CN115174405A - Bandwidth allocation method based on ARIMA statistical model - Google Patents
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0896—Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities
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- H—ELECTRICITY
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- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0823—Errors, e.g. transmission errors
- H04L43/0829—Packet loss
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0876—Network utilisation, e.g. volume of load or congestion level
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Abstract
The invention discloses a bandwidth allocation method based on an ARIMA statistical model, which is based on a network framework of an SDN and utilizes the characteristic of separation of a control plane and a data forwarding plane to flexibly control the bandwidth use of the data plane through the control plane. And acquiring a bandwidth data set Oboe of the ABR video stream from Github, constructing an SDN network experiment platform, simulating the actual bandwidth use condition, and measuring the bandwidth use condition. According to the measured historical bandwidth, predicting the use requirement of future bandwidth by using an ARIMA statistical model, setting an adjustment coefficient to adjust the bandwidth utilization rate and the packet loss rate, and distributing the bandwidth according to the adjustment result. According to the prediction of the ARIMA statistical model, the method can improve the bandwidth utilization rate under the condition of ensuring the transmission quality.
Description
Technical Field
The invention belongs to the field of computer networks, and particularly relates to a bandwidth allocation method based on an ARIMA statistical model.
Background
With the development of the internet, new types of network applications and services (e.g., web surfing, audio, video conferencing and streaming media, online gaming, e-commerce, etc.) have emerged to end users. These applications and services may generate their own feature streams that need to be delivered over the network. However, all of these applications require different processing of their own streams for successful delivery over the network. For example, some applications such as video conferencing require some bandwidth to transmit traffic and are sensitive to packet loss. In the traditional method for allocating static bandwidth in network, the utilization rate of bandwidth is lower under the condition of ensuring transmission quality.
Disclosure of Invention
In view of the above-mentioned drawbacks and disadvantages of the prior art, an object of the present invention is to provide a bandwidth allocation method based on ARIMA model.
In order to achieve the purpose, the invention adopts the following technical scheme:
a bandwidth allocation method based on an ARIMA model is characterized by comprising the following steps:
step 1: acquiring a bandwidth data set Oboe of the ABR video stream from Github, dividing the data set into a training set and a testing set, and determining parameters of an ARIMA model from the training set;
and 2, step: and (4) constructing an SDN network experiment platform, and connecting a switch in a data plane and a controller in a control plane. The controller sends a port state request message to the switch, and the switch sends the port state message to the controller after receiving the port state request message.
And step 3: and calculating the used bandwidth of the port by using the port state information obtained in the step 2.
And 4, step 4: and taking a switch port connected with the user host as an object, recording the used bandwidth, and predicting the bandwidth use requirement of the next time period by using an ARIMA model. And setting an adjustment coefficient, adjusting the bandwidth utilization rate and the packet loss rate of the prediction value of the ARIMA model, and distributing the bandwidth according to the adjusted final value.
According to the invention, the setting and adjusting coefficient in the step 4 adjusts the bandwidth utilization rate and the packet loss rate, if the bandwidth utilization rate needs to be improved, the coefficient should be less than 1, the smaller the coefficient is, the higher the bandwidth utilization rate is, but the packet loss rate is increased; if the packet loss rate needs to be reduced, the coefficient should be greater than 1, and the larger the coefficient, the lower the packet loss rate, but the bandwidth utilization rate will be reduced.
Specifically, the switch is an OpenFlow switch, and the bandwidth use requirement of the object, namely the ABR video stream, is predicted.
Further, the prediction is performed by using an ARIMA model, which specifically comprises:
searching parameters p, d, q, n which enable the AIC = -2ln (L) +2k (akage pool information content) to be the minimum in a training set of a VBR video stream bandwidth data set; wherein p is an autocorrelation coefficient, d is a difference coefficient, q is a partial correlation coefficient, n is the length of a bandwidth time sequence, k is the number of unknown parameters in the model, and L is a maximum likelihood function value likelihood function in the model;
and running an ARIMA model on the controller for determining parameters, recording the bandwidth utilization data, and predicting the bandwidth of the next period by using the ARIMA model when the recorded bandwidth data is equal to n.
Preferably, local iterations of the process are predicted. Recording the bandwidth of use b for n consecutive periods at the beginning of the prediction process 1 ,b 2 ,b 3 ,...,b n And then calling an ARIMA model to predict the bandwidth utilization requirement b of the next period n+1 (ii) a Then using { b 2 ,b 3 ,b 4 ,...,b n+1 Replace { b } 1 ,b 2 ,b 3 ,...,b n Predicting the bandwidth utilization requirement b of the next period n+2 . And repeating the process, and carrying out local iteration until the transmission task is completed.
Further preferably, the topology structure of the SDN network includes 1 RYU controller, 5 OpenFlow switches, and 5 hosts.
The bandwidth allocation method based on the ARIMA model utilizes the characteristic that the control plane and the data forwarding plane are separated, flexibly controls the bandwidth usage of the data plane through the control plane, predicts the bandwidth usage requirement of the next period by using the ARIMA model after recording the bandwidth usage of n periods, finally allocates the bandwidth according to the adjusted final value after adjusting the bandwidth usage and the packet loss rate of the predicted value, and improves the bandwidth usage rate on the premise of ensuring the transmission quality.
Drawings
Fig. 1 is a schematic diagram of bandwidth prediction and allocation under an SDN network architecture according to an embodiment;
figure 2 is a schematic diagram of an SDN network topology;
FIG. 3 is a graph of the prediction results of the ARIMA model;
FIG. 4 is a diagram of the prediction result after adjustment by the adjustment factor;
FIG. 5 is an illustration of adjustment coefficients;
fig. 6 is a comparison of the results of bandwidth allocation and static bandwidth allocation predicted according to the ARIMA model.
The invention will be explained and explained in more detail below with reference to the figures and exemplary embodiments.
Detailed Description
In the SDN network architecture proposed in recent years, by decoupling the control plane and the data plane, the limitation of the conventional network architecture is overcome, and the manageability, expandability, controllability, dynamics and flexibility of the network are greatly improved. The applicant provides a bandwidth allocation method based on an ARIMA statistical model on the basis of summarizing the structure and the working principle of an SDN network. The method uses an ARIMA statistical model to predict future bandwidth use requirements, adjusts the bandwidth utilization rate and the packet loss rate of a prediction result, and then allocates bandwidth to application according to the adjustment result. In addition, the feasibility of the method is verified on an actual SDN network experimental platform built by using the OpenFlow switch.
The embodiment provides a bandwidth allocation method based on an ARIMA model, which comprises the following steps:
step 1: acquiring a bandwidth data set Oboe of an ABR video stream, dividing the data set into a test set and a training set, and determining parameters of an ARIMA model in the training set, namely, the parameters which enable AIC = -2ln (L) +2k to be the minimum, wherein the minimum parameters comprise p (autocorrelation coefficient), d (difference coefficient), q (partial correlation coefficient), n (length of a bandwidth time sequence), k is the number of unknown parameters in the model, and L is a maximum likelihood function value likelihood function in the model;
and 3, operating the RYU controller, connecting the switch in the SDN network topology structure built in the step 2 with a remote controller, then collecting the state of the switch port by using a port state request message on a data plane, and collecting the use condition of the bandwidth. The port state contains a number of entries including, the number of packets received, the number of packets transmitted, the number of bytes received, the number of bytes transmitted, the number of packets discarded by RX, the number of packets discarded by TX, the number of errors received, the number of errors transmitted, and so forth. The invention focuses on the received byte number and the transmitted byte number, and the byte number transmitted at the beginning of a period is subtracted from the byte number transmitted at the end of the period to obtain the byte number transmitted in the period, and the used bandwidth of the period can be obtained through conversion.
And 4, step 4: and (3) when the bandwidth time sequence acquired in the step (3) is equal to n, inputting the time bandwidth sequence into an ARIMA model with determined parameters, and predicting to obtain the use bandwidth requirement of the next period.
And 5: and (5) adjusting the bandwidth utilization rate and the packet loss rate coefficient of the prediction result obtained in the step (4) to obtain a final prediction result.
Step 6: and allocating the use bandwidth of the next period according to the final prediction result obtained in the step 5.
The following are specific experimental examples given by the inventors.
Experimental example:
as shown in fig. 1, under the SDN network architecture, a bandwidth allocation method based on ARIMA model is implemented, which includes the following steps:
step 1: acquiring a bandwidth data set Oboe of an ABR video stream, dividing the data set into a test set and a training set, and determining parameters of an ARIMA model in the training set, namely the parameters with the minimum value in AIC = -2ln (L) +2k, wherein the parameters comprise p (autocorrelation coefficient), d (difference coefficient), q (partial correlation coefficient), n (length of a bandwidth time sequence), k is the number of unknown parameters in the model, and L is a maximum likelihood function value likelihood function in the model.
and 3, operating the RYU controller, setting the ip of the switch controller to be 192.168.1.224, the port number to be 6653, the connection mode to be TCP connection, setting the used OpenFlow protocol to be OpenFlow1.3, and then connecting the RYU controller on the department of science V530-48T4X in the step 2.
And 4, step 4: the iperf program is operated in a server mode on one computer with an Ubuntu 18.04.5LTS system and a CPU (Central processing Unit) of Intel i5 7800H @2.5GHz, and the iperf program is operated in a client mode on the other computer with an Ubuntu 18.04.5LTS system and a CPU of Intel i5 7800H @2.5 GHz. And (3) transmitting data to the iperf server side on the client side of the iperf by using the bandwidth data in the test set in the step 1.
And 5: the controller sends a port state request message to collect the state of the switch port. Recording the number of received bytes and the number of transmitted bytes at the beginning of the cycle, recording the number of transmitted bytes and the number of received bytes at the end of the cycle, calculating the use bandwidth of one cycle, and recording the use bandwidth of one cycle according to the time sequence.
Step 6: the bandwidth-used data collected in step 3 is equal to n, i.e. the bandwidth data is { b } 1 ,b 2 ,b 3 ,...,b n And (4) inputting the time bandwidth sequence into an ARIMA model with determined parameters, and predicting the use bandwidth requirement of the next period.
And 7: and (4) adjusting the bandwidth utilization rate and the packet loss rate coefficient of the prediction result obtained in the step (6) to obtain a final prediction result. As shown in fig. 5, the adjustment coefficient adjusts the bandwidth utilization rate and the packet loss rate, if the bandwidth utilization rate needs to be increased, the coefficient should be less than 1, and the smaller the coefficient is, the higher the bandwidth utilization rate is, but the packet loss rate will increase; if the packet loss rate needs to be reduced, the coefficient should be greater than 1, and the larger the coefficient, the lower the packet loss rate, but the bandwidth utilization rate will be reduced. According to data measured by multiple experiments, the prediction error fluctuates about 5%, but within 10%, in order to ensure the transmission quality, the adjustment coefficient in the experiment is 1.1, namely, the allocated bandwidth is increased by 10% on the prediction result of the ARIMA model.
And step 8: and allocating the use bandwidth of the next period according to the final prediction result obtained in the step 7.
And step 9: record the bandwidth used in the next cycle, bn +1, by { b } 2 ,b 3 ,b 4 ,...,b n+1 Replace { b ] in step 6 1 ,b 2 ,b 3 ,...,b n Predicting the bandwidth b used in the next period n+2 Then, step 6 to step 9 are repeated.
And repeating the process until the transmission task of the step 4 is completed.
And recording the bandwidth predicted value and the actual bandwidth utilization value of the ARIMA model, and drawing a graph, wherein as shown in FIG. 3, the No. 1 broken line is the bandwidth utilization value, and the No. 2 broken line is the bandwidth predicted value of the ARIMA model.
And recording the bandwidth predicted value and the actual bandwidth utilization value which are adjusted by the adjustment coefficient, and drawing a graph, wherein as shown in fig. 4, the No. 1 broken line is the bandwidth utilization value, and the No. 2 broken line is the bandwidth predicted value which is adjusted by the adjustment coefficient. As described in step 7, the adjustment coefficient in this experiment is 1.1, which is greater than 1, the packet loss rate is reduced, the transmission quality is guaranteed, but the bandwidth utilization rate is also reduced.
Fig. 6 is a comparison graph of the results of bandwidth allocation and static bandwidth allocation predicted by the ARIMA model, as shown in the figure, under the condition of the same packet loss ratio, that is, the same transmission quality, the bandwidth allocation predicted by the ARIMA model of this embodiment is 10.7% higher than the bandwidth utilization ratio of the static bandwidth allocation.
The preferred embodiments have been described in detail with reference to the accompanying drawings, however, the present invention is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present invention, and these simple modifications are included in the protection scope of the present disclosure.
It should be noted that the technical features described in the above embodiments may be combined in any suitable manner without contradiction, and various possible combinations are not described again to avoid unnecessary repetition.
Claims (6)
1. A bandwidth allocation method based on an ARIMA statistical model is characterized by comprising the following steps:
step 1: acquiring a bandwidth data set Oboe of the ABR video stream from Github, dividing the data set into a training set and a testing set, and determining parameters of an ARIMA statistical model from the training set;
step 2: an SDN network experiment platform is built, and a switch in a data plane and a controller in a control plane are connected; the controller sends a port state request message to the switch, and the switch sends the port state message to the controller after receiving the port state request message;
and step 3: calculating the use bandwidth of the port by using the port state information obtained in the step 2;
and 4, step 4: taking a switch port connected with a user host as an object, recording the used bandwidth, and predicting the bandwidth use requirement of the next time period by using an ARIMA statistical model; and setting an adjustment coefficient, adjusting the bandwidth utilization rate and the packet loss rate of the prediction value of the ARIMA statistical model, and distributing the bandwidth according to the adjusted final value.
2. The method according to claim 1, wherein the bandwidth utilization ratio and the packet loss ratio are adjusted in the setting of the adjustment coefficient in step 4, if the bandwidth utilization ratio needs to be increased, the coefficient should be less than 1, and the smaller the coefficient, the higher the bandwidth utilization ratio, but the packet loss ratio will be increased; if the packet loss rate needs to be reduced, the coefficient should be greater than 1, and the larger the coefficient is, the lower the packet loss rate is, but the bandwidth utilization rate will be reduced.
3. The method of claim 1, wherein the switch is an OpenFlow switch and the predicted object is a bandwidth usage requirement of an ABR video stream.
4. The method according to claim 1 or 2, wherein the predicting using the ARIMA statistical model comprises:
searching a parameter p, d, q, n which enables AIC = -2ln (L) +2k to be the minimum from a training set of a VBR video stream bandwidth data set; wherein p is an autocorrelation coefficient, d is a difference coefficient, q is a partial correlation coefficient, n is the length of a bandwidth time sequence, k is the number of unknown parameters in the model, and L is a likelihood function of a maximum likelihood function value in the model;
and running an ARIMA statistical model for determining parameters on the controller, recording the bandwidth utilization data, and predicting the bandwidth of the next period by using the ARIMA model when the recorded bandwidth data is equal to n.
5. The method of claim 1, wherein the prediction process selects a local iteration that records the bandwidth of use { b } for n consecutive cycles at the beginning of the prediction process 1 ,b 2 ,b 3 ,...,b n And then calling an ARIMA statistical model to predict the bandwidth utilization requirement b of the next period n+1 (ii) a Then using { b 2 ,b 3 ,b 4 ,...,b n+1 H instead of b 1 ,b 2 ,b 3 ,...,b n H, predicting the bandwidth demand b of the next cycle n+2 (ii) a And repeating the process, and carrying out local iteration until the transmission task is completed.
6. The method of claim 1, wherein the topology of the SDN network comprises 1 RYU controller, 5 OpenFlow switches, and 5 hosts.
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