CN114338532B

CN114338532B - Optical network resource prediction method and device, storage medium and terminal equipment

Info

Publication number: CN114338532B
Application number: CN202111649463.7A
Authority: CN
Inventors: 秦海洁; 陈云; 刘祎
Original assignee: China Telecom Corp Ltd
Current assignee: China Telecom Corp Ltd
Priority date: 2021-12-30
Filing date: 2021-12-30
Publication date: 2024-04-30
Anticipated expiration: 2041-12-30
Also published as: CN114338532A

Abstract

The disclosure relates to the technical field of communication, and in particular relates to a method and a device for estimating optical network resources, a storage medium and terminal equipment. The method comprises the following steps: collecting historical data of a preset statistical period as a pre-estimated sample; wherein the estimated sample comprises OLT data and PON data; preprocessing the estimated sample to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data, PON intermediate data; configuring an activity rate threshold of a target scene; wherein the activity rate threshold comprises a wideband activity rate increment and an ITV activity rate threshold; determining an optical network flow estimation result based on the intermediate data, the activity rate threshold value and the association relation between the startup user and the flow brought by the startup user; the optical network traffic estimation result comprises: any one or a combination of any multiple of a downlink flow average value predicted value, a downlink flow peak value predicted value, an uplink flow average value predicted value and an uplink flow peak value predicted value. The method and the device can realize the prediction of the network resources of the optical network.

Description

Optical network resource prediction method and device, storage medium and terminal equipment

Technical Field

The disclosure relates to the technical field of communication, and in particular relates to an optical network resource estimating method, an optical network resource estimating device, a storage medium and a terminal device.

Background

With the rapid development of internet technology, the demand for internet speed is increasing when users use the internet. At present, the number of users surfing the internet is relatively stable, and the number of general network users cannot be obviously changed; however, the stock users, namely the users with broadband and ITV, have the conditions that part of the users are on the internet daily, the starting rate is not high or the users are not started; however, under some special dates or scenes, there is a steep increase in the open probability, and the ITV blocking phenomenon occurs due to the limitation of the bandwidth of the optical network resources. Therefore, it is necessary to accurately predict the network capability, especially the optical network resources, in advance to satisfy the network demand change of the user.

It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

The disclosure aims to provide an optical network resource estimating method, an optical network resource estimating device, a storage medium and a terminal device, which can realize the estimation of the optical network resource and further overcome the defects caused by the limitations and defects of the related technology at least to a certain extent.

Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.

According to a first aspect of the present disclosure, there is provided an optical network resource estimation method, including:

Collecting historical data of a preset statistical period as a pre-estimated sample; wherein the estimated samples comprise OLT data and PON data;

Preprocessing the estimated sample to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data, PON intermediate data; and

Configuring an activity rate threshold of a target scene; wherein the activity rate threshold comprises a wideband activity rate increment and an ITV activity rate threshold;

Determining an optical network flow estimation result based on the intermediate data, the activity rate threshold and the association relation between the startup user and the flow brought by the startup user; wherein, the optical network flow estimation result includes: any one or a combination of any multiple of a downlink flow average value predicted value, a downlink flow peak value predicted value, an uplink flow average value predicted value and an uplink flow peak value predicted value.

In an exemplary embodiment of the present disclosure, the OLT data includes: first device configuration data, first device bandwidth traffic data, first user usage behavior data, and user value data;

the PON data includes: second device configuration data, second device bandwidth traffic data, second user usage behavior data, and second user value data.

In one exemplary embodiment of the present disclosure, acquiring OLT intermediate data includes:

taking an OLT device as a unit, respectively accumulating uplink and downlink bandwidth capacity of all links, signing bandwidth of each service of each user of a down-link user, and calculating the on-rate to obtain OLT data intermediate data; the OLT intermediate data includes: any one or a combination of any multiple of the downlink capacity of the total bandwidth of the OLT, the uplink capacity of the total bandwidth of the OLT, the downlink contracted total bandwidth of the broadband of the underhung user, the uplink contracted total bandwidth of the broadband of the underhung user, the ITV total bandwidth of the underhung user, the increment broadband user number and the increment ITV user number.

In one exemplary embodiment of the present disclosure, acquiring PON intermediate data comprises:

Taking a PON port as a unit, respectively accumulating the contracted bandwidths of the services of each user of the down-hanging user, and calculating the opening probability of each service to obtain PON intermediate data; wherein, the PON intermediate data comprises: any one or a combination of any of the broadband subscription total bandwidth of the down subscriber, the ITV total bandwidth of the down subscriber, the incremental broadband user number, and the incremental ITV user number.

In an exemplary embodiment of the present disclosure, the configuring the activity rate threshold of the target scene includes:

and configuring an activity rate threshold of at least one group of target scenes based on the statistical result of the historical data of the designated period.

In an exemplary embodiment of the present disclosure, determining a downlink traffic average value predicted value based on the intermediate data, the activity rate threshold, and an association relationship between a startup user and traffic brought by the startup user includes:

determining the total increment of the downlink subscription bandwidth according to the activity rate threshold; the downlink subscription bandwidth sum increment comprises a broadband downlink sum increment and an ITV downlink sum increment;

calculating a first coefficient based on the sum of signed downlink bandwidths of the starting equipment and a downlink flow average value calculated based on a plurality of statistical period data; the starting-up equipment signed-up downlink bandwidth sum comprises starting-up broadband signed-up downlink bandwidth sum and starting-up ITV signed-up downlink bandwidth sum;

determining a downlink flow average value increase value according to the first coefficient and the downlink subscription bandwidth sum increment;

and determining the downlink flow average value estimated value based on the downlink flow average value increased value and the downlink flow average value calculated based on a plurality of statistical period data.

In an exemplary embodiment of the present disclosure, determining an uplink traffic average value predicted value based on the intermediate data, the activity rate threshold, and an association relationship between a startup user and traffic brought by the startup user includes:

Counting the increment of the uplink sum of the bandwidth according to the increment of the broadband activity rate;

determining a second coefficient based on the uplink flow average value calculated by the plurality of statistical period data and the sum of the uplink bandwidth of the startup broadband subscription;

Calculating an uplink flow direction average value increment value according to the second coefficient and the broadband uplink sum increment value;

And determining an upstream flow average value predicted value based on the upstream flow average value increased value and an upstream flow average value calculated based on a plurality of statistical period data.

In an exemplary embodiment of the present disclosure, determining a downstream traffic peak value according to the intermediate data, the activity rate threshold, and an association relationship between the power-on user and traffic brought by the power-on user includes:

Calculating a third coefficient based on the sum of signed downlink bandwidths of the starting equipment and the downlink flow peak value calculated based on the plurality of statistical period data; the starting-up equipment signed-up downlink bandwidth sum comprises starting-up broadband signed-up downlink bandwidth sum and starting-up ITV signed-up downlink bandwidth sum;

Determining a downlink flow peak increment value according to the third coefficient and the downlink subscription bandwidth sum increment;

And determining the downstream flow peak value predicted value based on the downstream flow peak value calculated based on the plurality of statistical period data based on the downstream flow peak value increased value.

In an exemplary embodiment of the present disclosure, determining an upstream traffic peak value predicted value based on the intermediate data, the activity rate threshold, and an association relationship between a power-on user and traffic brought by the power-on user includes:

Determining a fourth coefficient based on the uplink flow peak value calculated by the plurality of statistical period data and the sum of the uplink bandwidth of the startup broadband subscription;

calculating an uplink flow direction peak value increment according to the fourth coefficient and the broadband uplink total increment;

and determining an upstream flow peak value predicted value based on the upstream flow peak value increased value and an upstream flow peak calculated based on a plurality of statistical period data.

According to a second aspect of the present disclosure, there is provided an optical network resource estimating apparatus, including:

The historical data acquisition module is used for acquiring historical data of a preset statistical period as a pre-estimated sample; wherein the estimated samples comprise OLT data and PON data;

the data preprocessing module is used for preprocessing the estimated sample to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data, PON intermediate data; and

The threshold parameter configuration module is used for configuring an activity rate threshold of the target scene; wherein the activity rate threshold comprises a wideband activity rate increment and an ITV activity rate threshold;

The pre-estimation processing module is used for determining an optical network flow pre-estimation result based on the intermediate data, the activity rate threshold and the association relation between the startup user and the flow brought by the startup user; wherein, the optical network flow estimation result includes: any one or a combination of any multiple of a downlink flow average value predicted value, a downlink flow peak value predicted value, an uplink flow average value predicted value and an uplink flow peak value predicted value.

According to a third aspect of the present disclosure, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described optical network resource estimation method.

According to a fourth aspect of the present disclosure, there is provided a terminal device comprising:

A processor; and

A memory for storing executable instructions of the processor;

wherein the processor is configured to execute the above-described method of estimating optical network resources by executing the executable instructions.

In the method for predicting optical network resources provided by the embodiment of the disclosure, OLT intermediate data and PON intermediate data are obtained by collecting OLT data and PON data as sample data and preprocessing the sample data; after an activity rate threshold of a target scene is configured, an optical network flow estimation result is determined based on the intermediate data, the activity rate threshold and the association relation between the startup user and the flow brought by the startup user. The method can be used for estimating the network resource flow of the special scene optical network from the angle of the association relation between the startup user and the flow brought by the startup user; and, the optical network traffic prediction result includes: the downlink flow average value predicted value, the downlink flow peak value predicted value, the uplink flow average value predicted value and the uplink flow peak value predicted value can realize the accurate prediction of the network flow of the optical network equipment.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.

Fig. 1 schematically illustrates a schematic diagram of an optical network resource estimation method in an exemplary embodiment of the disclosure;

fig. 2 schematically illustrates a schematic diagram of an optical network resource link structure in an exemplary embodiment of the disclosure;

fig. 3 schematically illustrates a schematic diagram of an optical network resource estimating apparatus according to an exemplary embodiment of the disclosure;

Fig. 4 schematically illustrates a composition diagram of a terminal device in an exemplary embodiment of the present disclosure;

fig. 5 schematically illustrates a schematic diagram of a storage medium in an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.

In the related technology, although the number of users surfing the internet tends to be saturated at present, the number of users does not have obvious increment, but the stock users, namely the users with broadband and ITV, have the conditions that part of users surf the internet daily, the starting rate is not high or the users are not started. But under special holidays, such as special scenes of big reading soldiers, thirty years and the like, the users who start up and surf the internet are increased rapidly, namely, the users who start up increase the scenes rapidly. Especially, the daily ITV film watching user group is mainly old people, the starting rate is low, but when large reading soldiers are in the late thirty-spring of the year, the film watching users are in steep increase, namely, the starting rate is in a steep increase scene. Because of the problem of limited optical network resource bandwidth, ITV often has a jam, faults occur in important communication scenes, user perception is particularly poor, and a large number of users report the situation that a large number of large readers ever occur in a certain place in a certain year. In addition, according to the national uniform deployment requirement, operators frequently increase the speed of the user network in recent years, and a speed increasing scene exists when the users do not increase the bandwidth. Although operators are continuously accelerating the subscriber network, subscribers often declare that the acceleration is slow, again due to limited device bandwidth capabilities. The above scenes are all characterized in that the number of users is not increased but the use flow of the users is increased, namely, the device ports are not increased but the device bandwidth is full. In order to meet increasing user demands and improve user perception, network capacity, particularly optical network resources, of a specific scene need to be accurately estimated in advance. The specific scene is that the resource estimation of the bandwidth capacity of the equipment is required due to the use behavior change of the user, so that the use flow brought by each user when surfing the internet and watching the video is required to be obtained. The current ways to obtain the flow are: DPI (DEEP PACKET Inspection technology based on data packet) collects the traffic of single user and single application, the traffic of user level, ONU equipment collected by network management, or the ticket traffic on AAA (Authentication, authorization and Accounting) service. However, at present, the DPI is required to collect the flow of each application of each user, and the flow of each application of each user of the whole network is required to be obtained by full-spectrum light collection and analysis of the whole network, but tens of millions of funds are required to be deployed on the network, so the DPI cannot obtain the flow of each application of each user of the whole network. The AAA ticket statistics is the accumulated traffic between the internet surfing and the disconnection, and even if Guan Guangmao (90% of users do not open Guan Guangmao), the network is set to automatically disconnect for 48 hours, so the accumulated internet surfing ticket traffic is generally accumulated every 2 days, and is not the instantaneous traffic.

In view of the above-mentioned drawbacks and shortcomings in the prior art, the present exemplary embodiment provides an optical network resource estimating method, which can implement the estimation of the optical network resource requirement. Referring to fig. 1, the method for estimating optical network resources may include the following steps:

S11, collecting historical data of a preset statistical period as a pre-estimated sample; wherein the estimated samples comprise OLT data and PON data;

S12, preprocessing the estimated sample to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data, PON intermediate data; and

S13, configuring an activity rate threshold of a target scene; wherein the activity rate threshold comprises a wideband activity rate increment and an ITV activity rate threshold;

S14, determining an optical network flow estimation result based on the intermediate data, the activity rate threshold and the association relation between the startup user and the flow brought by the startup user; wherein, the optical network flow estimation result includes: any one or a combination of any multiple of a downlink flow average value predicted value, a downlink flow peak value predicted value, an uplink flow average value predicted value and an uplink flow peak value predicted value.

In the optical network resource estimation method provided by the present exemplary embodiment, OLT intermediate data and PON intermediate data are obtained by collecting OLT data and PON data as sample data and preprocessing them; and after the activity rate threshold value of the target scene is configured, determining an optical network traffic estimation result based on the intermediate data and the activity rate threshold value. The method can be used for estimating the network resource flow of the special scene optical network from the angle of the association relation between the startup user and the flow brought by the startup user; and, the optical network traffic prediction result includes: the downlink flow average value predicted value, the downlink flow peak value predicted value, the uplink flow average value predicted value and the uplink flow peak value predicted value can realize the accurate prediction of the network flow of the optical network equipment.

The steps of the optical network resource estimation method in this exemplary embodiment will be described in more detail below with reference to the accompanying drawings and examples.

In step S11, collecting historical data of a preset statistical period as a pre-estimated sample; wherein the estimated samples include OLT data and PON data.

In this example embodiment, the method described above may be performed at the server side, or implemented by cooperation between the user terminal and the server side. For example, the user may send a data estimation request to the server at the user terminal; the data estimation request may include a time period for estimating the optical network resources, a network area, hardware device data, and the like. For example, a user desires to evaluate the network demand of area a, area B during an eleven holiday. After receiving the data estimation request, the server side can create a corresponding data processing task and execute the data processing task.

Specifically, the server may first collect historical data of a preset statistical period. For example, referring to the network resource link structure shown in fig. 2, a BRAS (Broadband Remote ACCESS SERVER) device 201 is connected to an OLT (Optical LINE TERMINAL) device 202, and the OLT device 202 is connected to a plurality of ONUs (Optical Network Unit ) devices 204 through an Optical splitter 203. Two types of port data on the OLT equipment can be extracted on the network manager of the optical access network equipment OLT, namely, the data of an upper port are collected through the BRAS equipment, namely, the data of an uplink and downlink flow peak value and flow average value of an uplink total link of the OLT; and downlink port data, i.e., upstream and downstream flow peak and flow average data of PON (Passive Optical Network ) ports. In addition, the user subscription bandwidth data hung under each PON port on the OLT apparatus can be extracted on the AAA platform. For example, the duration of one statistical period may be configured to be one week; historical data for a plurality of consecutive periods may be collected as pre-estimated samples.

In this example embodiment, in the above-mentioned estimated sample, the OLT data includes: first device configuration data, first device bandwidth traffic data, first user usage behavior data, and user value data; the PON data includes: second device configuration data, second device bandwidth traffic data, second user usage behavior data, and second user value data. Wherein the first device may be an OLT device; the second device may be a PON port.

Specifically, the collected OLT data may include data of a plurality of fields including: the system comprises the basic information of the OLT equipment, the uplink configuration of the OLT equipment, the bandwidth of the OLT equipment and the use behavior of the OLT user. The OLT device basic information may include time, OLT IP, branch company, and OLT name; the uplink configuration of the OLT apparatus may include: a single uplink downlink bandwidth OLT-singlink-Band-down, a single uplink bandwidth OLT-singlink-Band-up, a used port number of OLT-user-num and a total port number of All-port-num. The OLT device bandwidth may include: the system comprises an OLT downstream flow average value, an OLT upstream flow average value, an OLT downstream flow peak value and an OLT upstream flow peak value. The user usage behavior data may include: the broadband user number is hung under the OLT, the ONU-on-Num-Band of the broadband starting user number of the OLT, the ITV user number is hung under the OLT, and the ONU-on-Num-ITV of the OLT-ITV starting user number.

The collected PON port data may contain data for a plurality of fields including: PON device basic information, PON device configuration, PON device bandwidth, PON user usage behavior. Wherein, the PON device basic information may include: time, OLT IP, OLT-PON port, branch office, OLT name. The PON device configuration information may include: PON port total bandwidth capability. The PON device bandwidth information may include: PON port downstream flow mean, PON port upstream flow mean, PON port downstream flow peak, PON port upstream flow peak. The PON user usage behavior information may include: PON port down-hanging broadband user number, PON port broadband start-up user number, PON port down-hanging ITV user number, PON port-ITV start-up user number

Further, the user value data may contain data of the following fields, including: broadband account number, signed broadband downlink bandwidth sign-band_Down, signed broadband uplink bandwidth sign-band_Up and ITV service type sign-ITV_Down.

In step S12, preprocessing the estimated sample to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data, PON intermediate data.

In this example embodiment, after the estimated sample data is obtained, it may be preprocessed to obtain corresponding intermediate data. Specifically, for OLT intermediate data, the uplink and downlink bandwidth capacity of all links, the subscription bandwidth of each service of each user of the down-link user, and the calculation probability may be respectively accumulated by taking one OLT device as a unit, so as to obtain OLT intermediate data; the OLT intermediate data includes: any one or a combination of any multiple of the downlink capacity of the total bandwidth of the OLT, the uplink capacity of the total bandwidth of the OLT, the downlink contracted total bandwidth of the broadband of the underhung user, the uplink contracted total bandwidth of the broadband of the underhung user, the ITV total bandwidth of the underhung user, the increment broadband user number and the increment ITV user number. Referring to table 1, an OLT intermediate data table may be generated.

TABLE 1

Wherein, the total bandwidth downlink capacity of the OLT link OLT-Band-all-down=single uplink downlink bandwidth OLT-singlink-Band-down has used the port number OLT-user-num;

OLT-Band-all-up = single uplink upstream bandwidth OLT-singlink-Band-up the number of ports used OLT-user-num;

Downlink subscriber broadband downlink subscription total bandwidth ONU-Band-all-Down = Σ (sign-band_down);

The ITV total bandwidth ONU-ITV-all = Σ (sign-itv_down) of the underhung subscriber.

Specifically, for PON intermediate data, a PON port may be used as a unit, to accumulate subscription bandwidths of services of each user of the down-hanging user, and calculate an opening probability of each service, so as to obtain PON intermediate data; wherein, the PON intermediate data comprises: any one or a combination of any of the broadband subscription total bandwidth of the down subscriber, the ITV total bandwidth of the down subscriber, the incremental broadband user number, and the incremental ITV user number. As shown with reference to table 2, a PON intermediate data table may be generated.

TABLE 2

In step S13, an activity threshold of the target scene is configured; wherein the activity rate threshold comprises a wideband activity rate increment and an ITV activity rate threshold.

In this example embodiment, the activity rate threshold of at least one set of the target scenes may be configured based on statistics of the specified period history data. Specifically, for a power-on user steep increase scene, to obtain the broadband increased active user number and the ITV increased active user number, an estimated scene threshold needs to be set, where the threshold includes a broadband activity rate increment and an ITV activity rate threshold. For example, the present invention primarily sets two threshold scenarios for ITV active steep rise scenarios (e.g., thirty years, big reading soldiers, etc.) based on data of the same year or year. Wherein, in the first scene, the threshold value is set to 10% for broadband activity rate increment, and the ITV activity rate threshold value is set to 80%; the scene two threshold is set to 10% for wideband activity rate increment and the ITV activity rate threshold is set to 100%. In addition, for the speed-up scene, the change of the subscription bandwidth of the down-hanging user is directly calculated without setting a threshold value, and the increment of the subscription bandwidth is obtained.

Or in some exemplary embodiments, the user may configure wideband activity rate increment and ITV activity rate thresholds based on empirical values. Or the number of the active users can be compared according to a plurality of statistical periods of the same month in different years, and the broadband activity rate increment and the ITV activity rate threshold value are determined according to the comparison result of the active users.

In step S14, determining an optical network traffic estimation result based on the intermediate data, the activity rate threshold, and the association relationship between the startup user and traffic brought by the startup user; wherein, the optical network flow estimation result includes: any one or a combination of any multiple of a downlink flow average value predicted value, a downlink flow peak value predicted value, an uplink flow average value predicted value and an uplink flow peak value predicted value.

In the present exemplary embodiment, since the occupied bandwidth of the ITV has a fixed value, and the OLT (generally 2000 multiple users) and PON (60 users hung under MAX) coverage areas are substantially similar to each other, the audience user groups can be regarded as substantially consistent traffic due to the internet surfing behavior. By utilizing the characteristic, the use flow relation of the ports, which is brought by the total subscription bandwidth of the users who hang the power-on under the ports, is calculated, namely the use flow of the ports is divided by the total subscription bandwidth of the users who hang the power-on under the ports, and the use flow brought by each subscription bandwidth under the ports is obtained.

Specifically, in this exemplary embodiment, determining the downlink traffic average value based on the intermediate data, the activity rate threshold, and the association relationship between the boot user and traffic brought by the boot user includes:

Step S211, determining the sum increment of the downlink subscription bandwidth according to the activity rate threshold; the downlink subscription bandwidth sum increment comprises a broadband downlink sum increment and an ITV downlink sum increment;

Step S212, calculating a first coefficient based on the sum of the signed downlink bandwidths of the starting equipment and a downlink flow average value calculated based on a plurality of statistical period data; the starting-up equipment signed-up downlink bandwidth sum comprises starting-up broadband signed-up downlink bandwidth sum and starting-up ITV signed-up downlink bandwidth sum;

Step S213, determining a downlink flow average value increasing value according to the first coefficient and the downlink subscription bandwidth sum increment;

Step S214, determining the downlink flow average value predicted value based on the downlink flow average value increased value and the downlink flow average value calculated based on the plurality of statistical period data.

Specifically, an increment of the sum of the downstream subscription bandwidths may be calculated first. For a power-on user steep increase scene, the signed bandwidth increment is calculated by the following formula:

broadband downlink total increment (band_incr_down_) =default broadband downlink subscription bandwidth (100M: modifiable) ×broadband increased active user number;

ITV downlink sum delta (itv_incr_down_) =default ITV downlink subscription bandwidth (16M) ×active number of ITV increases;

Wherein the increased active user number of the broadband = the total number of the down-hung broadband of the device x the broadband activity rate is increased; according to the previous scene, the broadband activity rate is increased by 10%;

wherein the increased number of active users of ITV = the total number of users of the underhung ITV of the device x the increase in ITV activity rate; for example, the ITV activity threshold is set to 80% or 100% according to the previous scenario;

ITV activity increment = ITV activity threshold-mean of ITV activity in the first 8 phases;

for the speed-up scene, the front-back change condition of the subscription bandwidth of the hanging user can be directly calculated.

The calculation of the coefficients, i.e. the traffic used per contracted bandwidth, can then be performed. In order to represent the relationship between each type of port power-on user and the flow brought by the port power-on user, the relationship can be marked as DOWN_r1, and the DOWN_r1 is used as a coefficient for calculating the average value of the downlink flow, and the calculation formula is as follows:

starting up the broadband subscription downlink bandwidth sum=broadband subscription downlink bandwidth sum×broadband on probability;

starting ITV subscription downstream bandwidth sum=ITV subscription downstream bandwidth sum×ITV starting rate

Down_r1=ads_tmp_down/(start-up broadband subscription downstream bandwidth sum+start-up ITV subscription downstream bandwidth sum);

The ads_tmp_down represents an average value of downlink flow average values in historical data in a plurality of continuous statistical periods, and the data is collected from a network manager of the OLT device.

Then, a downlink traffic average value increase value p_ads_down can be calculated; the calculation formula may include:

p_ads_down=down_r1× (broadband downlink total increment band_incr_down_ +itv downlink total increment itv_incr_down_);

Thereafter, a downstream traffic average estimate (e_ads_down) may be calculated; wherein,

e_ADS_DOWN＝p_ADS_DOWN+ADS_tmp_DOWN。

Specifically, in this exemplary embodiment, determining the uplink traffic average value based on the intermediate data, the activity rate threshold, and the association relationship between the boot user and traffic brought by the boot user includes:

step S221, counting the increment of the uplink sum of the bandwidth according to the increment of the broadband activity rate;

step S222, determining a second coefficient based on the uplink flow average value calculated by the data of the plurality of statistical periods and the sum of the uplink bandwidths of the startup broadband subscription;

step S223, calculating an uplink flow direction average value increment value according to the second coefficient and the broadband uplink sum increment;

step S224, determining an upstream flow average value predicted value based on the upstream flow average value increased value and the upstream flow average value calculated based on the plurality of statistical period data.

For example, because of the ITV service characteristics, there is no uplink subscription bandwidth, so the uplink traffic average value estimation only needs to consider the broadband service. First, an increment of the sum of the upstream subscription bandwidths may be calculated. For a power-on user steep increase scene, the calculation formula of the signed bandwidth increment can include:

broadband uplink total increment (band_incr_up_) =default broadband uplink subscription bandwidth (20M: modifiable) ×broadband increased active user number;

wherein the increased active user number of the broadband = the total number of the down-hung broadband of the device x the broadband activity rate is increased; for example, the wideband activity rate increment may be 10% in the wideband activity ramp up scenario;

And for the speed-up scene, directly calculating the front-back change condition of the subscription bandwidth of the down-hanging user.

Then, a coefficient calculation, i.e. the traffic used per contracted bandwidth, can be performed. To represent the relationship between the power-on user of each device and the flow brought by the power-on user, we will call it up_r1 as a coefficient for calculating the average value of the uplink flow, and the calculation formula may include:

Starting up the broadband subscription uplink bandwidth sum = broadband subscription uplink bandwidth sum x broadband on probability;

up_r1=ads_tmp_up/start-UP broadband subscription upstream bandwidth sum;

the ads_tmp_up represents an average value of uplink flow average values of historical data of a plurality of continuous statistical periods, and the data is collected from PON network management of the OLT.

Thereafter, an upstream traffic average value p_ads_up may be calculated, and the calculation formula may include:

p_ads_up=up_r1×wideband upstream sum delta band_incr_up

Then, an upstream traffic average value estimated value e_ads_up can be calculated; the calculation formula may include:

e_ADS_UP＝p_ADS_UP+ADS_tmp_UP。

Specifically, in this exemplary embodiment, determining the downstream traffic peak value predicted value based on the intermediate data, the activity rate threshold, and the association relationship between the boot user and the traffic brought by the boot user includes:

Step S231, determining the sum increment of the downlink subscription bandwidth according to the activity rate threshold; the downlink subscription bandwidth sum increment comprises a broadband downlink sum increment and an ITV downlink sum increment;

Step S232, calculating a third coefficient based on the total signed downlink bandwidth of the starting equipment and the downlink flow peak value calculated based on a plurality of statistical period data; the starting-up equipment signed-up downlink bandwidth sum comprises starting-up broadband signed-up downlink bandwidth sum and starting-up ITV signed-up downlink bandwidth sum;

Step S233, determining a downlink flow peak increment value according to the third coefficient and the downlink subscription bandwidth sum increment;

Step S234, determining the downstream flow peak estimated value based on the downstream flow peak value calculated based on the plurality of statistical period data based on the downstream flow peak value increase value.

Specifically, in this exemplary embodiment, determining the uplink traffic peak value estimated based on the intermediate data, the activity rate threshold, and the association relationship between the boot user and traffic brought by the boot user includes:

step S241, bandwidth uplink sum increment is counted according to broadband activity rate increment;

Step S242, determining a fourth coefficient based on the uplink flow peak value calculated by the plurality of statistical period data and the sum of the uplink bandwidths of the startup broadband subscription;

step S243, calculating an uplink flow direction peak value increase according to the fourth coefficient and the broadband uplink total increase;

Step S244, determining an upstream traffic peak estimated value based on the upstream traffic peak increment value and the upstream traffic peak calculated based on the plurality of statistical period data.

In some exemplary embodiments, the method provided by the present disclosure predicts the link traffic on the OLT during the national celebration. First, the coefficient was calculated for 8 weeks of data as history data before the national holiday. Considering that partial students may leave the holidays and return home in the national celebration holidays, the number of active users is relatively higher than September, but the number of active users in summer holidays is not higher than that in September, so that 8.12 data of the number of active users in summer holidays is taken as basic data. The newly added traffic of national celebration is accumulated on 8.12 period data.

Then, two pairs of thresholds are set for comparison and prediction, namely a scene threshold pair: the broadband activity rate increases by 10%, and the ITV activity rate threshold value 80%; scene two threshold pair: the broadband activity rate increases by 10%, the ITV activity rate threshold is 100%, the super threshold is not calculated any more, and the ITV activity rate is directly increased to the threshold after being lower than the threshold. And outputting a result. The predicted results are as follows: the average value and the peak value duty ratio of the uplink busy hour output by the two scene threshold values are lower, and the peak value resource duty ratio of the uplink traffic of 1 OLT is lower than 30 percent (38 percent of Yongchuan x.x.x). The scene has more than 60% of average value of downlink busy hour, more than 70% of downlink peak value and 29 OLTs, and the scene has more than 60% of average value of downlink busy hour, more than 11% of average value of downlink busy hour, more than 70% of downlink peak value and 35 OLTs, as shown in table 3.

TABLE 3 Table 3

Wherein, for scenario 1, there are 29 downstream peak duty ratios exceeding 70%, and 13 OLTs configure only 1 link. As shown in table 4.

TABLE 4 Table 4

Wherein for scenario two, the downstream peak ratio exceeds 70% with 35 OLTs, of which 17 OLTs only configure 1 link, as shown in table 5.

TABLE 5

According to the estimated result, on one hand, the branch company expands the capacity of the OLT with more users, especially the OLT with 1 link. On the other hand, the branch company can expand the capacity of equipment with more key users or users in the OLT with the busy hour average value exceeding 60% and the peak value exceeding 70%.

And considering the long-term use condition of the user, and finally adopting a scene-threshold value pair to perform network resource capacity expansion optimization. After the step, post-evaluation is carried out, and the flow demand of the user during national celebration is met by adopting a scene I estimation method.

According to the optical network resource prediction method, after historical flow data are collected, data preprocessing is carried out; setting a user startup threshold value of a specific scene; and then calculating the downlink flow average value, the downlink flow peak value, the uplink flow average value and the uplink flow peak value of various equipment ports of the optical network resources by a calculation algorithm based on the association relation between the startup user and the flow brought by the startup user. The method utilizes four major historical data of the optical network resources, including equipment configuration, equipment bandwidth flow, user use behavior and user value data, and totally adds 24 attributes, and performs special scene optical network resource flow estimation for the first time from the angle of the association relation between the startup user and the flow brought by the startup user. The relation of the real flow brought by the boot users (including broadband and ITV) is set as a coefficient by utilizing the signed bandwidth of the boot users hung under each type of ports of the OLT equipment and the use flow of each type of ports, the boot rate under a specific scene is associated, and the downlink flow average value, the downlink flow peak value, the uplink flow average value and the uplink flow peak value of each type of ports are output to realize the prediction of the network flow of the optical network equipment. In addition, the method can provide a method for judging whether the network equipment and the ports meet the requirements of users in a specific scene; the network planning can be realized according to the number, the user perception is good after the network is accelerated, and the important communication is effectively ensured; and, make the network resource of the optical network investment accurate, the targeted dilatation in advance, promote user's perception. The technical scheme of the present disclosure has been applied in the telecommunications annual rolling planning and the scenes of national celebration, spring festival, large reader, 200M liter 400M, etc., and has been applied in each specific scene such as epidemic situation.

It is noted that the above-described figures are only schematic illustrations of processes involved in a method according to an exemplary embodiment of the invention, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.

Further, referring to fig. 3, in this exemplary embodiment, there is further provided an optical network resource estimating apparatus 30, including: the system comprises a historical data acquisition module 301, a data preprocessing module 302, a threshold parameter configuration module 303 and an estimated processing module 304. Wherein,

The historical data collection module 301 may be configured to collect historical data of a preset statistical period as a pre-estimated sample; wherein the estimated samples include OLT data and PON data.

The data preprocessing module 302 may be configured to preprocess the estimated sample to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data, PON intermediate data.

The threshold parameter configuration module 303 may be configured to configure an activity rate threshold of the target scene; wherein the activity rate threshold comprises a wideband activity rate increment and an ITV activity rate threshold.

The pre-estimation processing module 304 may be configured to determine an optical network traffic pre-estimation result based on the intermediate data, the activity rate threshold, and an association relationship between a startup user and traffic brought by the startup user; wherein, the optical network flow estimation result includes: any one or a combination of any multiple of a downlink flow average value predicted value, a downlink flow peak value predicted value, an uplink flow average value predicted value and an uplink flow peak value predicted value.

In this exemplary embodiment, the OLT data includes: first device configuration data, first device bandwidth traffic data, first user usage behavior data, and user value data;

In this exemplary embodiment, acquiring OLT intermediate data includes: taking an OLT device as a unit, respectively accumulating up-down bandwidth capacity of all links, signing bandwidth of each service of each user of the down-hanging user and calculating the open probability to obtain OLT data intermediate data; the OLT intermediate data includes: any one or a combination of any multiple of the downlink capacity of the total bandwidth of the OLT, the uplink capacity of the total bandwidth of the OLT, the downlink contracted total bandwidth of the broadband of the underhung user, the uplink contracted total bandwidth of the broadband of the underhung user, the ITV total bandwidth of the underhung user, the increment broadband user number and the increment ITV user number.

In the present exemplary embodiment, acquiring PON intermediate data includes: taking a PON port as a unit, respectively accumulating the contracted bandwidths of the services of each user of the down-hanging user, and calculating the opening probability of each service to obtain PON intermediate data; wherein, the PON intermediate data comprises: any one or a combination of any of the broadband subscription total bandwidth of the down subscriber, the ITV total bandwidth of the down subscriber, the incremental broadband user number, and the incremental ITV user number.

In this exemplary embodiment, the threshold parameter configuration module 303 may configure the activity rate threshold of at least one group of the target scenes based on the statistics of the specified period history data.

In this exemplary embodiment, the pre-estimation processing module 304 may determine a downlink traffic average value predicted value based on the intermediate data, the activity rate threshold, and an association relationship between the power-on user and traffic brought by the power-on user, including:

Calculating a first coefficient based on a downlink flow average value calculated by signing a downlink bandwidth total of the starting equipment and based on a plurality of statistical period data; the starting-up equipment signed-up downlink bandwidth sum comprises starting-up broadband signed-up downlink bandwidth sum and starting-up ITV signed-up downlink bandwidth sum;

In this exemplary embodiment, the pre-estimation processing module 304 may determine an uplink traffic average value predicted value based on the intermediate data, the activity rate threshold, and an association relationship between the power-on user and traffic brought by the power-on user, including:

In this exemplary embodiment, the pre-estimation processing module 304 may determine a downstream traffic peak value predicted value based on the intermediate data, the activity rate threshold, and an association relationship between the power-on user and traffic brought by the power-on user, including:

calculating a third coefficient based on the total signed downlink bandwidth of the starting equipment and the downlink flow peak value calculated based on the data of a plurality of statistical periods; the starting-up equipment signed-up downlink bandwidth sum comprises starting-up broadband signed-up downlink bandwidth sum and starting-up ITV signed-up downlink bandwidth sum;

In this exemplary embodiment, the pre-estimation processing module 304 may determine an upstream traffic peak value predicted value based on the intermediate data, the activity rate threshold, and an association relationship between the power-on user and traffic brought by the power-on user, including:

The specific details of each module in the above-mentioned optical network resource estimating device are already described in detail in the corresponding optical network resource estimating method, so that the details are not repeated here.

It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.

In an exemplary embodiment of the present disclosure, a computer system capable of implementing the above method is also provided.

Those skilled in the art will appreciate that the various aspects of the invention may be implemented as a system, method, or program product. Accordingly, aspects of the invention may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.

A terminal device 400 according to this embodiment of the present invention is described below with reference to fig. 4. The terminal device 400 shown in fig. 4 is only an example, and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

As shown in fig. 4, the terminal device 400 is in the form of a general purpose computing device. The components of terminal device 400 may include, but are not limited to: the at least one processing unit 610, the at least one memory unit 620, and a bus 630 that connects the various system components, including the memory unit 620 and the processing unit 610.

Wherein the storage unit stores program code that is executable by the processing unit 610 such that the processing unit 610 performs steps according to various exemplary embodiments of the present invention described in the above-described "exemplary methods" section of the present specification. For example, the processing unit 610 may perform the steps as shown in fig. 1.

The storage unit 620 may include readable media in the form of volatile storage units, such as Random Access Memory (RAM) 6201 and/or cache memory unit 6202, and may further include Read Only Memory (ROM) 6203.

The storage unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.

Bus 630 may be a local bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or using any of a variety of bus architectures.

The computer system 600 may also communicate with one or more external devices 50 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the computer system 600, and/or any devices (e.g., routers, modems, etc.) that enable the computer system 600 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 650. The display unit 640 may also be connected through an input/output (I/O) interface 650. Moreover, computer system 600 may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through network adapter 660. As shown, network adapter 660 communicates with other modules of computer system 600 over bus 630. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with computer system 600, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, a computer-readable storage medium having stored thereon a program product capable of implementing the method described above in the present specification is also provided. In some possible embodiments, the various aspects of the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the invention as described in the "exemplary methods" section of this specification, when said program product is run on the terminal device.

Referring to fig. 5, a program product 500 for implementing the above-described method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).

Furthermore, the above-described drawings are only schematic illustrations of processes included in the method according to the exemplary embodiment of the present invention, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An optical network resource estimation method is characterized by comprising the following steps:

2. The method for optical network resource estimation according to claim 1, wherein the OLT data includes: first device configuration data, first device bandwidth traffic data, first user usage behavior data, and user value data;

3. The method for optical network resource estimation according to claim 1, wherein obtaining OLT intermediate data comprises:

Taking an OLT device as a unit, respectively accumulating up-down bandwidth capacity of all links, signing bandwidth of each service of each user of the down-hanging user and calculating the open probability to obtain OLT data intermediate data; the OLT intermediate data includes: any one or a combination of any multiple of the downlink capacity of the total bandwidth of the OLT, the uplink capacity of the total bandwidth of the OLT, the downlink contracted total bandwidth of the broadband of the underhung user, the uplink contracted total bandwidth of the broadband of the underhung user, the ITV total bandwidth of the underhung user, the increment broadband user number and the increment ITV user number.

4. The method for optical network resource estimation according to claim 1, wherein obtaining PON intermediate data comprises:

5. The method for optical network resource estimation according to claim 1, wherein the configuring the activity threshold of the target scene includes:

6. The method for estimating optical network resources according to claim 1, wherein determining the downstream traffic average value based on the intermediate data, the activity threshold, and the association relationship between the power-on user and traffic brought by the power-on user comprises:

7. The method for estimating optical network resources according to claim 1, wherein determining an upstream traffic average value estimated based on the intermediate data, the activity threshold, and an association relationship between a boot user and traffic brought by the boot user, comprises:

8. The method for estimating optical network resources according to claim 1, wherein determining the downstream traffic peak value estimated value based on the intermediate data, the activity rate threshold, and the association relationship between the power-on user and traffic brought by the power-on user comprises:

9. The method for estimating optical network resources according to claim 1, wherein determining an upstream traffic peak value estimated value based on the intermediate data, the activity rate threshold, and an association relationship between a power-on user and traffic brought by the power-on user, comprises:

10. An optical network resource estimation device, characterized in that the device comprises:

The pre-estimation processing module is used for determining an optical network flow pre-estimation result based on the intermediate data, the activity rate threshold value and the association relation between the startup user and the flow brought by the startup user; wherein, the optical network flow estimation result includes: any one or a combination of any multiple of a downlink flow average value predicted value, a downlink flow peak value predicted value, an uplink flow average value predicted value and an uplink flow peak value predicted value.

11. A storage medium having stored thereon a computer program which when executed by a processor implements the optical network resource estimation method according to any one of claims 1 to 9.

12. A terminal device, comprising:

A processor; and

A memory for storing executable instructions of the processor;

Wherein the processor is configured to perform the optical network resource estimation method of any one of claims 1 to 9 via execution of the executable instructions.