Wireless meter control method and system

Abstract

The invention relates to the field of wireless sensors, in particular to a wireless meter control method and system, and specifically, each meter maintains a queue of a slow start threshold value and a congestion window value when entering fast retransmission recently, and acquires signal strength regularly; when fast retransmission is triggered, calculating an average value and a standard deviation of all values in the queue, if the standard deviation is smaller than one fourth of the average value, calculating a new slow start threshold value according to the slow start threshold value and the average value, otherwise, calculating a signal intensity change condition from the current moment to the last time of triggering fast retransmission, determining a new slow start threshold value based on the change condition, and updating the slow start threshold value maintained by the meter; and adjusting the congestion window to the slow start threshold value, increasing to the average value according to a linear increasing mode, and adjusting the congestion window in real time according to the signal intensity.

Description

Technical Field

[0001] The present invention relates to the field of wireless sensors, and in particular to a wireless meter control method and system. Background Art

[0002] Wireless meters play an important role in infrastructure such as smart grids, smart water services, and smart gas services, and have even become a feature of modern urban management and public services. Wireless meters provide great convenience for monitoring and management of industries such as water supply, electricity, and natural gas by collecting real-time data and transmitting it wirelessly to the central system. These wireless meters are usually installed in users' homes or industrial equipment, and record the changes of various physical quantities such as current, voltage, water flow, and air pressure in real time, and send these data to data concentrators or gateways, and then aggregate them to the back-end system for analysis, statistics, and processing. Compared with traditional wired metering systems, wireless meter networks have the advantages of more flexible deployment methods, lower costs, easier installation, and easier maintenance.

[0003] However, with the increasing number of wireless meters and the increase in the frequency of data collection, the problem of network congestion in data transmission has become increasingly prominent. Wireless communication networks are usually affected by factors such as signal interference, bandwidth limitations, and multi-user competition, which lead to problems such as packet loss, increased latency, and reduced network throughput during transmission. These problems not only affect the real-time and accuracy of wireless meter data, but may also lead to serious consequences such as abnormal system alarms and untimely data updates, which in turn affect the efficiency and reliability of the intelligent management system. Effective congestion control in wireless meter networks has become the key to ensuring system stability and improving data transmission efficiency. Summary of the invention

[0004] In order to ensure that the wireless meter can send data to the base station quickly and stably, firstly, the present invention provides a wireless meter control method, the method comprising the following steps: Each meter maintains a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and collects signal strength periodically; When fast retransmission is triggered, the average value and standard deviation of all values ​​in the queue are calculated. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, the signal strength change between the current time and the last time fast retransmission is triggered is calculated, and a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated. The congestion window is adjusted to the slow start threshold, and after increasing to the average value in a linear increasing manner, the congestion window is adjusted in real time according to the signal strength.

[0005] Optionally, the new slow start threshold is calculated according to the slow start threshold and the average value, specifically: Calculate the ratio of the standard deviation to the average value, subtract the ratio from 1 as the adjustment factor, calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount according to the adjustment factor and the relative deviation; If the average value is greater than the current slow start threshold, the adjustment amount is added to the current slow start threshold as the new slow start threshold. If the average value is less than the current slow start threshold, the adjustment amount is subtracted from the current slow start threshold as the new slow start threshold. If the average value is equal to the current threshold, the slow start threshold remains unchanged.

[0006] Optionally, determining a new slow start threshold based on the change is specifically: Obtaining an average change rate and an average signal strength in the change situation; If the average signal strength is greater than the current signal strength, then if the average rate of change is less than zero, the slow start threshold is lowered, otherwise, the slow start threshold remains unchanged; If the average signal strength is less than or equal to the current signal strength, then if the average change rate is less than zero, the slow start threshold is kept unchanged; otherwise, the slow start threshold is increased.

[0007] Optionally, the real-time adjustment of the congestion window according to the signal strength is specifically: Calculate the probability of triggering fast retransmission under the current signal strength and the current congestion window based on historical data; The number of ACKs is determined according to the probability. If the probability is greater than the upper limit, the congestion window decreases by 1 for each ACK of the number of ACKs received. If the probability is less than the lower limit, the congestion window increases by 1 for each ACK of the number of ACKs received. Otherwise, the congestion window size remains unchanged.

[0008] Optionally, the triggering condition for the fast retransmission is: receiving three repeated ACKs in succession, or expiration of a timeout timer.

[0009] Secondly, the present invention also provides a wireless meter control system, the system comprising the following modules: The collection module is used for each meter to maintain a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and to collect signal strength at regular intervals; A slow start threshold adjustment module is used to calculate the average value and standard deviation of all values ​​in the queue when fast retransmission is triggered. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, a change in signal strength between the current moment and the last time fast retransmission was triggered is calculated, a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated; The data transmission module is used to adjust the congestion window to the slow start threshold, increase it to the average value in a linear increasing manner, and then adjust the congestion window in real time according to the signal strength.

[0010] Optionally, the new slow start threshold is calculated according to the slow start threshold and the average value, specifically: Calculate the ratio of the standard deviation to the average value, subtract the ratio from 1 as the adjustment factor, calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount according to the adjustment factor and the relative deviation; If the average value is greater than the current slow start threshold, the adjustment amount is added to the current slow start threshold as the new slow start threshold. If the average value is less than the current slow start threshold, the adjustment amount is subtracted from the current slow start threshold as the new slow start threshold. If the average value is equal to the current threshold, the slow start threshold remains unchanged.

[0011] Optionally, determining a new slow start threshold based on the change is specifically: Obtaining an average change rate and an average signal strength in the change situation; If the average signal strength is greater than the current signal strength, then if the average rate of change is less than zero, the slow start threshold is lowered, otherwise, the slow start threshold remains unchanged; If the average signal strength is less than or equal to the current signal strength, then if the average change rate is less than zero, the slow start threshold is kept unchanged; otherwise, the slow start threshold is increased.

[0012] Optionally, the real-time adjustment of the congestion window according to the signal strength is specifically: Calculate the probability of triggering fast retransmission under the current signal strength and the current congestion window based on historical data; The number of ACKs is determined according to the probability. If the probability is greater than the upper limit, the congestion window decreases by 1 for each ACK of the number of ACKs received. If the probability is less than the lower limit, the congestion window increases by 1 for each ACK of the number of ACKs received. Otherwise, the congestion window size remains unchanged.

[0013] Optionally, the triggering condition for the fast retransmission is: receiving three repeated ACKs in succession, or expiration of a timeout timer.

[0014] Finally, the present invention also provides a computer program, wherein the computer program comprises the following modules: The collection module is used for each meter to maintain a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and to collect signal strength at regular intervals; A slow start threshold adjustment module is used to calculate the average value and standard deviation of all values ​​in the queue when fast retransmission is triggered. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, a change in signal strength between the current moment and the last time fast retransmission was triggered is calculated, a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated; The data transmission module is used to adjust the congestion window to the slow start threshold, increase it to the average value in a linear increasing manner, and then adjust the congestion window in real time according to the signal strength.

[0015] When the network congestion is relatively stable, that is, when the standard deviation of the congestion window value is relatively small, the present invention adjusts the new slow start threshold according to the average value of the slow start threshold and the congestion window value, thereby avoiding the transmission rate drop that may be caused by blind halving; and when the standard deviation is relatively large, the slow start threshold is adjusted according to the change in signal strength, thereby avoiding the use of a larger slow start threshold when the channel quality is poor, thereby causing more packet loss. Moreover, in the congestion avoidance stage, the congestion window is adjusted in real time according to the signal strength, and the available channel resources are used more flexibly. When the signal strength is good, the congestion window can be more actively increased to improve the transmission rate. When the signal strength is poor, the congestion window can be reduced in time to avoid further packet loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the process of Embodiment 1; Figure 2 A schematic diagram of congestion window adjustment is shown; Figure 3 It is a structural diagram of embodiment 2. DETAILED DESCRIPTION

[0017] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0018] Specific embodiment 1, as Figure 1 As shown, embodiment 1 provides a wireless meter control method, characterized in that the method comprises the following steps: S1, each meter maintains a slow start threshold, a queue of congestion window values ​​that recently entered fast retransmission, and collects signal strength periodically; The slow start threshold is a parameter in TCP congestion control. It determines when the congestion window (cwnd) switches from the slow start phase to the congestion avoidance phase. In the slow start phase, cwnd increases by 1 for each ACK received, growing exponentially. When the sender receives three repeated ACKs in a row, it enters the fast retransmission phase and retransmits the data packet immediately without waiting for the timeout timer to expire. The meter records the congestion window size when the most recent fast retransmissions occurred, and records the congestion window size values ​​when the most recent fast retransmissions occurred in the queue. In addition, the meter also collects signal strength (RSSI) at regular intervals. Meters include but are not limited to water meters, gas meters, and electricity meters.

[0019] S2, when fast retransmission is triggered, the average value and standard deviation of all values ​​in the queue are calculated. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, the signal strength change between the current moment and the last time fast retransmission was triggered is calculated, and a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated; When three repeated ACKs are received in succession, or the timeout timer expires and triggers a fast retransmission, the average and standard deviation of all values ​​in the queue are calculated. If the standard deviation is less than one-fourth of the average, the congestion window values ​​during the most recent fast retransmissions are relatively concentrated, and the network congestion is relatively stable. In this case, a new slow start threshold is calculated based on the current slow start threshold (ssthresh) and the average value of the congestion window value in the queue. In an alternative embodiment, the standard deviation is less than the threshold, and a new slow start threshold is calculated based on the slow start threshold and the average value, and the threshold is determined based on the average value. In one embodiment, the average of the current slow start threshold and the average value of the congestion window value in the queue is used as the new slow start threshold.

[0020] In yet another embodiment, the new slow start threshold is calculated based on the slow start threshold and the average value, specifically: Calculate the ratio of the standard deviation to the average value, subtract the ratio from 1 as the adjustment factor, calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount according to the adjustment factor and the relative deviation; If the average value is greater than the current slow start threshold, the adjustment amount is added to the current slow start threshold as the new slow start threshold. If the average value is less than the current slow start threshold, the adjustment amount is subtracted from the current slow start threshold as the new slow start threshold. If the average value is equal to the current threshold, the slow start threshold remains unchanged.

[0021] Calculate the ratio of the standard deviation of the congestion window queue to the average value, and then subtract the ratio from 1 to obtain the adjustment factor. If the standard deviation is very small relative to the average value, the ratio is close to 0 and the adjustment factor is close to 1. If the standard deviation is large, that is, close to one-fourth of the average value, the ratio is close to 0.25 and the adjustment factor is close to 0.75. Calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount based on the adjustment factor and the relative deviation. In one embodiment, the adjustment factor is multiplied by the relative deviation as the adjustment coefficient, and the product of the adjustment coefficient and the current slow start threshold or the average value or the last element in the queue is used as the adjustment amplitude. If the average value is greater than the current slow start threshold, it means that the congestion level in the recent few times is relatively light, and the adjustment amount is added to the current slow start threshold; if the average value is less than the current slow start threshold, it means that the congestion level in the recent few times is relatively heavy, and the adjustment amount is subtracted from the current slow start threshold; if the average value is equal to the current slow start threshold, it means that the congestion level in the recent few times is basically matched with the current slow start threshold, and the slow start threshold is kept unchanged. Assume that the current slow start threshold is 20, the average value of the congestion window queue is 25, the standard deviation is 2, the ratio of the standard deviation to the average value is 0.08, the adjustment factor is 0.92, the relative deviation is 0.25, and the adjustment coefficient is 0.23. Since the average value 25 is greater than the current slow start threshold 20, the new slow start threshold is 20+0.23*20=24.6, which is rounded to 25.

[0022] In yet another embodiment, the new slow start threshold is calculated based on the slow start threshold and the average value, specifically: Calculate the ratio of the standard deviation to the average value, subtract the ratio from 1 as the adjustment factor, calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount according to the adjustment factor and the relative deviation; If the average value is greater than the current slow start threshold, the adjustment amount is added to the current slow start threshold as a new slow start threshold; if the average value is less than the current slow start threshold, the slow start threshold is kept unchanged or the relative deviation is reduced.

[0023] If the standard deviation is greater than or equal to one-fourth of the average value or the threshold, it means that the congestion window values ​​during the most recent fast retransmissions are relatively dispersed, indicating that the network congestion situation fluctuates greatly. In this case, the historical information of the congestion window alone is not enough to accurately judge the network status, and it is necessary to combine the changes in signal strength. In one embodiment, the signal strength changes from the last time the fast retransmission was triggered to the current moment are calculated. If the signal strength continues to decrease, it means that the channel quality has deteriorated, and the slow start threshold is reduced; if the signal strength continues to rise, it means that the channel quality has improved, and the slow start threshold is increased; if the signal strength fluctuates greatly, it means that the channel is unstable, and the slow start threshold is kept unchanged or reduced.

[0024] In another preferred embodiment, the determining of a new slow start threshold based on the change is specifically: Obtaining an average change rate and an average signal strength in the change situation; If the average signal strength is greater than the current signal strength, then if the average rate of change is less than zero, the slow start threshold is lowered, otherwise, the slow start threshold remains unchanged; If the average signal strength is less than or equal to the current signal strength, then if the average change rate is less than zero, the slow start threshold is kept unchanged; otherwise, the slow start threshold is increased.

[0025] Obtain the average rate of change and the average signal strength in the change situation, preferably, obtain the change in signal strength from the last time fast retransmission was triggered to the current moment. If the average signal strength value is greater than the current signal strength, if the average rate of change is less than zero, it further confirms that the signal strength is on a downward trend. At this time, the slow start threshold is lowered to avoid further packet loss. For example, the slow start threshold can be multiplied by a factor less than 1, such as 0.8 or 0.9. If the average signal strength is higher than the current value, but if the rate of change is not less than zero, it means that the signal strength may have only temporarily decreased and then recovered. At this time, the slow start threshold is kept unchanged to avoid unnecessary adjustments.

[0026] If the current signal strength is greater than the average signal strength, but if the rate of change is less than zero, it means that the signal strength may only drop temporarily. In this case, keep the slow start threshold unchanged to avoid unnecessary adjustments. If the average rate of change is greater than or equal to zero: This means that the signal strength is rising or remaining stable. In this case, increase the slow start threshold to increase the sending rate and better utilize channel resources. For example, you can multiply the slow start threshold by a factor greater than 1, such as 1.1 or 1.2.

[0027] S3, adjusting the congestion window to the slow start threshold, increasing it linearly to the average value, and then adjusting the congestion window in real time according to the signal strength.

[0028] After calculating the new slow start threshold, the congestion window is first set to the new slow start threshold to avoid network congestion or bandwidth waste caused by the congestion window being too large or too small; starting from the new slow start threshold, the congestion window grows linearly until it reaches the average value of the congestion window during the most recent fast retransmissions. After the congestion window reaches the average value of the congestion window, the congestion window is adjusted in real time according to the current signal strength. In one embodiment, if the signal strength is greater than a preset value, the congestion window increase is increased, for example, according to a slope of 1.5 or 2, and if the signal strength is not greater than a preset value, the congestion window increase is reduced, for example, according to a slope of 0.8. Wherein, the slope is the linear slope of the transmission round and the congestion window. Assuming that the congestion window is 24, the congestion window is increased in a linear manner, that is, 1 MSS is increased for each RTT until the congestion window reaches 30, and then the congestion window is adjusted in real time according to the signal strength. For example, if the signal strength suddenly increases by 5dBm, the congestion window can be increased at a faster rate, for example, 1 MSS is increased for every 2 RTTs. If the signal strength suddenly drops by 3dBm, you can start increasing the congestion window at a slower rate, such as increasing it by 1 MSS every 4 RTTs.

[0029] In yet another embodiment, adjusting the congestion window in real time according to the signal strength is specifically: Calculate the probability of triggering fast retransmission under the current signal strength and the current congestion window based on historical data; The number of ACKs is determined according to the probability. If the probability is greater than the upper limit, the congestion window decreases by 1 for each ACK of the number of ACKs received. If the probability is less than the lower limit, the congestion window increases by 1 for each ACK of the number of ACKs received. Otherwise, the congestion window size remains unchanged.

[0030] A model is established based on historical data. The model can predict the probability of triggering fast retransmission under specific signal strength and congestion window. Preferably, machine learning or statistical methods are used to build the model, and then the probability of fast retransmission is calculated based on the current signal strength and congestion window. If the probability is greater than the upper limit, congestion is likely to occur, and the congestion window is reduced. If the probability is less than the lower limit, the congestion window is increased to improve transmission efficiency. If the probability is between the upper and lower limits, the congestion window is kept unchanged. In this embodiment, not only the congestion window is increased, but also if the probability of fast retransmission is high, the congestion window is reduced to avoid triggering fast retransmission. Figure 2As shown, after the congestion window reaches the average value of 20, the congestion window may increase in the direction of 1 or decrease in the direction of 2. In one embodiment, the ACK number is determined according to the probability. Specifically, if the probability is greater than the upper limit, the difference between the probability and the upper limit is calculated. If the probability is less than the lower limit, the difference between the lower limit and the probability is calculated. The ACK number is calculated based on the difference. The present invention does not limit the specific calculation method. It only needs to meet the condition that the larger the difference, the smaller the ACK number, and the smaller the difference, the larger the ACK number. After obtaining the congestion window adjusted in real time, the meter controls the transmission of data according to the congestion window.

[0031] Specific embodiment 2 provides a wireless meter control system, such as Figure 3 As shown, the system includes the following modules: The collection module is used for each meter to maintain a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and to collect signal strength at regular intervals; A slow start threshold adjustment module is used to calculate the average value and standard deviation of all values ​​in the queue when fast retransmission is triggered. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, a change in signal strength between the current moment and the last time fast retransmission was triggered is calculated, a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated; The data transmission module is used to adjust the congestion window to the slow start threshold, increase it to the average value in a linear increasing manner, and then adjust the congestion window in real time according to the signal strength.

[0032] Optionally, the new slow start threshold is calculated according to the slow start threshold and the average value, specifically: Calculate the ratio of the standard deviation to the average value, subtract the ratio from 1 as the adjustment factor, calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount according to the adjustment factor and the relative deviation; If the average value is greater than the current slow start threshold, the adjustment amount is added to the current slow start threshold as the new slow start threshold. If the average value is less than the current slow start threshold, the adjustment amount is subtracted from the current slow start threshold as the new slow start threshold. If the average value is equal to the current threshold, the slow start threshold remains unchanged.

[0033] Optionally, determining a new slow start threshold based on the change is specifically: Obtaining an average change rate and an average signal strength in the change situation; If the average signal strength is greater than the current signal strength, then if the average rate of change is less than zero, the slow start threshold is lowered, otherwise, the slow start threshold remains unchanged; If the average signal strength is less than or equal to the current signal strength, then if the average change rate is less than zero, the slow start threshold is kept unchanged; otherwise, the slow start threshold is increased.

[0034] Optionally, the real-time adjustment of the congestion window according to the signal strength is specifically: Calculate the probability of triggering fast retransmission under the current signal strength and the current congestion window based on historical data; The number of ACKs is determined according to the probability. If the probability is greater than the upper limit, the congestion window decreases by 1 for each ACK of the number of ACKs received. If the probability is less than the lower limit, the congestion window increases by 1 for each ACK of the number of ACKs received. Otherwise, the congestion window size remains unchanged.

[0035] Optionally, the triggering condition for the fast retransmission is: receiving three repeated ACKs in succession, or expiration of a timeout timer.

[0036] A third specific embodiment provides a computer program, wherein the computer program includes the following modules: The collection module is used for each meter to maintain a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and to collect signal strength at regular intervals; A slow start threshold adjustment module is used to calculate the average value and standard deviation of all values ​​in the queue when fast retransmission is triggered. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, a change in signal strength between the current moment and the last time fast retransmission was triggered is calculated, a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated; The data transmission module is used to adjust the congestion window to the slow start threshold, increase it to the average value in a linear increasing manner, and then adjust the congestion window in real time according to the signal strength.

[0037] The computer program provided in the third specific embodiment runs in the meter or the wireless module of the meter.

[0038] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0039] As another aspect, the present invention further provides a computer-readable medium, wherein the computer-readable medium carries one or more programs, and when the one or more programs are executed by a device or a processor, the method described in the first embodiment is implemented.

[0040] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A wireless meter control method, characterized in that: The method comprises the following steps: Each meter maintains a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and collects signal strength periodically; When fast retransmission is triggered, the average value and standard deviation of all values ​​in the queue are calculated. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, the signal strength change between the current time and the last time fast retransmission is triggered is calculated, and a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated. The congestion window is adjusted to the slow start threshold, and after increasing to the average value in a linear increasing manner, the congestion window is adjusted in real time according to the signal strength.

2. The method according to claim 1, characterized in that The new slow start threshold is calculated according to the slow start threshold and the average value, specifically: Calculate the ratio of the standard deviation to the average value, subtract the ratio from 1 as the adjustment factor, calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount according to the adjustment factor and the relative deviation; If the average value is greater than the current slow start threshold, the adjustment amount is added to the current slow start threshold as the new slow start threshold. If the average value is less than the current slow start threshold, the adjustment amount is subtracted from the current slow start threshold as the new slow start threshold. If the average value is equal to the current threshold, the slow start threshold remains unchanged.

3. The method according to claim 1, characterized in that The determining of a new slow start threshold based on the change is specifically: Obtaining an average change rate and an average signal strength in the change situation; If the average signal strength is greater than the current signal strength, then if the average rate of change is less than zero, the slow start threshold is lowered, otherwise, the slow start threshold remains unchanged; If the average signal strength is less than or equal to the current signal strength, then if the average change rate is less than zero, the slow start threshold is kept unchanged; otherwise, the slow start threshold is increased.

4. The method according to claim 1, characterized in that: The real-time adjustment of the congestion window according to the signal strength is specifically as follows: Calculate the probability of triggering fast retransmission under the current signal strength and the current congestion window based on historical data; The number of ACKs is determined according to the probability. If the probability is greater than the upper limit, the congestion window decreases by 1 for each ACK of the number of ACKs received. If the probability is less than the lower limit, the congestion window increases by 1 for each ACK of the number of ACKs received. Otherwise, the congestion window size remains unchanged.

5. The method according to claim 1, characterized in that The triggering condition of the fast retransmission is: receiving three repeated ACKs in succession, or the timeout timer expires.

6. A wireless meter control system, characterized in that: The system includes the following modules: The collection module is used for each meter to maintain a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and to collect signal strength at regular intervals; A slow start threshold adjustment module is used to calculate the average value and standard deviation of all values ​​in the queue when fast retransmission is triggered. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, a change in signal strength between the current moment and the last time fast retransmission was triggered is calculated, a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated; The data transmission module is used to adjust the congestion window to the slow start threshold, increase it to the average value in a linear increasing manner, and then adjust the congestion window in real time according to the signal strength.

7. The system according to claim 6, characterized in that The new slow start threshold is calculated according to the slow start threshold and the average value, specifically: Calculate the ratio of the standard deviation to the average value, subtract the ratio from 1 as the adjustment factor, calculate the relative deviation between the current slow start threshold and the average value, and calculate the actual adjustment amount according to the adjustment factor and the relative deviation; If the average value is greater than the current slow start threshold, the adjustment amount is added to the current slow start threshold as the new slow start threshold. If the average value is less than the current slow start threshold, the adjustment amount is subtracted from the current slow start threshold as the new slow start threshold. If the average value is equal to the current threshold, the slow start threshold remains unchanged.

8. The system according to claim 6, characterized in that The determining of a new slow start threshold based on the change is specifically: Obtaining an average change rate and an average signal strength in the change situation; If the average signal strength is greater than the current signal strength, then if the average rate of change is less than zero, the slow start threshold is lowered, otherwise, the slow start threshold remains unchanged; If the average signal strength is less than or equal to the current signal strength, then if the average change rate is less than zero, the slow start threshold is kept unchanged; otherwise, the slow start threshold is increased.

9. The system according to claim 6, characterized in that The real-time adjustment of the congestion window according to the signal strength is specifically as follows: Calculate the probability of triggering fast retransmission under the current signal strength and the current congestion window based on historical data; The number of ACKs is determined according to the probability. If the probability is greater than the upper limit, the congestion window decreases by 1 for each ACK of the number of ACKs received. If the probability is less than the lower limit, the congestion window increases by 1 for each ACK of the number of ACKs received. Otherwise, the congestion window size remains unchanged.

10. A computer program, characterized in that The computer program comprises the following modules: The collection module is used for each meter to maintain a slow start threshold, a queue of congestion window values ​​that have recently entered fast retransmission, and to collect signal strength at regular intervals; A slow start threshold adjustment module is used to calculate the average value and standard deviation of all values ​​in the queue when fast retransmission is triggered. If the standard deviation is less than one quarter of the average value, a new slow start threshold is calculated based on the slow start threshold and the average value. Otherwise, a change in signal strength between the current moment and the last time fast retransmission was triggered is calculated, a new slow start threshold is determined based on the change, and the slow start threshold maintained by the meter is updated; The data transmission module is used to adjust the congestion window to the slow start threshold, increase it to the average value in a linear increasing manner, and then adjust the congestion window in real time according to the signal strength.

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