Flow fluctuation prediction method and system for adaptive flow of wireless ad hoc network

Abstract

The invention belongs to the technical field of wireless ad hoc networks, and particularly relates to a flow fluctuation prediction method and system for adaptive flow of a wireless ad hoc network, and the method comprises the following steps: S1, carrying out the smoothing of the network flow of the ad hoc network through a constructed adaptive smoothing factor model, and obtaining the smoothed network flow Fn; s2, calculating a current cache data volume Bn; and S3, adaptively adjusting the current transmission rate to match the real-time data flow, so that the data volume in the cache region is kept balanced. The method has the advantages that stable and reliable transmission of traffic fluctuation complex services can be completed, and the real-time performance of transmission can also be achieved. On the basis that a common wireless self-organizing network product can meet simple services, a function of meeting complex flow transmission services by the wireless self-organizing network is added.

Description

Technical Field

[0001] The present application belongs to the technical field of wireless ad hoc networks, and specifically relates to a method and system for predicting flow fluctuations of adaptive flows in wireless ad hoc networks. Background Art

[0002] In wireless ad hoc network communications, existing wireless ad hoc networks directly use real-time traffic as the basis for adjusting transmission resources, which can only meet the traffic transmission of simple business needs (such as stable traffic business), and the main focus of work is on resource allocation. However, for the frequent and uncertain traffic fluctuations brought by complex business types, it is a great challenge to achieve fair resource allocation. There are many studies on adaptive flow in communication in the field of basic mobile communications, but in the field of wireless ad hoc network communications, there are not many related research and practice contents. Wireless ad hoc networks are distributed, peer-to-peer wireless communication network structures with transceiver functions that do not rely on central base stations. Wireless ad hoc networks are composed of multiple nodes with mobility and arbitrariness, which are completely different from basic mobile communication networks. The adaptive flow part in the field of wireless ad hoc network communications is very different from that in the field of basic mobile communications in terms of their respective infrastructure and application scenarios. Common products use real-time traffic as the basis for adjusting transmission resources, which can meet the traffic transmission of simple business needs (such as stable traffic business). However, for the frequent and uncertain traffic fluctuations brought about by complex business types, general solutions will fall into the situation of frequent adjustment of transmission resources, greatly wasting limited wireless ad hoc network resources on resource scheduling and adjustment, greatly reducing business transmission capabilities, or even failing to complete basic business transmission. Summary of the invention

[0003] The purpose of the present application is to provide a method and system for predicting traffic fluctuations of adaptive flows in wireless ad hoc networks, aiming to solve the technical problem that traditional wireless ad hoc network equipment cannot adapt to such increasingly complex market demands.

[0004] To achieve the above object, the present application proposes a method for predicting flow fluctuation of a wireless ad hoc network adaptive flow, comprising the following steps:

[0005] S1. Use the constructed adaptive smoothing factor model to smooth the network traffic of the ad hoc network and obtain the smoothed network traffic F n ;

[0006] S2. Calculate the current cache data volume B n ;

[0007] S3. Adaptively adjust the current transmission rate to match the real-time data flow, so that the amount of data in the buffer area remains balanced. Further preferably, in step S1, the formula of the adaptive smoothing factor model is as follows: α n =(en ·(fs)+s) 2

[0008] α n The constraints are:

[0009]

[0010] Deviation value e n The calculation formula is as follows:

[0011]

[0012] e n The constraints are:

[0013]

[0014] In the formula, f and s are exponential smoothing constants, e n is the deviation value;

[0015] Smoothed network traffic F n The calculation formula is as follows:

[0016] F n =α n ·R n +(1-α n )·F n-1

[0017] R n Current flow, F n-1 For historical traffic.

[0018] Further preferably, in step S2, the current cache data volume B n The calculation formula is as follows:

[0019] B n =B n-1 +T s ·R n -T s ·r n

[0020] B n The constraints are:

[0021]

[0022] Where, T s is the sampling time interval; r n is the transmission rate.

[0023] Further preferably, in step S3, at the initial stage of data transmission, there is no data in the cache area. As the data is transmitted, if the current transmission rate cannot meet the transmission requirements, the amount of cached data will increase; if the current transmission rate exceeds the transmission requirements, the amount of cached data will decrease until the cache area is cleared. When the amount of cached data is large, it is expected to keep the amount of cache data at a balanced value within a reasonable time.

[0024] Further preferably, in step S3, when the buffer area is maintained at the equilibrium value, the current transmission rate is expected to match the real-time data flow, and the current transmission capacity t is checked from the beginning of data transmission. n , characterized by the time required to clear the current buffer at the current transmission rate, and the calculation formula is as follows:

[0025]

[0026] When the current transmission capacity reaches the resource adjustment threshold, the expected transmission rate r' is calculated using the following formula:

[0027]

[0028] Where, T c Adjust the cost for resources, T max Adjust the expected threshold Max and T for resources l is the time value corresponding to the buffer balance value of the rate increase, T up Adjust the threshold value Up for the resource.

[0029] Further preferably, if the ratio of the current buffer data volume to the current transmission rate is less than 1, the expected transmission rate calculation formula is as follows:

[0030]

[0031] When the expected transmission rate does not meet the adjustment threshold, if the ratio of the current buffer data volume to the current transmission rate is greater than 1 and the expected transmission rate is greater than the current transmission rate, the transmission rate is also adjusted; if the buffer data volume exceeds the buffer setting value, the traffic stability condition is still not met. In order to avoid data loss due to buffer overflow, the transmission rate is adjusted to the current traffic prediction value.

[0032] Preferably, when increasing the transmission rate, the stability of the real-time traffic is first determined, and two consecutive deviation values ​​e n When the sum is less than 0.5, the real-time traffic is considered stable, and the adjustment threshold of the transmission rate is three consecutive deviation values ​​e n When the sum is less than 0.5, the traffic is stable; when the transmission rate is adjusted upward from the initial transmission rate, the adjustment threshold of the transmission rate is set to two consecutive deviation values ​​e nThe sum is less than 0.5; if the real-time flow is continuous T o If the time is not stable, then take T o The average of the real-time traffic within the time period is used as the smoothed traffic value to calculate the expected transmission rate.

[0033] Further preferably, when the buffer data is less than the balance value, if the duration T dowm When the duration buffer data is less than the equilibrium value, the expected transmission rate is calculated using the following formula:

[0034]

[0035] Among them, β is the deviation between the smoothed flow value and the current transmission rate, and the calculation formula is as follows:

[0036]

[0037] When the transmission rate is adjusted to decrease, the transmission rate is adjusted when the real-time traffic is stable. Here, three consecutive deviation values ​​e are set when the transmission rate decreases. n When the sum is less than 0.5, the flow is stable.

[0038] In addition, to achieve the above-mentioned purpose, the present invention also proposes a flow fluctuation prediction system for adaptive flow in wireless ad hoc network, comprising a data acquisition module, a data processing module and a data output module;

[0039] Data acquisition module: used to obtain data information;

[0040] Data storage module: set up data buffer for storing data;

[0041] Data processing module: used for data processing, setting resource adjustment indication flag Resource_adj_flag and timer Resource_adj_time;

[0042] Resource_adj_flag takes values ​​from 0 to 2. Resource_adj_flag is 0, indicating that the current transmission capacity needs to be checked. Resource_adj_flag is 1, indicating that the transmission rate needs to be adjusted. Resource_adj_flag is 2, indicating waiting for the rate to stabilize. The current transmission capacity is not checked during resource adjustment and resource stabilization.

[0043] The initial value of the timer Resource_sta_timer is N; the initial value of the counter w is 0;

[0044] Data output module: outputs processed data.

[0045] Further preferably, the resource adjustment indication flag Resource_adj_flag is used to indicate whether resource adjustment is required, and the timer Resource_adj_timer is used during resource adjustment;

[0046] If t n > T up , when the traffic is stable, calculate the expected transmission rate r', and when the traffic remains unstable for T o , also calculate the expected transmission rate r'. If the expected transmission rate r' is legal, set Resource_adj_flag to 1; start the timer Resource_adj_timer;

[0047] When the timer Resource_adj_timer counts down from M to 0, assign r' to r n , and set Resource_adj_flag to 2; stop the timer Resource_adj_timer, and start the timer Resource_sta_timer; when the timer Resource_sta_timer counts down from N to 0, set Resource_adj_flag to 0; stop the timer Resource_sta_timer;

[0048] If t n < T min , start the counter w++, and when w < Z, if t n > T min occurs, then stop the counter w and set it to 0. When w == Z, if t n is still less than T min , when the traffic is stable, calculate the expected transmission rate r'. If the expected transmission rate r' is legal, set Resource_adj_flag to 1, and stop the counter w; start the timer Resource_adj_timer;

[0049] When the timer Resource_adj_timer counts down from M to 0, assign r' to r n , and set Resource_adj_flag to 2; stop the timer Resource_adj_timer, and start the timer Resource_sta_timer; when the timer Resource_sta_timer counts down from N to 0, set Resource_adj_flag to 0; stop the timer Resource_sta_timer;

[0050] Z is the number of downsampling for the resource adjustment threshold, t n is the time required to empty the current buffer at the current transmission rate, Tup Adjust the threshold value Up for the resource, T min Adjust the desired threshold Min for the resource.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1) The real-time traffic data is processed in real time using an adaptive smoothing factor model and used as input for resource adjustment. The improved algorithm can adjust itself according to the speed of traffic trend changes. When the network traffic is stable, the smoothed network traffic is more in line with the real-time traffic; when the network traffic fluctuates greatly, the smoothed network traffic is more stable and reliable in trend changes.

[0053] 2) Add the buffer data volume parameter as an input parameter for resource adjustment. The buffer data volume and the real-time transmission rate can directly reflect the service transmission delay. Increasing this parameter can achieve real-time transmission.

[0054] 3) The integration of traffic smoothing algorithm and buffer area data volume parameters not only ensures the real-time transmission function of the service but also reduces the frequency of resource adjustment caused by traffic fluctuations, allowing the service to be transmitted stably.

[0055] 4) Real-time calculation and processing based on the statistical frequency of real-time traffic, without the risk of delayed resource adjustment due to increased processing.

[0056] 5) The computational complexity of this method is very small and has no effect on the time of time slot task processing under the same computer performance.

[0057] 6) Compared with the existing method of traffic transmission that only meets simple business needs, this design scheme enables complex business types with large and frequent traffic fluctuations to be flexibly and stably transmitted in the wireless ad hoc network system. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0059] Figure 1 An embodiment of the present application is a schematic diagram of the process of the present application.

[0060] Figure 2 It is a schematic diagram of real-time traffic and smooth traffic in one embodiment of the present application.

[0061] Figure 3 It is a schematic diagram of real-time traffic and expected transmission rate in one embodiment of the present application. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0064] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features limited to "first" and "second" may explicitly or implicitly include at least one of the features. In addition, if "and / or" or "and / or" appears in the full text, its meaning includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or solutions that satisfy both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0065] In wireless ad hoc network communications, existing wireless ad hoc networks directly use real-time traffic as the basis for adjusting transmission resources, which can only meet the traffic transmission needs of simple services (such as stable traffic services), and the main focus is on resource allocation. However, for the frequent and uncertain traffic fluctuations brought about by complex business types, it is a great challenge to achieve fair resource allocation.

[0066] Figure 1 As shown, a method for predicting flow fluctuation of a wireless ad hoc network adaptive flow includes the following steps:

[0067] S1. Use the constructed adaptive smoothing factor model to smooth the network traffic of the ad hoc network and obtain the smoothed network traffic F n .

[0068] In step S1: firstly, the network traffic is smoothed based on a moving average algorithm, which is based on Kaufman adaptive moving average. The calculation method of the improved smoothing factor is to use the traffic deviation value to predict and calculate the wireless ad hoc network traffic.

[0069] Smoothed network traffic F n is the current flow rate R n and historical flow F n-1 The calculation formula is as follows:

[0070] F n =α n ·R n +(1-α n )·F n-1

[0071] Among them, α n is the smoothing factor, 0≤α n ≤1. This method can adjust itself according to the speed of traffic trend change. When the network traffic is stable, the smoothed network traffic is more in line with the real-time traffic; when the network traffic fluctuates greatly, the smoothed network traffic is more stable and reliable in trend change. In the selection of smoothing factors, the deviation between the smoothed network traffic and the real-time traffic is used as the key parameter for constructing the smoothing factor. The deviation value e n The calculation formula is as follows:

[0072]

[0073] e n The constraints are:

[0074]

[0075] After that two exponential smoothing constants are calculated, which characterize the trend speed:

[0076]

[0077] The formula for the adaptive smoothing factor model is as follows:

[0078] α n =(e n ·(fs)+s) 2

[0079] α n The constraints are:

[0080]

[0081] S2. Current cache data volume B n The calculation formula is as follows:

[0082] Bn =B n-1 +T s ·R n -T s ·r n

[0083] B n The constraints are:

[0084]

[0085] S3. Adaptively adjust the current transmission rate to match the real-time data flow to keep the data volume in the cache balanced.

[0086] At the beginning of data transmission, there is no data in the buffer. As data is transmitted, if the current transmission rate cannot meet the transmission requirements, the amount of data in the buffer will increase; if the current transmission rate exceeds the transmission requirements, the amount of data in the buffer will decrease until the buffer is cleared. When the amount of buffered data is large, it is expected that the amount of data in the buffer will be kept at a balanced value within a reasonable time; when the buffer is kept at a balanced value, it is expected that the current transmission rate matches the real-time data traffic. View the current transmission capacity from the beginning of data transmission t n , characterized by the time required to clear the current buffer at the current transmission rate, and the calculation formula is as follows:

[0087]

[0088] When the current transmission capacity reaches the resource adjustment threshold, the expected transmission rate is calculated using the following formula:

[0089]

[0090] In this method, when adjusting the transmission rate, in order to ensure transmission performance, the transmission rate is increased quickly on demand; the transmission rate is decreased slowly and adaptively. To avoid frequent and small adjustments of the transmission rate, the transmission rate adjustment threshold is set to 20% of the current transmission rate according to the matching of the transmission capacity.

[0091] When increasing the transmission rate, first determine the stability of the real-time traffic. n When the sum is less than 0.5, the real-time traffic is considered stable, and the adjustment threshold of the transmission rate is three consecutive deviation values ​​e n When the sum is less than 0.5, the traffic is stable; however, in order to reduce the transmission delay caused by the mismatch of transmission capacity, when the transmission rate is adjusted upward from the initial transmission rate, the adjustment threshold of the transmission rate is set to two consecutive deviation values ​​e n The sum is less than 0.5; if the real-time traffic is not stable within the continuous To time, then take T oThe average of the real-time traffic within the time is used as the smoothed traffic value to calculate the expected transmission rate. In addition, in order to eliminate the influence of an extreme single large traffic value on the instability of the transmission rate, if the ratio of the current buffer data volume to the current transmission rate is less than 1, the expected transmission rate calculation formula is as follows:

[0092]

[0093] At the same time, in order to speed up the matching speed between transmission capacity and real-time traffic, when the expected transmission rate does not meet the adjustment threshold, if the ratio of the current buffer data volume to the current transmission rate is greater than 1 and the expected transmission rate is greater than the current transmission rate, the transmission rate is also adjusted. However, if the buffer data volume exceeds 60% of the maximum buffer value, the traffic stability condition is still not met. In order to avoid data loss caused by buffer overflow, the transmission rate is adjusted to the current traffic prediction value.

[0094] When the buffer data is less than the balance value, if it continues for T dowm When the duration buffer data is less than the equilibrium value, the expected transmission rate is calculated using the following formula:

[0095]

[0096] Among them, β is the deviation between the smoothed flow value and the current transmission rate, and the calculation formula is as follows:

[0097]

[0098] When the transmission rate is adjusted to decrease, the transmission rate is adjusted when the real-time traffic is stable. Here, three consecutive deviation values ​​e are set when the transmission rate decreases. n When the sum is less than 0.5, the flow is stable.

[0099] A flow fluctuation prediction system for adaptive flow in wireless ad hoc network, comprising a data acquisition module, a data processing module and a data output module;

[0100] Data acquisition module: used to obtain data information;

[0101] Data storage module: set up data buffer for storing data;

[0102] Data processing module: used for data processing, setting resource adjustment indication flag Resource_adj_flag and timer Resource_adj_time;

[0103] The value range of Resource_adj_flag is 0 to 2; when Resource_adj_flag is 0, it means that the current transmission capacity needs to be checked; when Resource_adj_flag is 1, it means that the transmission rate needs to be adjusted; when Resource_adj_flag is 2, it means waiting for the rate to stabilize; the current transmission capacity is not checked during the resource adjustment period and the resource stabilization period;

[0104] The initial value of the timer Resource_sta_timer is N; the initial value of the counter w is 0;

[0105] Data output module: Output the processed data.

[0106] The resource adjustment indication flag Resource_adj_flag is used to indicate whether resource adjustment is required, and the timer Resource_adj_timer is used during the resource adjustment period;

[0107] If t n > T up , when the traffic is stable, calculate the expected transmission rate r', and when the traffic remains unstable for T o , also calculate the expected transmission rate r'. If the expected transmission rate r' is legal, set Resource_adj_flag to 1; start the timer Resource_adj_timer;

[0108] When the timer Resource_adj_timer counts down from M to 0, assign r' to r n , and set Resource_adj_flag to 2; stop the timer Resource_adj_timer and start the timer Resource_sta_timer; when the timer Resource_sta_timer counts down from N to 0, set Resource_adj_flag to 0; stop the timer Resource_sta_timer;

[0109] If t n < T min , start the counter w++, and when w < Z, if t n > T min appears, then stop the counter w and set it to 0. When w == Z, if t n is still less than T min , when the traffic is stable, calculate the expected transmission rate r'. If the expected transmission rate r' is legal, set Resource_adj_flag to 1 and stop the counter w; start the timer Resource_adj_timer;

[0110] When the timer Resource_adj_timer decreases from M to 0, r' is assigned to r n , and set Resource_adj_flag to 2; turn off the timer Resource_adj_timer, and turn on the timer Resource_sta_timer; when the timer Resource_sta_timer decreases from N to 0, set Resource_adj_flag to 0; turn off the timer Resource_sta_timer;

[0111] Z is the number of resource adjustment threshold Down samples, t n The time required to clear the current buffer at the current transfer rate, T up Adjust the threshold value Up for the resource, T min Adjust the desired threshold Min for the resource.

[0112] Embodiment 1:

[0113] (1) Introduction to relevant parameters:

[0114] The resource adjustment indication flag Resource_adj_flag is used to indicate whether resources need to be adjusted. Resource_adj_flag takes values ​​of 0 to 2. Resource_adj_flag is 0, indicating that the current transmission capacity needs to be checked; Resource_adj_flag is 1, indicating that the transmission rate needs to be adjusted; Resource_adj_flag is 2, indicating waiting for the rate to stabilize. The current transmission capacity is not checked during resource adjustment and resource stabilization. The timer Resource_adj_timer is used during resource adjustment; the timer Resource_sta_timer is used during resource stabilization. The parameter and symbol table are shown in Table 1.

[0115] Table 1 Parameters and symbols

[0116]

[0117]

[0118] (2) The detailed implementation process is as follows:

[0119] Set the following parameters according to the scale of the ad hoc network and the device application scenario: Maximum cache capacity B max ; Resource adjustment cost T c ; Sampling time interval T s ; Rate stability overhead T j ; The rate rise buffer area balance value corresponds to the time value T l ; Resource adjustment threshold UpT up; Resource adjustment expected threshold MaxT max ; Resource adjustment expected threshold MinT min ; Resource adjustment threshold DownT down ; Traffic data unstable threshold T o ; Number of samples during resource adjustment Number of samples during rate stabilization Number of samples corresponding to the unstable threshold of traffic data Number of resource adjustment threshold Down samples

[0120] The initial parameters are as follows: initial transmission rate r0; initial cache data volume B0; initial smooth network traffic F0; initial resource adjustment indication flag Resource_adj_flag = 0; timer Resource_adj_timer initial value is M, timer Resource_sta_timer initial value is N; counter w initial value is 0; the method flow is shown in Table 2.

[0121] Table 2 Method flow chart

[0122]

[0123]

[0124] (3) The experimental results are as follows:

[0125] Here we use a segment of real-time traffic data to analyze this method. The horizontal axis in the figure is the number of sampling points, and the vertical axis is the corresponding traffic value, transmission rate, and buffer size within the sampling interval. The green line is the real-time traffic change curve, the black line is the smoothed traffic curve, the blue line is the real-time transmission rate curve, and the red line is the buffer data volume change curve. Figure 2 It can be seen that the algorithm can smooth the flow fluctuations of 0 to 13M, which can not only absorb instantaneous bursts to ensure stability, but also fit the trend of point distribution well to meet the timeliness. Figure 3 It can be seen that the initial data transmission rate is small. As the traffic is input, the amount of data in the buffer area increases, and the transmission rate increases adaptively. As the transmission rate increases to meet the transmission demand, the amount of data in the buffer area begins to decrease until the amount of data in the buffer area is less than the equilibrium value. Then, according to the transmission rate and the transmission demand, the transmission rate changes adaptively until the transmission rate matches the transmission demand.

[0126] from Figure 3As can be seen in the figure, the transmission rate will increase from the initial transmission rate to the transmission rate that reduces the amount of data accumulated in the buffer at a low rate to the equilibrium value, and then the transmission rate will adaptively maintain the size that matches the transmission demand while the buffer maintains the equilibrium value. Figure 3 It can be seen that the maximum data volume in the cache is less than 7M, which does not exceed the maximum value of the cache, that is, the cache overflow packet loss caused by the transmission capacity is avoided; and after the transmission rate is stable, the data volume in the cache remains near the equilibrium value, that is, the data transmission delay is very small, close to real-time transmission. In addition, the initial rate of the node is small, and then it is adaptively adjusted according to the transmission demand, which well ensures high resource utilization.

[0127] The adaptive flow traffic fluctuation prediction and evaluation method and its application proposed in this paper can not only complete the stable and reliable transmission of complex traffic fluctuation services, but also realize the real-time transmission. On the basis of the common wireless self-organizing network products that can meet simple services, the wireless self-organizing network is added to meet the complex traffic transmission business function.

[0128] Although the embodiments of the present application have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for predicting flow fluctuation of wireless ad hoc network adaptive flow, characterized in that: The following steps are involved: S1. Use the constructed adaptive smoothing factor model to smooth the network traffic of the ad hoc network and obtain the smoothed network traffic F n ; S2. Calculate the current cache data volume B n ; S3. Adaptively adjust the current transmission rate to match the real-time data flow to keep the data volume in the cache balanced.

2. The method for predicting flow fluctuation of wireless ad hoc network adaptive flow according to claim 1, characterized in that: In step S1, the formula of the adaptive smoothing factor model is as follows: a n =(e n ·(fs)+s) 2 α n The constraints are: Deviation value e n The calculation formula is as follows: e n The constraints are: In the formula, f and s are exponential smoothing constants, e n is the deviation value; Smoothed network traffic F n The calculation formula is as follows: F n =a n ·R n +(1-a n )·F n-1 R n Current flow, F n-1 For historical traffic.

3. The method for predicting flow fluctuation of wireless ad hoc network adaptive flow according to claim 2, characterized in that: In step S2, the current cache data volume B n The calculation formula is as follows: B n =B n-1 +T s ·R n -T s ·r n B n The constraints are: Where, T s is the sampling time interval; r n is the transmission rate.

4. The method for predicting flow fluctuation of wireless ad hoc network adaptive flow according to claim 1, characterized in that: In step S3, at the initial stage of data transmission, there is no data in the cache area. As the data is transmitted, if the current transmission rate cannot meet the transmission requirements, the amount of cached data will increase; if the current transmission rate exceeds the transmission requirements, the amount of cached data will decrease until the cache area is cleared; when the amount of cached data is large, it is expected to keep the amount of cached data at a balanced value within a reasonable time.

5. The method for predicting flow fluctuation of wireless ad hoc network adaptive flow according to claim 3, characterized in that: In step S3, when the buffer area is maintained at the equilibrium value, the current transmission rate is expected to match the real-time data flow, and the current transmission capacity t is checked from the beginning of data transmission. n , characterized by the time required to clear the current buffer at the current transmission rate, and the calculation formula is as follows: When the current transmission capacity reaches the resource adjustment threshold, the expected transmission rate r' is calculated using the following formula: Where, T c Adjust the cost for resources, T max Adjust the expected threshold Max and T for resources l is the time value corresponding to the buffer balance value of the rate increase, T up Adjust the threshold value Up for the resource.

6. The method for predicting flow fluctuation of wireless ad hoc network adaptive flow according to claim 5, characterized in that: If the ratio of the current buffer data volume to the current transmission rate is less than 1, the expected transmission rate is calculated as follows: When the expected transmission rate does not meet the adjustment threshold, if the ratio of the current buffer data volume to the current transmission rate is greater than 1 and the expected transmission rate is greater than the current transmission rate, the transmission rate is also adjusted; If the amount of data in the cache exceeds the cache setting value, the flow stability condition is still not met. In order to avoid data loss caused by cache overflow, the transmission rate is adjusted to the current flow prediction value.

7. The method for predicting flow fluctuation of wireless ad hoc network adaptive flow according to claim 5, characterized in that: When increasing the transmission rate, first determine the stability of the real-time traffic. n When the sum is less than 0.5, the real-time traffic is considered stable, and the adjustment threshold of the transmission rate is three consecutive deviation values ​​e n When the sum is less than 0.5, the traffic is stable; when the transmission rate is adjusted upward from the initial transmission rate, the adjustment threshold of the transmission rate is set to two consecutive deviation values ​​e n The sum is less than 0.5; if the real-time flow is continuous T o If there is no stability in the time, then take T o The average of the real-time traffic within the time period is used as the smoothed traffic value to calculate the expected transmission rate.

8. The method for predicting flow fluctuation of wireless ad hoc network adaptive flow according to claim 5, characterized in that: When the buffer data is less than the balance value, if it continues for T dowm When the duration buffer data is less than the equilibrium value, the expected transmission rate is calculated using the following formula: Among them, β is the deviation between the smoothed flow value and the current transmission rate, and the calculation formula is as follows: When the transmission rate is adjusted to decrease, the transmission rate is adjusted when the real-time traffic is stable. Here, three consecutive deviation values ​​e are set when the transmission rate decreases. n When the sum is less than 0.5, the flow is stable.

9. A traffic fluctuation prediction system for adaptive flow in wireless ad hoc network, which is deployed by using the traffic fluctuation prediction and evaluation method for adaptive flow in wireless ad hoc network as claimed in any one of claims 1 to 8, characterized in that: It includes a data acquisition module, a data processing module and a data output module; Data acquisition module: used to obtain data information; Data storage module: set up data buffer for storing data; Data processing module: used for data processing, setting resource adjustment indication flag Resource_adj_flag and timer Resource_adj_time; Resource_adj_flag takes values ​​from 0 to 2. Resource_adj_flag is 0, indicating that the current transmission capacity needs to be checked. Resource_adj_flag is 1, indicating that the transmission rate needs to be adjusted. Resource_adj_flag is 2, indicating waiting for the rate to stabilize. The current transmission capacity is not checked during resource adjustment and resource stabilization. The initial value of the timer Resource_sta_timer is N; the initial value of the counter w is 0; Data output module: outputs processed data.

10. The flow fluctuation prediction system for adaptive flow in wireless ad hoc network according to claim 9, characterized in that: The resource adjustment indication flag Resource_adj_flag is used to indicate whether resources need to be adjusted, and the timer Resource_adj_timer is used during resource adjustment; If n >T up , calculate the expected transmission rate r' when the flow is stable, and the flow is continuously unstable T o The expected transmission rate r' is also calculated. If the expected transmission rate r' is legal, Resource_adj_flag is set to 1; the timer Resource_adj_timer is started; When the timer Resource_adj_timer decreases from M to 0, r' is assigned to r n , and set Resource_adj_flag to 2; turn off the timer Resource_adj_timer and turn on the timer Resource_sta_timer; When the timer Resource_sta_timer decreases from N to 0, set Resource_adj_flag to 0; turn off the timer Resource_sta_timer; If t n <T min , start the counter w++, when w < Z, if t n >T min , then close the counter w and set it to 0, when w = Z, if t n is still less than T min , calculate the expected transmission rate r' when the traffic is stable, if the expected transmission rate r' is legal, set Resource_adj_flag to 1, close the counter w; start the timer Resource_adj_timer; When the timer Resource_adj_timer decreases from M to 0, r' is assigned to r n , and set Resource_adj_flag to 2; turn off the timer Resource_adj_timer and turn on the timer Resource_sta_timer; When the timer Resource_sta_timer decreases from N to 0, Resource_adj_flag is set to 0; Close the timer Resource_sta_timer; Z is the number of resource adjustment threshold Down samples, t n The time required to clear the current buffer at the current transfer rate, T up Adjust the threshold value Up for the resource, T min Adjust the desired threshold Min for the resource.

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