, The method triggers a pre-fetch condition in response to the prediction result, obtains the data to be pre-stored from the data source, and caches the data in a fast storage medium, including: Integrate pre-fetch conditions into the rule engine; In response to the prediction result triggering the pre-fetching condition, the prediction result is parsed according to the rule engine; Get the data to be stored from the data source and cache the data in a fast storage medium.

5. The data pre-fetching method of RS485 based on optical fiber according to claim 4, characterized in that, The step of obtaining the data to be pre-stored from the data source and caching the data in a fast storage medium includes: Obtain the data to be stored from the data source; According to the Redis cluster, use the shard key to distribute data to different nodes; Call Celery asynchronous tasks to cache data in fast storage media.

6. The data pre-fetching method of RS485 based on optical fiber according to claim 5, characterized in that, The method of acquiring data from a data source and caching the data in a fast storage medium further includes: In response to the data cache time being greater than the expiration time, the cached data is cleared.

7. The data pre-fetching method of RS485 based on optical fiber according to any one of claims 1 to 6, characterized in that: The pre-fetching condition is that the predicted value exceeds a threshold value, and / or at every preset time interval.

8. A data pre-fetching device for RS485 based on optical fiber, characterized in that: include: The acquisition module is used to obtain RS485 communication data and clean and format the data; The prediction module is used to predict future data demand based on the cleaned and formatted data and output the prediction results; The response module is used to trigger the pre-fetching condition in response to the prediction result, obtain the data to be pre-stored from the data source, and cache the data in a fast storage medium.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the optical fiber-based RS485 data pre-fetching method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the data pre-fetching method of RS485 based on optical fiber according to any one of claims 1 to 7 are implemented.

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