CN109831315B - Capacity expansion prediction method and device for network traffic - Google Patents
Capacity expansion prediction method and device for network traffic Download PDFInfo
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Abstract
Embodiments of the present invention provide a method and an apparatus for predicting capacity expansion of network traffic, which can implement accurate capacity expansion prediction through a large amount of data sampled at high frequency. The method comprises the following steps: the monitoring equipment samples the network flow at a preset sampling frequency to acquire link data; converting the link flow of the link corresponding to any link identification ID into a relative value of the link flow; in a preset time period, if the relative value of the link flow at any sampling moment is greater than a first threshold value, recording the link flow of the link corresponding to any link identification ID at any sampling moment as an accumulation value; the monitoring equipment is according to the formula
Converting the accumulation value in a preset time period into an expansion preparation value, and resetting the accumulation value; and when the capacity expansion preparation value exceeds a second threshold value, issuing a capacity expansion forecast to a network manager or a network controller.
Description
Technical Field
The embodiment of the invention relates to the field of communication, in particular to a method and a device for capacity expansion prediction of network traffic.
Background
Monitoring of a network is being transformed from a low-frequency sampling monitoring method represented by a Simple Network Management Protocol (SNMP) to a high-frequency sampling monitoring method represented by telemetry (telemanagement). Most of the conventional network monitoring modes are that a collector acquires monitoring data through a pull mode (pull mode), and the data sampling frequency is relatively low, and the data is generally sampled once every 5 minutes. Telemetrology is a remote technique for collecting data from physical or virtual devices at high speed. The device actively sends the data information of the device to the collector through a push mode (push mode), and a real-time and high-speed data acquisition function is provided. The high frequency sampling technique represented by telemetrology can realize a high frequency sampling technique at intervals of 0.1 second, 1 second, 5 seconds, 10 seconds, and the like. the telemetrology device comprises a collector, an analyzer, and a controller, wherein the collector and the analyzer are often merged into a network controller or a network manager.
In a traditional network, based on a monitoring mode of low-frequency sampling such as SNMP and the like, equipment reports the link rate including the average flow and the peak flow of the link every 5 minutes. The capacity expansion forecast of the traditional network is based on that the average flow of the network in 24 hours exceeds a certain threshold value, or the peak flow exceeds a certain threshold value in 24 hours. Because the low-frequency sampling can not completely reflect the link flow condition, the expansion prediction based on the average flow over-threshold value smoothes a plurality of micro-burst phenomena in the network, and therefore the micro-burst flow over-threshold value can not be reflected. The maximum value of the micro burst can be obtained based on the capacity expansion forecast that the peak flow exceeds the threshold, but the average flow of the network is possibly low, and the capacity expansion is completed in advance when the network flow is low, so that the waste of equipment performance and investment is caused. After technologies such as telemetrology are used, an analyzer obtains a large amount of high-frequency sampling performance data of a link, the conventional mode that the average rate exceeds the threshold or the peak rate exceeds the threshold still brings about the same problem as the mode that the capacity expansion prediction is realized by using a low-frequency sampling monitoring mode such as SNMP, and the accurate capacity expansion prediction cannot be realized through a large amount of high-frequency sampling data.
Disclosure of Invention
Embodiments of the present invention provide a method and an apparatus for predicting capacity expansion of network traffic, which can implement accurate capacity expansion prediction through a large amount of data sampled at high frequency.
In a first aspect, a method for providing a capacity expansion forecast of network traffic includes the following steps: the method comprises the steps that network traffic is sampled by monitoring equipment at a preset sampling frequency, and link data are obtained, wherein the link data comprise sampling time, a link identification ID and link traffic of a link corresponding to the link identification ID; the predetermined sampling frequency is greater than a frequency threshold; the monitoring equipment converts link traffic of a link corresponding to any link identification ID into a relative value of the link traffic, wherein the relative value of the link traffic is the link traffic/bandwidth value of the link corresponding to the link identification ID; in a preset time period, if the relative value of the link flow at any sampling moment is greater than a first threshold value, recording the link flow of the link corresponding to any link identification ID at any sampling moment as an accumulation value; the monitoring device is based on a formula
Converting the accumulated value in the predetermined time period into a capacity expansion preparation value, and converting the accumulated value into a capacity expansion preparation valueClearing the accumulation value; wherein, a represents the accumulation value, EP represents a capacity expansion preparation value calculated for a predetermined time period before the predetermined time period, EP represents the capacity expansion preparation value corresponding to the predetermined time period, and n represents a conversion coefficient for converting the accumulation value a into the capacity expansion preparation value EP; and when the capacity expansion preparation value exceeds a second threshold value, issuing a capacity expansion forecast to a network manager or a network controller, wherein the capacity expansion forecast comprises forecast time, a forecast link identifier ID, a capacity expansion preparation value and a forecast capacity expansion state, and the forecast time is the last time of the preset time period or any time after the last time.
In the above scheme, since the network traffic can be sampled by adopting the predetermined sampling frequency greater than the frequency threshold, the link traffic of the link corresponding to any link identifier ID is converted into the relative value of the link traffic; in a preset time period, if the relative value of the link flow at any sampling moment is greater than a first threshold value, recording the link flow of the link corresponding to any link identification ID at any sampling moment as an accumulation value; the monitoring equipment is according to the formula
Converting the accumulation value in a preset time period into an expansion preparation value, and resetting the accumulation value; and when the capacity expansion preparation value exceeds a second threshold value, issuing a capacity expansion forecast to a network manager or a network controller. A large amount of sampled data can be processed in the case of a network configured with a high frequency sampling mechanism, and the processing mechanism through the two thresholds is responsive to both smooth and micro-bursty network traffic. And because the conversion of the accumulation value and the capacity expansion preparation value converts a large amount of sampling data of the whole network into capacity expansion decision data with decisive significance, and the capacity expansion prompt is automatically generated in the network with high-frequency sampling, the labor cost is reduced, the accuracy of a capacity expansion time point is effectively improved, the actual utilization rate of a network link is improved under the condition of not influencing the user experience, and the investment of network capacity expansion is saved.
In a second aspect, a capacity expansion forecasting device for network traffic is provided, including: a sampling module for sampling the network traffic at a predetermined sampling frequency,acquiring link data, wherein the link data comprises sampling time, a link identification ID and link flow of a link corresponding to the link identification ID; the predetermined sampling frequency is greater than a frequency threshold; a conversion module, configured to convert link traffic of a link corresponding to any one of the link identifiers ID sampled by the sampling module into a relative value of the link traffic, where the relative value of the link traffic is equal to the link traffic/bandwidth value of the link corresponding to the link identifier ID; a recording module, configured to record, in a predetermined time period, link traffic of a link corresponding to any one of the link identifiers ID at any one of the sampling times as an accumulated value if a relative value of the link traffic, which is obtained by conversion by the conversion module at any one of the sampling times, is greater than a first threshold value; a calculation module for calculating according to a formula
Converting the accumulation value recorded by the recording module in the preset time period into an expansion preparation value, and clearing the accumulation value; wherein, a represents the accumulation value, EP represents a capacity expansion preparation value calculated for a predetermined time period before the predetermined time period, EP represents the capacity expansion preparation value corresponding to the predetermined time period, and n represents a conversion coefficient for converting the accumulation value a into the capacity expansion preparation value EP; and the sending module is used for issuing a capacity expansion forecast to a network manager or a network controller when the capacity expansion preparation value calculated by the calculating module exceeds a second threshold, wherein the capacity expansion forecast comprises forecast time, a forecast link Identifier (ID), a capacity expansion preparation value and a forecast capacity expansion state, and the forecast time is the last time of the preset time period or any time after the last time.
In a third aspect, a capacity expansion forecasting device for network traffic is provided, which includes a communication interface, a processor, a memory, and a bus; the processor is connected with the memory through a bus, and when the capacity expansion forecasting device of the network traffic runs, the processor executes the computer execution instruction stored in the memory, so that the capacity expansion forecasting device of the network traffic executes the capacity expansion forecasting method of the network traffic.
In a fourth aspect, a computer storage medium is provided, which includes instructions, and is characterized in that when the instructions are executed on a computer, the instructions cause the computer to execute the capacity expansion forecasting method for network traffic as described above.
In a fifth aspect, a computer program product is provided, which includes instruction codes for executing the method for capacity expansion forecasting of network traffic as described above.
It can be understood that any one of the provided expansion forecasting devices, computer storage media, or computer program products of the network traffic is used to execute the method corresponding to the first aspect provided above, so that the beneficial effects that can be achieved by the expansion forecasting devices of the network traffic may refer to the beneficial effects of the method of the first aspect and the corresponding solutions in the following specific embodiments, and are not described herein again.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic diagram of a topology information structure of a whole network according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a method for predicting capacity expansion of network traffic according to an embodiment of the present invention;
fig. 3 is a schematic diagram illustrating a method for predicting capacity expansion of network traffic according to another embodiment of the present invention;
fig. 4 is a schematic diagram of a capacity expansion forecasting device of network traffic according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a capacity expansion forecasting device of network traffic according to another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The capacity expansion forecast of the traditional network is based on that the average flow of the network in 24 hours exceeds a certain threshold value, or the peak flow exceeds a certain threshold value in 24 hours. Because the low-frequency sampling can not completely reflect the link flow condition, the expansion prediction based on the average flow over-threshold value smoothes a plurality of micro-burst phenomena in the network, and therefore the micro-burst flow over-threshold value can not be reflected. The maximum value of the micro burst can be obtained based on the capacity expansion forecast that the peak flow exceeds the threshold, but the average flow of the network is possibly low, and the capacity expansion is completed in advance when the network flow is low, so that the waste of equipment performance and investment is caused.
In order to solve the above problem, an embodiment of the present application provides a method for predicting capacity expansion of network traffic, where the method is applied to a network architecture as shown in fig. 1, where a network includes a plurality of links, and nodes are connected with each other through the links, and the network architecture as shown in fig. 1 includes a node 101, a node 102, a link 111, a link 112, and a link 113, where the link 111 and the link 112 are connected through the node 101, and the link 112 and the link 113 are connected through the node 102; the node may be network element devices of different forms, such as: gateways, routes, switches, etc. When the scheme provided by the embodiment of the application is implemented, the monitoring device needs to obtain topology information of the whole network from a network controller or a network manager, and the topology information of the whole network includes all node information and all link information in the network. Wherein the node information includes each node ID, for example, node ID1011 of node 101, node ID1021 of node 102; all the link identification IDs connected to each node, for example, the link identification ID1111 of the link 111 connected to the node 101, the link identification ID1121 of the link 112 connected to the node 101. The link information includes link identification IDs, e.g., link identification ID1111 of link 111, link identification ID1121 of link 112, link identification ID1131 of link 113; all node IDs connected to the link, for example, node ID1011 of node 101 connected to link 112, node ID1021 of node 102 connected to link 112. Secondly, the monitoring device obtains link bandwidth data of the whole network from a network controller or a network manager, wherein the link bandwidth data comprises a bandwidth value of a link.
Based on the obtained topology information of the whole network, the present application provides a method for predicting the capacity expansion of network traffic, which, as shown in fig. 2, specifically includes the following steps:
201. and the monitoring equipment samples the network flow at a preset sampling frequency to acquire link data.
The monitoring device itself sets the sample data retention time, e.g., 1 hour, 1 day, 1 week, 1 month, etc. Storing link data obtained by sampling the link flow of the whole network, and storing the link data according to the set storage time of the sampled data; link data files that exceed the sample data retention time will be purged.
The link data comprises sampling time, a link identification ID and link flow of a link corresponding to the link identification ID, and the predetermined sampling frequency is greater than a frequency threshold. For example, the monitoring device performs high frequency sampling by using a telemetric technique to obtain high frequency sampling data. The sampling time refers to the time when sampling occurs, and for high-frequency sampling data, the interval of the sampling time can be 0.1 second, 1 second, 10 seconds and the like; the greater the sampling frequency, the greater the amount of data that needs to be stored. The link identification ID is a serial number set for the link in the system; the link traffic of the link corresponding to the link identification ID is the traffic of the link in this direction at the sampling time. The saved link data also includes { link A end node, link Z end node }, where link A end node and link Z end node are the directions in which the traffic in the link is determined, and if different link identification IDs are set for the two directions in the link, the A end node and Z end node of the link may not need to be stored.
For example, the monitoring device samples at a rate of 1 time per second via telemetric techniques and sets the retention time of the sampled data to 1 week, and data files exceeding the retention time of the sampled data will be purged. The saved link data may include the following information:
{ 2018-10-3011: 28:55, aaa-bbb, node A, node B, 5.1Gbps }, wherein 2018-10-3011: 28:55 is the sampling occurrence time, and aaa-bbb is the link identification ID; node A is the link A end node, node B is the link Z end node, and 5.1Gbps is the traffic data for link aaa-bbb at the sampling instant (2018-10-3011: 28:55) in the direction from node A to node B.
202. And converting the link flow of the link corresponding to any link identification ID into a relative value of the link flow.
And the relative value of the link traffic is equal to the link traffic/bandwidth value of the link corresponding to the link identification ID.
For example, if the link ID of the link in step 201 is aaa-bbb and the bandwidth is 10Gb, the relative value of the link traffic of the link is 5.1/10 or 0.51, which is the link traffic/bandwidth value of the link corresponding to the link ID.
203. And in a preset time period, if the relative value of the link flow at any sampling moment is greater than a first threshold value, recording the link flow of the link corresponding to any link identification ID at any sampling moment as an accumulation value.
The first threshold is an absolute threshold or a relative threshold of the link bandwidth corresponding to the link identification ID; the relative threshold value of the link bandwidth is manually specified relative threshold bandwidth/bandwidth value of the link, the absolute threshold value of the link bandwidth is manually specified absolute threshold bandwidth/bandwidth value of the link, and c is 1. The manually specified relative threshold bandwidth and the absolute threshold bandwidth are both smaller than the bandwidth value of the link, that is, the relative threshold of the link bandwidth and the absolute threshold of the link bandwidth are both smaller than 1, and generally the relative threshold is smaller than the absolute threshold. For example, if the link ID of the link in step 201 is aaa-bbb, assuming that its bandwidth is 10Gb, the manually specified relative threshold bandwidth is 7Gb, and the manually specified absolute threshold bandwidth is 9Gb, and the first threshold is the relative threshold of the link bandwidth, then the relative threshold of the link bandwidth is 7/10-70%; or, when the first threshold is an absolute threshold of the link bandwidth, the absolute threshold of the link bandwidth is an artificially specified absolute threshold bandwidth/bandwidth value of the link, which is 9/10-0.9-90%. The relative threshold and the absolute threshold of the link bandwidth can be manually set for each link one by one, namely the relative threshold and the absolute threshold of different links in the whole network can be different; in addition, a uniform relative threshold and an absolute threshold may be set for all links of the entire network, for example, a uniform relative threshold of 70% and an absolute threshold of 90% may be set for all links of the entire network.
When the first threshold is a relative threshold of the link bandwidth, the monitoring equipment compares a relative value 0.51 of the link traffic with a relative threshold 0.7 of the link bandwidth, and the relative value 0.51 of the link traffic at the moment of the link is less than or equal to the relative threshold 0.7 of the link bandwidth; or when the first threshold is the absolute threshold of the link bandwidth, the monitoring device compares the relative value 0.51 of the link traffic with the absolute threshold 0.9 of the link bandwidth, and if the relative value 0.51 of the link traffic at the moment of the link is smaller than the relative threshold 0.7 of the link bandwidth, no further analysis processing is performed on the link traffic. And if the relative value of the sampling flow of the link is greater than the first threshold value of the link, starting a subsequent sampling data processing mechanism for processing.
For a certain link in the network, when the relative value of the link flow at any sampling moment is greater than a first threshold value, the following processing is carried out on the relative value of the link flow at any sampling moment:
assuming that the sampling time is t, s (t) is a link flow value of the link at the time t, an accumulated value of the link at any sampling time is a, an initial value of a is 0, an accumulated value at the current time is a, and within a predetermined time period (t (0) to t (ti), for example, the designated time period is 20:00:00 to 21:00:00 one hour or 0:00:00 to 24:00:00 one day), the value of a is:
where k (T) is a number that varies with time T, and assuming that the first threshold of the link is T, k (T) takes the values:
For example, the first threshold is an absolute threshold of the link bandwidth, assuming that a certain link bandwidth is 10Gb, and the absolute threshold AT is 0.9, AT a certain sampling time, data of a certain link is as follows:
{ 2018-10-3119: 55: 17; aaa-ddd, node a, node D, 9.5Gbps, where the relative value of link traffic is 9.5/10 ═ 0.95, 0.95>0.9, the sampling data processing mechanism exceeding the absolute threshold is started, the sampling time t is 2018-10-3119: 55:17, the link traffic value s (t) at the link time t is 0.95, the accumulated value a obtained when the relative value of link traffic of the link is greater than the first threshold is set to be the link traffic of the link within 1 hour with the predetermined time period t (0) being 19:00:00 to t (ti) being 20:00:00, the initial value of a is 0, and the value of a at the current time is 7.32.
According to the formula
The obtained a-7.32 + l 0.95-8.27.
204. According to the formula
And converting the accumulation value in the preset time period into an expansion preparation value, and clearing the accumulation value.
Wherein a represents the accumulation value, EP represents a capacity expansion preparation value calculated for a predetermined time period before the predetermined time period, EP represents the capacity expansion preparation value corresponding to the predetermined time period, and n represents a conversion coefficient (which may be a constant) for converting the accumulation value a into the capacity expansion preparation value EP.
Assuming that the capacity expansion preparation value of a link is EP, the EP is initialized to 0, and for the accumulated value a greater than the first threshold, t (0) to t (ti) are calculated for each unit statistical time (for example, 20:00:00 to 21:00:00 for one hour, or 0:00:00 to 24:00:00), and after the predetermined period of time (e.g., 21:00:00 in one hour or 24:00:00 in one day), the accumulated value a greater than the first threshold value needs to be converted into an expansion ready value EP, and the accumulated value a is cleared. Comprises the following steps: when t is t (ti), calculating a capacity expansion preparation value
c is 1 and the accumulation value a is set to zero. Where n is a coefficient for converting the accumulation value a into the expansion preparation value EP, and may be a constant.
For example, let the capacity expansion preparation value EP of a certain link be initialized to 0, the capacity expansion preparation value EP at the current time be 353.27, and the accumulation value be a, and within each predetermined time period (t (0) to t (ti)), assuming that an hour, the value of a accumulated from 19:00:00 to 20:00:00 is one hour, after the unit segment is ended (e.g., 20:00:00), it is necessary to convert the accumulation value a into the capacity expansion preparation value EP, and clear the accumulation value a.
It should be noted that: the value of EP is not cleared from initialization, but is only accumulated. The value of a is converted to EP by some setting at the end of one unit of statistical time and then cleared.
205. And when the capacity expansion preparation value exceeds a second threshold value, issuing a capacity expansion forecast to a network manager or a network controller.
The expansion forecast comprises forecast time, forecast link identification ID, expansion preparation value and forecast expansion state; the forecast time is the last time of the predetermined time period or any time after the last time, for example, any time within two minutes after the predetermined time period.
The monitoring equipment regularly checks the capacity expansion preparation values of all links, when the capacity expansion preparation value EP of a certain link is found to exceed a preset second threshold, the monitoring equipment issues a capacity expansion forecast to a network manager or a controller through a signaling, the capacity expansion preparation value of the certain link is forecasted to be exceeded, capacity expansion needs to be carried out as soon as possible, and the forecast message comprises: { forecast time, forecast link identification ID, capacity expansion ready value (optional), forecast capacity expansion state }.
For example, assuming that the capacity expansion preparation values EP of all links are checked every hour, and assuming that the second threshold is 2000, the EP is updated from 353.27 to 371.59 after the end of the hour, but is still less than 2000, the present link does not perform the capacity expansion prediction issuance. When the analyzer finds that the EP of a certain link is updated from 1995.39 to 2003.24 after the end of the current hour, the analyzer issues an expansion forecast to the network manager or the controller through signaling, and the analyzer forecasts that the expansion preparation value of the link is exceeded and the expansion is required to be expanded as soon as possible, where the forecast message includes: { forecast time, forecast link identification ID, capacity expansion ready value (optional), forecast capacity expansion status }, e.g., { 2018-10-3120: 01:00, ccc-ddd, 2003.24, ready for capacity expansion }.
When the network manager or the controller receives the forecast of the analyzer, the network manager or the controller informs the network operation and maintenance personnel of a certain link to prepare capacity expansion in an alarm or message mode.
When the network manager or the controller integrates the functions of the monitoring device and is also used as the monitoring device, the network manager or the controller directly informs a network operation and maintenance person of a certain link to prepare capacity expansion in an alarm or message mode.
In the above scheme, since the network traffic can be sampled by adopting the predetermined sampling frequency greater than the frequency threshold, the link traffic of the link corresponding to any link identifier ID is converted into the relative value of the link traffic; in a preset time period, if the relative value of the link flow at any sampling moment is greater than a first threshold value, recording the link flow of the link corresponding to any link identification ID at any sampling moment as an accumulation value; the monitoring equipment is according to the formula
Converting the accumulation value in a preset time period into an expansion preparation value, and resetting the accumulation value; when the capacity expansion preparation value exceeds the second threshold value, the capacity expansion preparation value is sent to the network management or the network controllerAnd (5) distributing an expansion forecast. A large amount of sampled data can be processed in the case of a network configured with a high frequency sampling mechanism, and the processing mechanism through the two thresholds is responsive to both smooth and micro-bursty network traffic. And because the conversion of the accumulation value and the capacity expansion preparation value converts a large amount of sampling data of the whole network into capacity expansion decision data with decisive significance, and the capacity expansion prompt is automatically generated in the network with high-frequency sampling, the labor cost is reduced, the accuracy of a capacity expansion time point is effectively improved, the actual utilization rate of a network link is improved under the condition of not influencing the user experience, and the investment of network capacity expansion is saved.
When the first threshold is a relative threshold of the link bandwidth corresponding to the link identifier ID, the present application provides a method for predicting the capacity expansion of the network traffic, which is shown in fig. 3 and specifically includes the following steps:
301. and the monitoring equipment samples the network flow at a preset sampling frequency to acquire link data.
The link data comprises sampling time, a link identification ID and link flow of a link corresponding to the link identification ID; the predetermined sampling frequency is greater than a frequency threshold.
302. And converting the link flow of the link corresponding to any link identification ID into a relative value of the link flow.
And the relative value of the link traffic is equal to the link traffic/bandwidth value of the link corresponding to the link identification ID.
303. And when the relative value of the link flow is determined to be larger than the first threshold and smaller than the third threshold, recording the link flow of the link corresponding to the link identification ID as an accumulated value.
The first threshold is a relative threshold of the link bandwidth corresponding to the link identifier ID, and the relative threshold of the link bandwidth is an artificially specified relative threshold bandwidth/bandwidth value of the link; the third threshold is an absolute threshold of the link bandwidth corresponding to the link identifier ID, and the absolute threshold of the link bandwidth is an artificially specified absolute threshold bandwidth/bandwidth value of the link.
The topology of the whole network, the link bandwidth data, the relative threshold and the absolute threshold of each link are all stored in the monitoring equipment.
When the relative threshold of the link bandwidth < the relative value of the link traffic < — the absolute threshold of the link bandwidth, a sampling data processing mechanism exceeding the relative threshold is started, for example, assuming that a certain link bandwidth is 10Gb, the relative threshold RT is 0.7, the absolute threshold AT is 0.9, and AT a certain sampling time, certain link data is as follows:
{ 2018-10-3119: 26: 34; aaa-ccc, node a, node C, 7.5Gbps }, where the relative value of link traffic is 0.75, 0.7<0.75<0.9, a sampling data processing mechanism exceeding the relative threshold is started, the sampling time t is 2018-10-3119: 26:34, the link traffic value s (t) at the link time t is 0.75, the accumulated value a obtained when the relative value of link traffic of the link is greater than the first threshold is set to be the link traffic of the link within 1 hour with the predetermined time period t (0) of 19:00:00 to t (ti) of 20:00:00, the initial value of a is 0, and the value a at the current time is 37.2.
Then
A +1 × s (t) 37.2+ 0.75-37.95.
304 according to a formula
And converting the accumulation value in the preset time period into an expansion preparation value, and clearing the accumulation value.
Wherein Z represents a fourth threshold set for the accumulation value A, wherein the relative threshold of the link bandwidth corresponding to the link identifier ID is less than Z < the absolute threshold of the link bandwidth corresponding to the link identifier ID.
Since the accumulation value a here is an accumulation value exceeding a relative threshold, and the influence on the link expansion is small relative to an accumulation value exceeding an absolute threshold, the conversion of a to EP can be performed using:
For example, if the capacity expansion preparation value EP of a link is initialized to 0, the capacity expansion preparation value EP at the current time is 353.27, and for the accumulated value a exceeding the first threshold, the accumulated value a of 19:00:00 to 20:00:00 is assumed to be an accumulated value a of 19:00:00 to 20:00:00 for one hour, after the unit segment is ended (for example, 20:00:00), the accumulated value a exceeding the first threshold needs to be converted into the capacity expansion preparation value EP, and the accumulated value a exceeding the first threshold needs to be cleared, there are:
305. When the capacity expansion preparation value exceeds the second threshold value, a capacity expansion forecast is issued to the network management or the network controller
The expansion forecast comprises forecast time, forecast link identification ID, expansion preparation value and forecast expansion state; the forecast time is the last time of the predetermined time period or any time after the last time, for example, any time within two minutes after the predetermined time period.
When the network manager or the controller receives the forecast of the analyzer, the network manager or the controller informs the network operation and maintenance personnel of a certain link to prepare capacity expansion in an alarm or message mode.
When the network manager or the controller integrates the functions of the monitoring device and is also used as the monitoring device, the network manager or the controller directly informs a network operation and maintenance person of a certain link to prepare capacity expansion in an alarm or message mode.
Referring to fig. 4, a capacity expansion forecasting device for network traffic is provided, including:
the sampling module 42 is configured to sample network traffic at a predetermined sampling frequency to obtain link data, where the link data includes a sampling time, a link identifier ID, and link traffic of a link corresponding to the link identifier ID; the predetermined sampling frequency is greater than a frequency threshold.
A converting module 43, configured to convert the link traffic of the link corresponding to any one of the link identifiers ID sampled by the sampling module 42 into a relative value of the link traffic, where the relative value of the link traffic is the link traffic/bandwidth value of the link corresponding to the link identifier ID.
A recording module 44, configured to record, in a predetermined time period, link traffic of a link corresponding to any link identifier ID at any sampling time as an accumulated value if the relative value of the link traffic, which is obtained through conversion by the conversion module 43 at any sampling time, is greater than a first threshold value.
A calculation module 45 for calculating according to the formula
Converting the accumulation value recorded by the recording module 44 in the predetermined time period into an expansion preparation value, and resetting the accumulation value; wherein a represents the accumulation value, EP represents a capacity expansion preparation value calculated for a predetermined time period before the predetermined time period, and EP represents the capacity expansion preparation value corresponding to the predetermined time periodN represents a conversion coefficient for converting the accumulation value A into an expansion preparation value EP;
a sending module 46, configured to issue a capacity expansion forecast to a network manager or a network controller when the capacity expansion preparation value calculated by the calculating module 45 exceeds a second threshold, where the capacity expansion forecast includes a forecast time, a forecast link identifier ID, a capacity expansion preparation value, and a forecast capacity expansion state, and the forecast time is the last time of the predetermined time period or any time after the last time.
Optionally, the first threshold is an absolute threshold or a relative threshold of a link bandwidth corresponding to the link identifier ID; wherein the relative threshold of the link bandwidth is manually specified relative threshold bandwidth/bandwidth value of the link, the absolute threshold of the link bandwidth is manually specified absolute threshold bandwidth/bandwidth value of the link, and c is 1.
Optionally, the first threshold is a relative threshold of a link bandwidth corresponding to the link identifier ID, where the relative threshold of the link bandwidth is an artificially specified relative threshold bandwidth/bandwidth value of the link; then, in the predetermined time period, if the relative value of the link traffic at any one of the sampling times is greater than a first threshold, recording the link traffic of the link corresponding to any one of the link identification IDs at any one of the sampling times as an accumulated value, including: the recording module 44 is specifically configured to record the link traffic of the link corresponding to the link identifier ID as an accumulated value when it is determined that the relative value of the link traffic is greater than the first threshold and smaller than a third threshold; the third threshold is an absolute threshold of a link bandwidth corresponding to the link identifier ID, where the absolute threshold of the link bandwidth is an artificially specified absolute threshold bandwidth/bandwidth value of the link;
z represents a fourth threshold value set for the accumulation value A, wherein the relative threshold value < Z of the link bandwidth corresponding to the link identification ID is less than the absolute threshold value of the link bandwidth corresponding to the link identification ID.
Optionally, the method further includes: the obtaining module 41 is configured to obtain topology information and link bandwidth data of a whole network in a network controller or a network manager, where the topology information includes a link identifier ID, and the link bandwidth data includes a bandwidth value of a link corresponding to the link identifier ID.
Under the condition of adopting an integrated module, the capacity expansion forecasting device of the network flow comprises: the device comprises a storage unit, a processing unit and an interface unit. The processing unit is configured to control and manage an action of the capacity expansion forecasting device for the network traffic, for example, the processing unit is configured to support the capacity expansion forecasting device for the network traffic to execute the process 201 and 204 in fig. 2 and the process 301 and 304 in fig. 3. And an interface unit, configured to support information interaction between the capacity expansion predicting apparatus for network traffic and other devices to execute 205 in fig. 2 and 305 in fig. 3. And the storage unit is used for storing the program codes and the data of the capacity expansion forecasting device of the network flow.
For example, the processing unit is a processor, the storage unit is a memory, and the interface unit is a communication interface. The device for predicting the expansion of network traffic is shown in fig. 5, and includes a communication interface 51, a processor 52, a memory 53, and a bus 54, where the communication interface 51 and the processor 52 are connected to the memory 53 through the bus 54.
The Memory 53 may be a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these. The memory may be self-contained and coupled to the processor via a bus. The memory may also be integral to the processor.
The memory 53 is used for storing application program codes for executing the scheme of the application, and is controlled by the processor 52 to execute. The communication interface 51 is used for performing information interaction with other devices, for example, information interaction between the capacity expansion forecasting apparatus supporting network traffic and other devices, for example, acquiring data from other devices or sending data to other devices. The processor 52 is configured to execute application program code stored in the memory 53 to implement the methods described in the embodiments of the present application.
Further, a computer storage medium (or media) is provided, which includes instructions that, when executed, perform the method operations performed by the capacity expansion prediction apparatus for network traffic in the above embodiments. Additionally, a computer program product is also provided, comprising the above-described computing storage medium (or media).
All relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and the function thereof is not described herein again.
It should be understood that, in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for predicting the expansion of network traffic is characterized by that,
the method comprises the steps that network traffic is sampled by monitoring equipment at a preset sampling frequency, and link data are obtained, wherein the link data comprise sampling time, a link identification ID and link traffic of a link corresponding to the link identification ID; the predetermined sampling frequency is greater than a frequency threshold;
the monitoring equipment converts link traffic of a link corresponding to any link identification ID into a relative value of the link traffic, wherein the relative value of the link traffic is the link traffic/bandwidth value of the link corresponding to the link identification ID;
in a preset time period, if the relative value of the link flow at any sampling moment is greater than a first threshold value, recording the link flow of the link corresponding to any link identification ID at any sampling moment as an accumulation value;
the monitoring device is based on a formula
Converting the accumulation value in the preset time period into an expansion preparation value, and resetting the accumulation value; wherein A represents the accumulation value and ep represents a previous one for the predetermined period of timeThe expansion preparation value is obtained by calculation in a preset time period, EP represents the expansion preparation value corresponding to the preset time period, n represents a conversion coefficient for converting the accumulation value A into the expansion preparation value EP, and ti represents the last moment of the preset time period;
the c satisfies the formula:
wherein Z represents a fourth threshold set for the accumulation value A, and the relative threshold of the link bandwidth corresponding to the link identifier ID < Z < the absolute threshold of the link bandwidth corresponding to the link identifier ID;
and when the capacity expansion preparation value exceeds a second threshold value, issuing a capacity expansion forecast to a network manager or a network controller, wherein the capacity expansion forecast comprises forecast time, a forecast link identifier ID, a capacity expansion preparation value and a forecast capacity expansion state, and the forecast time is the last time of the preset time period or any time after the last time.
2. The method of claim 1, wherein the network traffic expansion forecast is further characterized in that,
the first threshold is an absolute threshold or a relative threshold of a link bandwidth corresponding to the link identifier ID;
wherein the relative threshold of the link bandwidth is manually specified relative threshold bandwidth/bandwidth value of the link, the absolute threshold of the link bandwidth is manually specified absolute threshold bandwidth/bandwidth value of the link, and c is 1.
3. The method of claim 1, wherein the network traffic expansion forecast is further characterized in that,
the first threshold is a relative threshold of a link bandwidth corresponding to the link identifier ID, where the relative threshold of the link bandwidth is an artificially specified relative threshold bandwidth/bandwidth value of the link; then, in the predetermined time period, if the relative value of the link traffic at any one of the sampling times is greater than a first threshold, recording the link traffic of the link corresponding to any one of the link identification IDs at any one of the sampling times as an accumulated value, including:
when the monitoring equipment determines that the relative value of the link flow is greater than the first threshold and smaller than a third threshold, recording the link flow of the link corresponding to the link identification ID as an accumulated value; the third threshold is an absolute threshold of a link bandwidth corresponding to the link identifier ID, where the absolute threshold of the link bandwidth is an artificially specified absolute threshold bandwidth/bandwidth value of the link.
4. The method for capacity expansion forecasting of network traffic according to any one of claims 1 to 3, wherein before the monitoring device samples the network traffic at a predetermined sampling frequency to obtain the link data, the method further includes:
the monitoring equipment acquires topology information and link bandwidth data of the whole network in a network controller or a network manager, wherein the topology information comprises a link identification ID, and the link bandwidth data comprises a bandwidth value of a link corresponding to the link identification ID.
5. A capacity expansion forecasting device of network traffic is characterized in that,
the system comprises a sampling module, a link data processing module and a link processing module, wherein the sampling module is used for sampling network traffic at a preset sampling frequency to acquire link data, and the link data comprises sampling time, a link identification ID and link traffic of a link corresponding to the link identification ID; the predetermined sampling frequency is greater than a frequency threshold;
a conversion module, configured to convert link traffic of a link corresponding to any one of the link identifiers ID sampled by the sampling module into a relative value of the link traffic, where the relative value of the link traffic is equal to the link traffic/bandwidth value of the link corresponding to the link identifier ID;
a recording module, configured to record, in a predetermined time period, link traffic of a link corresponding to any one of the link identifiers ID at any one of the sampling times as an accumulated value if a relative value of the link traffic, which is obtained by conversion by the conversion module at any one of the sampling times, is greater than a first threshold value;
a calculation module for calculating according to a formula
Converting the accumulation value recorded by the recording module in the preset time period into an expansion preparation value, and clearing the accumulation value; wherein a represents the accumulation value, EP represents a capacity expansion preparation value calculated for a predetermined time period before the predetermined time period, EP represents the capacity expansion preparation value corresponding to the predetermined time period, n represents a conversion coefficient for converting the accumulation value a into the capacity expansion preparation value EP, and ti represents the last time of the predetermined time period;
the c satisfies the formula:
wherein Z represents a fourth threshold set for the accumulation value A, and the relative threshold of the link bandwidth corresponding to the link identifier ID < Z < the absolute threshold of the link bandwidth corresponding to the link identifier ID;
and the sending module is used for issuing a capacity expansion forecast to a network manager or a network controller when the capacity expansion preparation value calculated by the calculating module exceeds a second threshold, wherein the capacity expansion forecast comprises forecast time, a forecast link Identifier (ID), a capacity expansion preparation value and a forecast capacity expansion state, and the forecast time is the last time of the preset time period or any time after the last time.
6. The capacity expansion forecasting device of network traffic according to claim 5,
the first threshold is an absolute threshold or a relative threshold of a link bandwidth corresponding to the link identifier ID;
wherein the relative threshold of the link bandwidth is manually specified relative threshold bandwidth/bandwidth value of the link, the absolute threshold of the link bandwidth is manually specified absolute threshold bandwidth/bandwidth value of the link, and c is 1.
7. The capacity expansion forecasting device of network traffic according to claim 5,
the first threshold is a relative threshold of a link bandwidth corresponding to the link identifier ID, where the relative threshold of the link bandwidth is an artificially specified relative threshold bandwidth/bandwidth value of the link; then, in the predetermined time period, if the relative value of the link traffic at any one of the sampling times is greater than a first threshold, recording the link traffic of the link corresponding to any one of the link identification IDs at any one of the sampling times as an accumulated value, including:
the recording module is specifically configured to record the link traffic of the link corresponding to the link identifier ID as an accumulated value when it is determined that the relative value of the link traffic is greater than the first threshold and smaller than a third threshold; the third threshold is an absolute threshold of a link bandwidth corresponding to the link identifier ID, where the absolute threshold of the link bandwidth is an artificially specified absolute threshold bandwidth/bandwidth value of the link.
8. The apparatus according to any one of claims 5 to 7, further comprising:
the network management system comprises an acquisition module and a processing module, wherein the acquisition module is used for acquiring topology information and link bandwidth data of the whole network in a network controller or network management, the topology information comprises a link identification ID, and the link bandwidth data comprises a bandwidth value of a link corresponding to the link identification ID.
9. The capacity expansion forecasting device of the network flow is characterized by comprising a communication interface, a processor, a memory and a bus; the memory is used for storing computer execution instructions, the processor is connected with the memory through the bus, and when the capacity expansion forecasting device of the network traffic runs, the processor executes the computer execution instructions stored in the memory, so that the capacity expansion forecasting device of the network traffic executes the capacity expansion forecasting method of the network traffic according to any one of claims 1 to 4.
10. A computer storage medium comprising instructions that, when executed on a computer, cause the computer to perform the method of capacity expansion forecasting of network traffic of any of claims 1-4.
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