Network communication system and method for positioning crew in ship

Abstract

The invention provides an in-ship crew positioning network communication system and method, and relates to the technical field of network communication. The system comprises a data acquisition module, a system establishment module, a data evaluation module, a connection pool parameter configuration module, a test module and an optimization module. The method comprises the steps of starting a data acquisition module, establishing a database management system, evaluating database performance, configuring connection pool parameters, carrying out system testing, optimizing the connection pool parameters, and realizing sailor positioning and communication and continuous monitoring and maintenance. According to the in-ship crew positioning network communication system and method provided by the invention, a mode of optimizing connection pool configuration is adopted, the minimum connection number, the maximum connection number and the connection timeout time in the connection pool are adjusted step by step, optimal connection pool configuration parameters are approached step by step, and in a high-concurrency access scene, the communication efficiency is improved. And an updating request for quickly responding and processing the position information of the crew is made.

Description

Technical Field

[0001] The present invention relates to the technical field of network communications, and in particular to a network communication system and method for positioning crew members in a ship. Background Art

[0002] Maritime safety is a core issue in the global maritime transport system, particularly for large vessels such as naval vessels and ocean-going vessels. As the tonnage of these vessels continues to increase, crew management becomes increasingly complex. Vessel command requires meticulousness, precision, and swiftness, placing extremely high standards on crew management across all departments and compartments.

[0003] During seafaring, crew members are confined to their vessel. However, existing onboard crew location systems still have shortcomings, preventing ship management from promptly understanding the crew's location and movements in emergencies. For example, if a crew member encounters danger or suddenly falls ill, the inability to quickly locate them can delay rescue efforts and increase safety risks for the crew. Furthermore, if equipment failure causes crew members to lose contact in certain areas of the vessel, this can pose a threat to the vessel's safe operation.

[0004] The existing shipboard crew positioning system adopts a connection pool configuration strategy. The connection pool configuration strategy refers to a series of parameter settings and behavior planning for the connection pool in database connection management in order to optimize system performance and resource utilization. In the existing shipboard crew positioning system, in a high concurrent access scenario, when the minimum number of connections in the connection pool is set too low and cannot meet the high concurrent access requirements, the crew's location information update will be delayed due to untimely database connection acquisition. In an emergency, such as when the crew is in danger or needs emergency assistance, the management personnel cannot immediately obtain the latest crew location information, thereby delaying the rescue time. The lack of a reasonable connection pool configuration strategy and unreasonable connection pool configuration will cause database connections to be frequently created and destroyed, which not only increases the load on the database server, but also causes resource waste. The additional resource consumption will affect the operation of other important systems on the ship, such as navigation and communication, thereby indirectly affecting the safety of the crew. Summary of the Invention

[0005] In order to solve the technical problem in the prior art that the latest crew position information on a ship cannot be immediately obtained, thereby delaying rescue time and affecting crew safety, the present invention proposes a network communication system and method for positioning crew members on a ship.

[0006] In order to achieve the above purpose, the technical solution adopted by the present invention is: A crew positioning network communication system in a ship, the system includes a data acquisition module, a system establishment module, a data evaluation module, a connection pool parameter configuration module, a test module and an optimization module; wherein, Data acquisition module, used to obtain user parameters and equipment parameters in the ship; A system establishment module establishes a database management system and stores the user parameters and device parameters in the database management system; Data evaluation module, used to evaluate the database management system's carrying capacity and response time and predict the system's concurrent access volume; The connection pool parameter configuration module configures the minimum number of connections, maximum number of connections, and connection timeout of the connection pool according to the database management system's carrying capacity, concurrent access volume, and response time; The test module detects the minimum number of connections, maximum number of connections, and connection timeout period of the connection pool. It uses performance testing tools to simulate high-concurrency access and database connection requests and monitors the performance indicators of the connection pool during the test. The optimization module formulates adjustment strategies based on the results of monitoring tests and the load of the current database management system, and gradually adjusts and provides feedback on the minimum number of connections, maximum number of connections, and connection timeout in the connection pool.

[0007] On the other hand, the present invention also provides a method for the above-mentioned crew positioning network communication system in a ship, the method comprising the following steps: Step 1. Start the data acquisition module: collect user parameters and equipment parameters in the ship, and send the user parameters and equipment parameters to the database management system; Step 2, establish a database management system: establish a database management system on the server for storing the user parameters and device parameters; Step 3. Evaluate database performance: Evaluate the database management system's carrying capacity, response time, and concurrent access volume; Step 4. Configure connection pool parameters: Based on the evaluation results, configure the connection pool parameters, including the minimum number of connections, the maximum number of connections, and the connection timeout; Step 5. Perform system testing: After configuration is complete, use performance testing tools to simulate high-concurrency access and database connection requests, and monitor the performance indicators of the connection pool; Step 6. Optimize connection pool parameters: Based on the test results and the load of the current database management system, formulate an adjustment strategy, gradually adjust the connection pool parameters, and record the specific time, target parameters, and expected adjustment effect of each adjustment; Step 7: Crew positioning and communication: After optimizing the connection pool parameters, crew members use communication devices to upload their location information in real time and communicate with other crew members or shore personnel through the communication devices. Step 8. Continuous monitoring and maintenance: Based on the location information uploaded by the crew, the database management system is continuously monitored and regularly maintained.

[0008] Compared with the prior art, the present invention has the following advantages: This application adopts a method of optimizing the connection pool configuration, that is, formulating an adjustment strategy based on the load of the current database management system, gradually adjusting the minimum number of connections, the maximum number of connections and the connection timeout period in the connection pool, and continuously iterating and optimizing to the minimum number of connections, the maximum number of connections and the shortest connection timeout period, gradually approaching the optimal connection pool configuration parameters, and being able to quickly respond and process crew position information update requests in high-concurrency access scenarios, solving the problem that the existing crew position information update is delayed due to untimely database connection acquisition, making it impossible for managers to immediately obtain the latest crew position information in an emergency, thereby delaying rescue. Through gradual adjustment and optimization, when the crew encounters danger or needs emergency assistance, the manager can immediately obtain the latest crew position information, thereby responding quickly, greatly shortening the rescue time.

[0009] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 This is a structural block diagram of a crew positioning network communication system within a ship according to the present invention; Figure 2 is a flow chart of a communication adjustment strategy for crew positioning network within a ship according to the present invention; Figure 3 The present invention is a flow chart of a method for positioning a crew member in a ship through a network communication. DETAILED DESCRIPTION

[0011] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions 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, so as to more clearly understand the purposes, features and advantages of the present invention. It should be understood that the embodiments shown in the drawings are not limitations on the scope of the present invention, but are only intended to illustrate the essential spirit of the technical solutions of the present invention. Obviously, the embodiments described are only some 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 those of ordinary skill in the art without making creative work should fall within the scope of protection of the present invention.

[0012] Unless the context requires otherwise, throughout the specification and claims, the word "comprise" and variations such as "include" and "have" should be construed in an open, inclusive sense, that is, should be interpreted to mean "including, but not limited to."

[0013] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any manner in one or more embodiments.

[0014] As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. It should be noted that the term "or" is generally employed in its sense including "and / or" unless the context clearly dictates otherwise.

[0015] In the following description, in order to clearly show the structure and working mode of the present invention, many directional words will be used for description, but words such as "front", "back", "left", "right", "outside", "inside", "outward", "inward", "up", and "down" should be understood as convenient terms and should not be understood as restrictive terms.

[0016] The following describes the implementation details of the embodiments of the present invention in detail with reference to the accompanying drawings. The following content is only provided to facilitate understanding of the implementation details and is not necessary for implementing this solution.

[0017] The structural block diagram of the crew positioning network communication system in the ship of this application is as follows Figure 1 As shown, the crew positioning network communication system in the ship includes a data acquisition module, a system establishment module, a data evaluation module, a connection pool parameter configuration module, a testing module and an optimization module.

[0018] Specifically, the data acquisition module is used to acquire user and device parameters within the vessel. User parameters include the number of users and their behavior patterns; device parameters include the number of devices and their types. The number of users includes the number of crew members and management personnel, and user behavior patterns include login frequency and data request frequency. It should be noted that in the data acquisition module, user parameters also include user location information; device parameters also include device status and network connection status.

[0019] The system establishment module establishes a database management system based on the user parameters and equipment parameters in the ship acquired by the data acquisition module and stores the user parameters and equipment parameters in the database management system. It should be noted that the database management system includes but is not limited to the relational database management system MySQL.

[0020] The data assessment module evaluates the database management system's carrying capacity and response time, and predicts the system's concurrent access volume. Carrying capacity refers to the maximum amount of data, transactions, or user requests a database management system can handle while ensuring stable performance. Response time refers to the complete time period from a user initiating a request to the system returning a result, including network latency, query processing time, and result transmission time. Concurrent access volume refers to the number of users or services initiating requests to the database at the same time.

[0021] The connection pool parameter configuration module configures connection pool parameters, including the minimum and maximum number of connections, and the connection timeout period, based on the database management system's carrying capacity, concurrent access volume, and response time. The connection pool is a key technical component in a database management system, used to reuse and manage database connections. The minimum number of connections is the number of connections created when the connection pool is initialized, maintaining resident connections. The maximum number of connections is the maximum number of connections allowed in the connection pool. The connection timeout period is the maximum amount of time a client waits for a connection.

[0022] The test module is responsible for detecting the minimum number of connections, maximum number of connections, and connection timeout period of the connection pool. It uses performance testing tools to simulate high-concurrency access and database connection requests and monitor the performance indicators of the connection pool during the test.

[0023] The optimization module, based on the results of monitoring tests and the current database management system load, formulates an adjustment strategy, gradually adjusting the minimum and maximum number of connections in the connection pool, and providing feedback. If the adjustment results meet expectations, feedback is fed back to the "Connection Pool Parameter Configuration Module," forming a closed loop to continuously improve system performance. If not, the adjustment step size is gradually increased or decreased, and adjustments continue.

[0024] In some embodiments, the optimization module formulates an adjustment strategy based on the load of the current database management system according to the results of the monitoring test, such as Figure 2 As shown, the adjustment strategy includes the following steps: S1. Data collection and analysis phase: First, set a fixed monitoring cycle and use the monitoring tools provided by the database management system to monitor the performance indicators. At the end of each monitoring cycle, collect and analyze the performance indicator data of the connection pool in the test module from the monitoring terminal of the database management system; For example, performance indicator data of the connection pool is collected from the monitoring terminal of the database management system every 5 minutes.

[0025] The data analysis is: Calculate the average response time, maximum response time, and minimum response time.

[0026] Analyze throughput trends and identify peak and trough periods.

[0027] Count error rates and identify error types and when they occur.

[0028] Evaluate resource utilization and determine whether the system is approaching a bottleneck Sample data: Monitoring period: 5 minutes Collected data example: Timestamp: 2024-12-12 10:00:00; Response time: 450 ms; Throughput: 200 requests / s; Error rate: 0.5%; CPU utilization: 60%; Memory utilization: 70%.

[0029] S2, Preliminary Adjustment Phase: Based on the data analysis results, preliminarily design adjustment thresholds for the connection pool configuration parameters of response time, throughput, and error rate. If the database management system's response time is long, consider increasing the minimum number of connections; if the database management system's performance degrades under high concurrency, consider adjusting the maximum number of connections. For S2, there are the following examples: For example: response time threshold: 500ms, exceeding this value is considered long; throughput decrease threshold: 10% decrease compared to the previous cycle; error rate increase threshold: 1% increase compared to the previous cycle.

[0030] At this point, make preliminary adjustments: If the average response time exceeds 500ms and the CPU utilization is less than 80%, consider increasing the minimum number of connections, initially setting the increase to 10; If the throughput drops by more than 10% compared to the previous period, consider increasing the maximum number of connections, initially set to 50. If the error rate increases by more than 1% compared to the previous cycle, consider shortening the connection timeout. For example, if the original connection timeout is 30 seconds, it can be initially shortened to 5 seconds. The adjusted data is: average response time: 550ms, CPU utilization: 65% → increase the minimum number of connections from 20 to 30; Throughput: 180 requests / s (down 11% from the previous cycle) → Increased maximum number of connections from 500 to 550; Error rate: 1.2% → Reduce the connection timeout from 30 seconds to 25 seconds.

[0031] S3. Further adjustment stage: Based on the step size set in the initial adjustment stage, determine whether the effect of the initial adjustment strategy meets expectations. If it meets expectations, jump to provide feedback. If it does not meet expectations, gradually increase or decrease the adjustment step size, and record the specific time, target parameters and expected adjustment effect of each adjustment; The S3 step is analyzed as follows: 1. Setting step size: minimum number of connections adjustment step size: 5, maximum number of connections adjustment step size: 10, timeout adjustment step size: 2 seconds; 2. Determine the effectiveness of adjustments: After implementing the initial adjustments, wait for a 5-minute monitoring period to collect new performance indicator data. Analyze the adjusted performance indicators to determine whether the expected results have been achieved, such as reduced response time, increased throughput, or decreased error rate. 3. Adjustment step size: If the adjustment effect does not meet the expectations, gradually increase or decrease the adjustment step size. For example, if the response time does not improve significantly after increasing the minimum number of connections, increase the number of connections by 5 again. At this time, record the specific time, minimum number of connections, maximum number of connections, connection timeout period, and expected adjustment effect of each adjustment; For example: After the initial adjustment, the average response time is still 520ms → increase the minimum number of connections again from 30 to 35; Throughput increased to 190 requests / s, but still not meeting expectations → Increase the maximum number of connections from 550 to 560; The error rate dropped to 0.8%, but the connection timeout adjustment had no significant effect. → Shortened the connection timeout from 25 seconds to 23 seconds.

[0032] S4, implementation adjustment and monitoring phase: According to the further adjustment phase, the minimum number of connections, maximum number of connections, and connection timeout of the connection pool are gradually adjusted. After each adjustment, wait for a monitoring cycle to collect new performance indicator data and continuously monitor the performance indicators of the database management system; For example, after adjusting the minimum number of connections to 35, the average response time dropped to 480ms. After adjusting the maximum number of connections to 560, the throughput increased to 205 requests / s; After adjusting the connection timeout to 23 seconds, the error rate stabilized at around 0.7%.

[0033] S5. Iterative optimization and recording stage: Based on the performance of the database management system after each adjustment, continuously iteratively optimize the adjustment strategy, gradually approaching the optimal connection pool configuration parameters, that is, the parameter combination with the shortest response time, the highest throughput, the lowest error rate and reasonable resource utilization. Detailed records are kept of the history of each adjustment, including the adjustment time, step size, adjustment reason, adjustment content, including the minimum number of connections, maximum number of connections, connection timeout period, and performance indicators before and after the adjustment.

[0034] For example: Adjust time: 2024-12-12 10:10:00 Adjustment reason: Average response time exceeds the threshold Adjustment content: Minimum number of connections increased from 30 to 35 Performance indicators before adjustment: response time 550ms, throughput 180 requests / s, error rate 1.2%; Performance indicators after adjustment: response time 480ms, throughput 205 requests / s, error rate 0.7%.

[0035] Furthermore, in the step S5, the iterative optimization includes the following steps: b1. Collect performance data: After each connection pool parameter adjustment, obtain performance indicator data from the database management system's monitoring terminal, including the database management system's response time, throughput, error rate, and resource utilization, to reflect the current performance status of the database management system; b2. Analyze performance: Analyze the collected performance data and evaluate the impact of the current connection pool configuration parameters on system performance. By comparing the performance under different adjustment strategies, the database management system can compare the specific impact of the current connection pool configuration parameters on system performance. b3. Formulate an iterative strategy: Based on the analysis results, formulate the next iterative optimization strategy and determine the adjustment direction and step size, that is, increase or decrease the minimum number of connections, the maximum number of connections, and adjust the specific values ​​of the connection timeout. Adjusting the connection timeout includes shortening the connection timeout. b4. Implement adjustments: According to the established iteration strategy, gradually adjust the connection pool parameters. During the adjustment process, ensure the continuity and stability of the system to avoid interference with crew positioning services; b5. Continuous monitoring and evaluation: After the adjustment is completed, the performance indicators of the database management system are continuously monitored to evaluate the effectiveness of the adjustment strategy. The database management system can determine whether the adjustment strategy is effective and whether the expected performance improvement goals have been achieved; b6. Recording and Optimization: During continuous monitoring, record the specific time, target parameters, adjustment strategy, and performance after each adjustment. Based on the evaluation results, continuously optimize the adjustment strategy and gradually approach the optimal connection pool configuration parameters.

[0036] It should be noted that through continuous iterative optimization, the database management system can find the optimal connection pool configuration parameters and significantly improve the performance of the database management system, including shortening response time, increasing throughput, reducing error rates, and optimizing resource utilization.

[0037] In some embodiments, gradually adjusting the minimum number of connections, the maximum number of connections, and the connection timeout period in the connection pool includes the following specific steps: Step 1: Parameter definition: including definition: Minimum number of connections at time t ; The maximum number of connections at time t ; The connection timeout at time t ; Current response time R(t); Current concurrent query volume Q(t); Database CPU utilization U(t); The number of active connections in the connection pool L(t) is in the range of: ; Step 2: Establish the objective function: According to the defined parameters, establish the objective function: in, is the weight coefficient, according to the objective function, the minimum number of connections , Maximum number of connections and timeout Make adjustments; Step 3: Minimum number of connections Adjustment: Dynamic adjustment is performed based on the response time R(t) and the number of active connections L(t), including the following formula: For formula (1): For formula (2): in, is the response time threshold; is the utilization threshold; To adjust the step size; Step 4: Maximum number of connections Adjustment: Adjustment is made based on CPU utilization U(t) and concurrent query volume Q(t), including the following formula: For formula (3): If U(t) safe And Q(t)>Q peak ; For formula (4): If U(t)>=U safe ; Among them, U safe Q is the safe CPU utilization; peak This is the historical concurrent query peak value; To adjust the step size; The global maximum number of connections. Step 5: Set the connection timeout Adjustment: Adjustment is made based on the average waiting time W(t), including the following formula: For formula (5): If ; For formula (6): If ; Where W(t) is the average waiting time of the connection waiting queue, in milliseconds; To adjust the step size; is the minimum timeout period; Step 6. Dynamic adjustment: based on the objective function and minimum number of connections , Maximum number of connections and connection timeout , periodically collect R(t), Q(t), U(t), L(t), W(t), and calculate new parameters at this time , and use sliding average to avoid parameter mutation. The sliding average formula is: in, It is the smoothing coefficient, and the minimum number of connections, maximum number of connections and connection timeout of the connection pool are gradually adjusted according to the calculation results.

[0038] It should be noted that through the collaborative work of the data acquisition module, data evaluation module and optimization module, the system can accurately identify and resolve performance bottlenecks, thereby significantly improving the system's concurrent processing capabilities and response speed. Especially in high-concurrency scenarios, the database management system can maintain stable operation and provide accurate positioning services for crew members.

[0039] In some embodiments, as Figure 3 ​As shown, a method for positioning a crew member in a ship's network communication system includes the following steps: Step 1. Start the data acquisition module: collect user parameters and equipment parameters in the ship. After pre-processing, the collected user parameters and equipment parameters will be sent to the database management system; Step 2, establish a database management system: according to user parameters and equipment parameters, establish a database management system on the server; Step 3. Evaluate database performance: Use the data evaluation module to evaluate the database management system's carrying capacity, response time, and concurrent access volume; Step 4. Configure connection pool parameters: Based on the evaluation results, configure the minimum number of connections, maximum number of connections, and connection timeout period of the connection pool; Step 5. Perform system testing: After configuration is complete, use the performance testing tool in the test module to simulate high-concurrency access and database connection requests, and monitor the performance indicators of the connection pool; Step 6. Optimize connection pool parameters: Based on the test results, use the optimization module to gradually adjust the connection pool parameters and record the specific time, target parameters, and expected adjustment effect of each adjustment. Optimizing connection pool parameters also includes determining the optimization priority based on the test results.

[0040] Step 7: Crew positioning and communication: After optimizing the connection pool parameters, crew members use communication devices to upload their location information in real time and communicate with other crew members or shore personnel through the communication devices. Step 8. Continuous Monitoring and Maintenance: Based on the location information uploaded by crew members, the database management system is continuously monitored and regularly maintained. This maintenance includes data backup, virus detection, and performance tuning to ensure the long-term stable operation of the database management system. It should be noted that crew members can upload their location information in real time and communicate efficiently with other crew members or shore personnel through communication equipment. This not only improves the accuracy of crew positioning, but also enhances the efficiency and reliability of communication.

[0041] Furthermore, in some embodiments, in Step 5, performing the system test includes the following steps: a1. Select performance testing tool: Select LoadRunner as the performance testing tool; a2. Configure the test environment: Use the LoadRunner load testing tool to set up the test environment, including the test server, database server, and communication network. a3. Execute the test: Run the script in the database management system to simulate high-concurrency access and database connection requests, and use performance testing tools to monitor the response time, throughput, and error rate of the connection pool; a4. Analyze test results: Collect and analyze test results, and develop optimization strategies and adjustment plans.

[0042] Furthermore, in some embodiments, in Step 6, determining the optimization priority includes the following steps: Step 1: Collect and analyze database management system test results to identify performance bottlenecks.

[0043] Specifically, the LoadRunner load testing tool can be used to simulate high-concurrency access and database connection requests, testing the database management system's response time, throughput, and error rate. Testing has shown that the database management system's response time increases significantly in high-concurrency scenarios, throughput decreases, and error rates increase. Response time becomes the most significant performance bottleneck, with average response time increasing from a normal 50 milliseconds to over 200 milliseconds.

[0044] Step 2: Sort performance bottlenecks based on the urgency of business needs.

[0045] Specifically, high response time delays will lead to untimely updates of crew location information, affecting the efficiency of rescue and emergency response. Based on the urgency of business needs, response time is regarded as the primary performance bottleneck to be optimized.

[0046] Step 3: Evaluate the impact of parameter adjustments on the stability of the database management system and adjust the priority order.

[0047] Specifically, consider increasing the maximum number of connections in the connection pool and adjusting the connection timeout to improve the response time. Use simulation tools to simulate the behavior of the database management system after parameter adjustment and evaluate the impact on the stability of the database management system. In this case, increase the maximum number of connections from 300 to 500 and adjust the connection timeout from 60 seconds to 30 seconds to effectively improve the response time.

[0048] Step 4: Consider resource utilization and ultimately determine optimization priorities.

[0049] Specifically, taking into account resource requirements, optimization effects, and long-term operating costs, it was decided to implement the above parameter adjustment plan. In the short term, a certain amount of server resource investment will need to be increased, but in the long run, the system's performance and stability will be significantly improved, and operating costs caused by performance issues will be reduced. Ultimately, it was determined that optimizing the maximum number of connections and connection timeout period in the connection pool was the primary task, with the goal of improving system response time.

[0050] Example 1 Next, refer to Figure 2 , and give examples to analyze the adjustment strategy.

[0051] First, a set of performance indicator data of the connection pool in the test module is collected from the monitoring terminal of the database management system, including response time, throughput and number of concurrent connections, as shown in Table 1.

[0052] As can be seen from Table 1, the response time increases at time T2, the throughput decreases, and the number of concurrent consecutive calls increases.

[0053] Initial adjustment phase: Analyze the above data. Since the response time in Table 1 increases, the minimum number of connections should be increased. At the same time, since the performance decreases due to the increase in the number of concurrent connections, the maximum number of connections should be adjusted.

[0054] For example: increase the minimum number of connections from 10 to 20 and adjust the maximum number of connections from 500 to 600.

[0055] Further adjustments: Based on the step size set in the initial adjustment, increase the minimum number of connections by 10 and the maximum number of connections by 50 to determine the effectiveness of the initial adjustment strategy.

[0056] If expectations are met, such as reduced response time and improved throughput, the system will jump to provide feedback.

[0057] If the expected result is not achieved, the adjustment step size should be gradually increased or decreased, and the specific time, target parameters and expected adjustment effect of each adjustment should be recorded. First adjustment: The minimum number of connections was increased to 20, and the maximum number of connections was increased to 600, but the response time was still high.

[0058] Second adjustment: Increase the minimum number of connections to 30, keep the maximum number of connections unchanged, and test again.

[0059] Implementation adjustment and monitoring: Based on the results of the further adjustment phase, the minimum number of connections, maximum number of connections, and connection timeout of the connection pool are gradually adjusted, and the performance indicators of the database management system are continuously monitored. After multiple adjustments, it is finally determined that the system performance is optimal when the minimum number of connections is 35 and the maximum number of connections is 600. At this time, the time, parameter changes, and performance indicator changes of each adjustment are recorded. After multiple iterations, the optimal connection pool configuration parameters are finally determined.

[0060] The crew positioning network communication system and method provided in this application provide a reliable and efficient solution for crew positioning and communication within the ship through accurate data collection, scientific performance evaluation, comprehensive system testing and optimization, efficient positioning and communication functions, and a continuous monitoring and maintenance mechanism. It enables management personnel to immediately obtain the latest crew position information, thereby responding quickly and greatly shortening the rescue time.

[0061] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, from all points of view, the embodiments should be regarded as illustrative and non-restrictive. The scope of the present invention is defined by the appended claims rather than the foregoing description. It is intended that all changes that come within the meaning and range of equivalents of the claims be included in the present invention, and any reference signs in the claims should not be construed as limiting the claims to which they relate.

[0062] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A crew positioning network communication system in a ship, characterized in that: The system includes a data acquisition module, a system establishment module, a data evaluation module, a connection pool parameter configuration module, a testing module and an optimization module; wherein, Data acquisition module, used to obtain user parameters and equipment parameters in the ship; A system establishment module establishes a database management system and stores the user parameters and device parameters in the database management system; Data evaluation module, used to evaluate the database management system's carrying capacity and response time and predict the system's concurrent access volume; The connection pool parameter configuration module configures the minimum number of connections, maximum number of connections, and connection timeout of the connection pool according to the database management system's carrying capacity, concurrent access volume, and response time; The test module detects the minimum number of connections, maximum number of connections, and connection timeout period of the connection pool. It uses performance testing tools to simulate high-concurrency access and database connection requests and monitors the performance indicators of the connection pool during the test. The optimization module formulates adjustment strategies based on the results of monitoring tests and the load of the current database management system, and gradually adjusts and provides feedback on the minimum number of connections, maximum number of connections, and connection timeout in the connection pool.

2. The system according to claim 1, wherein: In the data acquisition module, the user parameters include the number of users and user behavior patterns, and the device parameters include the number of devices and device types; wherein the number of users includes crew members and management personnel, and the user behavior patterns include login frequency and data request frequency.

3. The system according to claim 1, wherein: The database management system includes a relational database management system MySQL.

4. A method for the crew positioning network communication system in a ship according to any one of claims 1 to 3, characterized in that: The method comprises the following steps: Step 1. Start the data acquisition module: collect user parameters and equipment parameters in the ship, and send the user parameters and equipment parameters to the database management system; Step 2, establish a database management system: establish a database management system on the server for storing the user parameters and device parameters; Step 3. Evaluate database performance: Evaluate the database management system's carrying capacity, response time, and concurrent access volume; Step 4. Configure connection pool parameters: Based on the evaluation results, configure the connection pool parameters, including the minimum number of connections, the maximum number of connections, and the connection timeout; Step 5. Perform system testing: After configuration is complete, use performance testing tools to simulate high-concurrency access and database connection requests, and monitor the performance indicators of the connection pool; Step 6. Optimize connection pool parameters: Based on the test results and the load of the current database management system, formulate an adjustment strategy, gradually adjust the connection pool parameters, and record the specific time, target parameters, and expected adjustment effect of each adjustment; Step 7: Crew positioning and communication: After optimizing the connection pool parameters, crew members use communication devices to upload their location information in real time and communicate with other crew members or shore personnel through the communication devices. Step 8. Continuous monitoring and maintenance: Based on the location information uploaded by the crew, the database management system is continuously monitored and regularly maintained.

5. The method according to claim 4, characterized in that In Step 5, the system test includes the following steps: a1. Select the LoadRunner load testing tool; a2. Configure the test environment: Use the LoadRunner load testing tool to set up the test environment, including the test server, database server, and communication network. a3. Execute the test: Run the script in the database management system to simulate high-concurrency access and database connection requests, and use performance testing tools to monitor the response time, throughput, and error rate of the connection pool; a4. Collect and analyze test results, and formulate optimization strategies and adjustment plans.

6. The method according to claim 4, characterized in that In Step 6, an adjustment strategy is formulated based on the load of the current database management system according to the test results, wherein the adjustment strategy includes the following steps: S1, data collection and analysis phase: after a monitoring cycle ends, the performance indicator data of the connection pool in the test module is collected from the monitoring terminal of the database management system and analyzed; S2, Preliminary Adjustment Phase: Based on the analysis results, a preliminary adjustment strategy for the connection pool configuration parameters is designed. If the database management system's response time is long, consider increasing the minimum number of connections. If the database management system's performance degrades under high concurrency, consider adjusting the maximum number of connections. S3, further adjustment stage: Based on the step size set for the initial adjustment, determine whether the effect of the initial adjustment strategy meets expectations. If it meets expectations, provide feedback. If it does not meet expectations, gradually increase or decrease the adjustment step size, and record the specific time, target parameters, and expected adjustment effect of each adjustment; S4. Implementation, Adjustment, and Monitoring Phase: During the further adjustment phase, the minimum number of connections, maximum number of connections, and connection timeout period of the connection pool are gradually adjusted, and the performance indicators of the database management system are continuously monitored. S5, iterative optimization and recording stage: Based on the performance indicators of the database management system after each adjustment, continuously iteratively optimize and adjust the strategy, gradually approach the optimal connection pool configuration parameters and record them.

7. The method according to claim 6, characterized in that In S5, the iterative optimization includes the following steps: b1. Collect performance data: After each adjustment of the connection pool configuration parameters, obtain performance indicator data from the database management system's monitoring terminal, including the database management system's response time, throughput, error rate, and resource utilization; b2. Performance analysis: Analyze the collected performance indicator data, evaluate the impact of the current connection pool configuration parameters on system performance, and compare the performance under different adjustment strategies; b3. Formulate an iterative strategy: Based on the analysis results, formulate the next iterative optimization strategy and determine the adjustment direction and step size; b4. Implement adjustments: Gradually adjust the connection pool parameters according to the established iterative optimization strategy; b5. Continuous monitoring and evaluation: After the adjustment is completed, the performance indicators of the database management system are continuously monitored to evaluate the effectiveness of the adjustment strategy and determine whether the expected performance improvement goals have been achieved; b6. Recording and Optimization: During continuous monitoring, record the specific time, target parameters, adjustment strategy, and performance after each adjustment. Based on the evaluation results, continuously optimize the adjustment strategy and gradually approach the optimal connection pool configuration parameters.

8. The method according to claim 4, characterized in that Step 6 of step 6 gradually adjusts the connection pool parameters, including the following steps: Step 1: Parameter definition: including defining the minimum number of connections at time t ;The maximum number of connections at time t ; Connection timeout at time t Current response time R(t); Current concurrent query volume Q(t); Database CPU utilization U(t); Number of active connections in the connection pool L(t), range: ; Step 2: Establish the objective function: According to the defined parameters, establish the objective function: in, is the weight coefficient, according to the objective function, the minimum number of connections , Maximum number of connections and connection timeout Make adjustments; Step 3: Minimum number of connections Adjustment: Dynamic adjustment is performed based on the response time R(t) and the number of active connections L(t), including the following formula: For formula (1): For formula (2): in, is the response time threshold; is the utilization threshold; To adjust the step size; Step 4: Maximum number of connections Adjustment: Adjustment is made based on CPU utilization U(t) and concurrent query volume Q(t), including the following formula: For formula (3): If U(t) safe And Q(t)>Q peak ;​ For formula (4): If U(t)>=U safe ; Among them, U safe Q is the safe CPU utilization; peak This is the historical concurrent query peak value; To adjust the step size; The global maximum number of connections. Step 5: Set the connection timeout Adjustment: Adjustment is made based on the average waiting time W(t), including the following formula: For formula (5): If ; For formula (6): If ; Where W(t) is the average waiting time of the connection waiting queue, in milliseconds; To adjust the step size; is the minimum timeout period; Step 6. Dynamic adjustment: based on the objective function and minimum number of connections , Maximum number of connections and connection timeout , periodically collect R(t), Q(t), U(t), L(t), W(t), and calculate new parameters at this time , and use sliding average to avoid parameter mutation. The sliding average formula is: in, It is the smoothing coefficient, and the minimum number of connections, maximum number of connections and connection timeout of the connection pool are gradually adjusted according to the calculation results.

9. The method according to claim 4, characterized in that In Step 6, optimizing the connection pool parameters further includes determining the optimization priority according to the test results.

10. The method according to claim 9, characterized in that Determining the optimization priority includes the following steps: Step 1: Collect and analyze database management system test results to identify performance bottlenecks; Step 2: Sort performance bottlenecks based on the urgency of business needs; Step 3: Evaluate the impact of parameter adjustments on the stability of the database management system and adjust the priority order; Step 4: Consider resource utilization and ultimately determine optimization priorities.

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