CN114338532A

CN114338532A - Optical network resource estimation method and device, storage medium and terminal equipment

Info

Publication number: CN114338532A
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: 2022-04-12
Anticipated expiration: 2041-12-30
Also published as: CN114338532B

Abstract

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

Description

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

Technical Field

The present disclosure relates to the field of communications technologies, and in particular, to an optical network resource estimation method, an optical network resource estimation device, a storage medium, and a terminal device.

Background

With the rapid development of internet technology, the demand of users on internet speed is increasing when using the internet. At present, the number of internet users is relatively stable, and the number of general network users can not change obviously; but the stock users, namely the users with the broadband and the ITV, have the conditions that part of users surf the internet daily and have low startup rate or are not started; however, there is a case that the open rate is increased sharply in some special dates or scenes, and the ITV stuck phenomenon occurs due to the limitation of the bandwidth of the optical network resources. Therefore, it is necessary to estimate network capacity, especially optical network resources, accurately in advance to meet the network requirement change of users.

It is to be noted that the information disclosed in the above background section is only for enhancement of 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 present disclosure aims to provide an optical network resource estimation method, an optical network resource estimation device, a storage medium, and a terminal device, which can realize estimation of optical network resources, and further overcome at least to some extent the defects caused by the limitations and defects of the related art.

Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by 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 an estimated sample; the pre-estimated sample comprises OLT data and PON data;

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

configuring an activity rate threshold of a target scene; wherein the activity threshold comprises a wideband activity incremental value and an ITV activity threshold;

determining an optical network traffic estimation result based on the intermediate data, the active rate threshold value and the incidence relation between the startup user and the traffic brought by the startup user; wherein the optical network traffic estimation result comprises: any one item or combination of any multiple items in the downlink flow average value estimated value, the downlink flow peak value estimated value, the uplink flow average value estimated value and the uplink flow peak value estimated 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 comprises: second device configuration data, second device bandwidth traffic data, second user usage behavior data, and second user value data.

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

respectively accumulating the uplink and downlink bandwidth capacities of all links, the signed bandwidth of each service of each user of a downlink user and calculating the on-time rate by taking one OLT device as a unit to obtain OLT data intermediate data; the OLT intermediate data comprises: the downlink capacity of the total bandwidth of the OLT link, the uplink capacity of the total bandwidth of the OLT link, the downlink signed total bandwidth of the broadband of the downlink user, the uplink signed total bandwidth of the broadband of the downlink user, the total bandwidth of the ITV of the downlink user, the number of the incremental broadband users and the number of the incremental ITV users.

In an exemplary embodiment of the present disclosure, acquiring PON intermediate data includes:

respectively accumulating the signed bandwidth of each service of each user of the down-hanging user by taking a PON port as a unit, and calculating the operation rate of each service to obtain PON middle data; wherein the PON intermediate data comprises: any one or any combination of a plurality of broadband signed total bandwidth of the user to be hung down, ITV total bandwidth of the user to be hung down, the number of incremental broadband users and the number of incremental ITV users.

In an exemplary embodiment of the present disclosure, the configuring an activity threshold of a target scenario includes:

configuring an activity threshold for at least one set of the target scenes based on statistics of historical data for a specified period of time.

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

determining the sum increment of downlink signed bandwidths according to the threshold value of the activity rate; the downlink signed 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-up equipment and a downlink flow average value calculated based on a plurality of statistical period data; the starting-up equipment signed downlink bandwidth sum comprises a starting-up broadband signed downlink bandwidth sum and a starting-up ITV signed downlink bandwidth sum;

determining a downlink flow mean value added value according to the first coefficient and the downlink signed bandwidth sum increment;

and determining the downlink flow mean value pre-estimated value based on the downlink flow mean value added value and the downlink flow mean value calculated based on a plurality of statistical period data.

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

counting the bandwidth uplink sum increment according to the broadband activity rate increment;

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

calculating an uplink flow direction mean value added value according to the second coefficient and the broadband uplink sum increment;

and determining an uplink flow mean value pre-estimated value based on the uplink flow mean value added value and an uplink flow mean value calculated based on a plurality of statistical period data.

In an exemplary embodiment of the present disclosure, determining a predicted value of a peak downlink traffic value based on the intermediate data, the activity threshold, and an association relationship between a 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-up equipment and the downlink flow peak value calculated based on the data of a plurality of statistical periods; the starting-up equipment signed downlink bandwidth sum comprises a starting-up broadband signed downlink bandwidth sum and a starting-up ITV signed downlink bandwidth sum;

determining a downlink flow peak value added value according to the third coefficient and the downlink signed bandwidth sum increment;

and determining the downlink flow peak value pre-estimated value based on the downlink flow peak value added value and the downlink flow peak value calculated based on a plurality of statistical period data.

In an exemplary embodiment of the present disclosure, determining an upstream traffic peak estimation value based on the intermediate data, the activity 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 startup broadband signed uplink bandwidth;

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

and determining an upstream flow peak value estimated value based on the upstream flow peak value added value and an upstream flow peak value 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 pre-estimation apparatus, including:

the historical data acquisition module is used for acquiring historical data of a preset statistical period as an estimated sample; the pre-estimated sample comprises OLT data and PON data;

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

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

the pre-estimation processing module is used for determining an optical network traffic pre-estimation result based on the intermediate data, the active rate threshold value and the incidence relation between the startup user and the traffic brought by the startup user; wherein the optical network traffic estimation result comprises: any one item or combination of any multiple items in the downlink flow average value estimated value, the downlink flow peak value estimated value, the uplink flow average value estimated value and the uplink flow peak value estimated 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-mentioned 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 perform the above optical network resource prediction method via execution of the executable instructions.

In the method for estimating the optical network resources provided by an embodiment of the present disclosure, OLT data and PON data are collected as sample data, and are preprocessed to obtain OLT intermediate data and PON intermediate data; and after configuring an active rate threshold of a target scene, determining an optical network traffic estimation result based on the intermediate data, the active rate threshold and an incidence relation between a starting user and traffic brought by the starting user. The method can carry out special scene optical network resource flow estimation from the angle of incidence relation between a starting user and the brought flow; and, the optical network traffic prediction result comprises: the downlink flow mean value pre-estimated value, the downlink flow peak value pre-estimated value, the uplink flow mean value pre-estimated value and the uplink flow peak value pre-estimated value can realize accurate pre-estimation of 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 present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.

Fig. 1 schematically illustrates a schematic diagram of a method for pre-estimating optical network resources in an exemplary embodiment of the disclosure;

fig. 2 schematically illustrates 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 pre-estimating apparatus in 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. Example embodiments may, however, be embodied in many different 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 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 their repetitive description 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 the form of 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, at present, although the number of internet users tends to be saturated, and the number of users has no obvious increment, the existing users, namely users with broadband and ITV, have the conditions that part of users surf the internet daily, the power-on rate is not high, or the users are not started. However, in some special holidays, such as big soldiers, thirty years and other special scenes, the users who start and surf the internet are in sharp increase, that is, the users who start the computer suddenly increase the scenes. Particularly, the daily ITV film watching user group is mainly the old, the starting rate is low, but the film watching users are steeply increased when reading the soldiers and late thirty spring years, namely, the starting rate is steeply increased. Due to the problem of limited network resource bandwidth of an optical network, an ITV is often stuck, a fault occurs in an important communication scene, user perception is particularly poor, and a large number of user reports occur when a large number of people read in a certain area in a certain year. In addition, according to the national uniform deployment requirement, in recent years, operators frequently increase the speed of the user network, and there is a speed increasing scene that the bandwidth of the user is not increased. Although operators are constantly speeding up user networks, users often claim that speed up is slower, also due to limited device bandwidth capabilities. The above scenarios are all characterized in that "the number of users is not increased but the traffic of the users is increased", that is, the device ports do not need to be increased, but the device bandwidth is occupied. In order to meet increasing user demands and improve user perception, accurate estimation of network capacity, particularly optical network resources, needs to be performed on a specific scene in advance. The specific scene is that resource estimation of the device bandwidth capacity is required due to the change of the user using behavior, so that the using flow brought by each user when accessing the internet and watching the video service is required to be obtained. The current approaches to obtain flow are: the DPI (Deep Packet Inspection, Packet-based Deep Inspection technology) collects traffic of a single user and a single application, traffic of a user level, that is, an ONU device, collected by a network manager, or ticket traffic on an AAA (Authentication, Authorization, and Accounting) service. However, at present, the DPI acquires the traffic of each application of each user, and needs the DPI to perform full-splitting, acquisition, and analysis on the whole network, but needs to perform full-splitting deployment on the network, which requires several tens of millions of capital investment, so the DPI cannot acquire the traffic of each application of each user of the whole network at present. The AAA bill statistics is the accumulated flow between the online and the disconnected network, even if the optical modem is not turned off (90% of users do not turn on or off the optical modem), the network is set to automatically disconnect the network within 48 hours, so the AAA bill statistics is the accumulated flow of the online bill every 2 days, and is not the instantaneous flow.

In view of the above disadvantages and shortcomings in the prior art, the present exemplary embodiment provides a method for estimating optical network resources, which can estimate the demand for optical network resources. Referring to fig. 1, the method for estimating the optical network resources may include the following steps:

s11, collecting historical data of a preset statistical period as an estimated sample; the pre-estimated sample comprises OLT data and PON data;

s12, preprocessing the pre-estimated sample to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data and PON intermediate data; and

s13, configuring an activity rate threshold of the target scene; wherein the activity threshold comprises a wideband activity incremental value and an ITV activity threshold;

s14, determining an optical network traffic estimation result based on the intermediate data, the activity threshold and the incidence relation between the startup user and the traffic brought by the startup user; wherein the optical network traffic estimation result comprises: any one item or combination of any multiple items in the downlink flow average value estimated value, the downlink flow peak value estimated value, the uplink flow average value estimated value and the uplink flow peak value estimated value.

In the method for estimating optical network resources provided by the present exemplary embodiment, OLT data and PON data are collected as sample data, and are preprocessed to obtain OLT intermediate data and PON intermediate data; and after configuring an active rate threshold of a target scene, determining an optical network traffic prediction result based on the intermediate data and the active rate threshold. The method can carry out special scene optical network resource flow estimation from the angle of incidence relation between a starting user and the brought flow; and, the optical network traffic prediction result comprises: the downlink flow mean value pre-estimated value, the downlink flow peak value pre-estimated value, the uplink flow mean value pre-estimated value and the uplink flow peak value pre-estimated value can realize accurate pre-estimation of network flow of the optical network equipment.

Hereinafter, the steps of the optical network resource estimation method in the present exemplary embodiment will be described in more detail with reference to the drawings and the embodiments.

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

In this exemplary embodiment, the method described above may be executed on the server side, or may be implemented by cooperation between the user terminal and the server side. For example, a user may send a data estimation request to a server at a user terminal; the data estimation request may include a time period to be subjected to optical network resource estimation, a network area, hardware device data, and the like. For example, a user desires to evaluate network requirements for area a and area B during an eleven vacation. After receiving the data estimation request, the server end 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 downstream to an OLT (Optical Line Terminal) device 202, and the OLT device 202 is connected to a plurality of ONU (Optical Network Unit) devices 204 through an Optical splitter 203. Two types of port data on optical access network equipment (OLT) can be extracted from a network manager of the OLT, namely uplink port data, namely uplink and downlink flow peak value and flow mean value data of an OLT uplink total link, are collected through BRAS equipment; and, the downstream port data, i.e. the upstream and downstream flow direction peak value and the flow average value data of a PON (Passive Optical Network) port. In addition, the user signed bandwidth data hung under each PON port on the OLT equipment can be extracted from the AAA platform. For example, the duration of one statistical period may be configured to be one week; historical data for a plurality of continuous periods can be collected as estimation samples.

In this exemplary embodiment, in the above 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 comprises: 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 the following fields, including: basic information of OLT equipment, uplink configuration of the OLT equipment, bandwidth of the OLT equipment and use behavior of OLT users. The basic information of the OLT equipment can comprise time, OLT IP, branch company and OLT name; the uplink configuration of the OLT apparatus may include: a single uplink downlink bandwidth OLT-single link-Band-down, a single uplink bandwidth OLT-single link-Band-up, a used port number OLT-user-num and a total port number All-port-num. The OLT device bandwidth may include: an OLT downlink flow average value, an OLT uplink flow average value, an OLT downlink flow peak value and an OLT uplink flow peak value. The user usage behavior data may include: the number of broadband users hanging under the OLT, the number of OLT broadband startup users ONU-on-Num-Band, the number of OLT ITV users hanging under the OLT, and the number of OLT-ITV startup users ONU-on-Num-ITV.

The collected PON port data may contain data of the following fields, including: basic information of PON equipment, configuration of the PON equipment, bandwidth of the PON equipment and use behaviors of PON users. The PON device basic information may include: time, OLT IP, OLT-PON port, branch company, OLT name. The PON device configuration information may include: PON port total bandwidth capability. The PON device bandwidth information may include: the mean value of the downstream flow of the PON port, the mean value of the upstream flow of the PON port, the peak value of the downstream flow of the PON port and the peak value of the upstream flow of the PON port. The PON user usage behavior information may include: number of PON port broadband user, number of PON port broadband startup user, number of PON port ITV user, and number of PON port-ITV startup users

Further, the user value data may contain data for the following fields, including: broadband account number, signed broadband downlink bandwidth sign-band _ Down, signed broadband uplink bandwidth sign-band _ Up and ITV business type sign-ITV _ Down.

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

In this exemplary embodiment, after obtaining the estimated sample data, the estimated sample data may be preprocessed to obtain corresponding intermediate data. Specifically, for the OLT intermediate data, the uplink and downlink bandwidth capabilities of all links, the contracted bandwidth of each service of each user of the drop-on user, and the startup rate may be respectively accumulated by using one OLT device as a unit to obtain the OLT data intermediate data; the OLT intermediate data comprises: the downlink capacity of the total bandwidth of the OLT link, the uplink capacity of the total bandwidth of the OLT link, the downlink signed total bandwidth of the broadband of the downlink user, the uplink signed total bandwidth of the broadband of the downlink user, the total bandwidth of the ITV of the downlink user, the number of the incremental broadband users and the number of the incremental ITV users. Referring to table 1, an OLT intermediate data table may be generated.

TABLE 1

The OLT link total bandwidth downlink capacity OLT-Band-all-down is the single uplink downlink bandwidth OLT-singlink-Band-down, and the used port number OLT-user-num;

the total bandwidth uplink capacity OLT-Band-all-up of the OLT link is equal to the uplink bandwidth OLT-single link-Band-up of the single uplink, and the number of used ports OLT-user-num is equal to the number of the used ports OLT-user-num;

a broadband downlink contracted total bandwidth ONU-Band-all-Down ═ sigma (sign-Band _ Down) of a downlink user;

and the ITV total bandwidth ONU-ITV-all of the user to be hung is sigma (sign-ITV _ Down).

Specifically, for PON intermediate data, the signed bandwidths of each service of each user of the off-hook user may be respectively accumulated and the service availability ratio of each service may be calculated in units of one PON port to obtain PON intermediate data; wherein the PON intermediate data comprises: any one or any combination of a plurality of broadband signed total bandwidth of the user to be hung down, ITV total bandwidth of the user to be hung down, the number of incremental broadband users and the number of incremental ITV users. Referring to table 2, a PON intermediate data table may be generated.

TABLE 2

In step S13, configuring an activity threshold of the target scene; wherein the activity threshold comprises a wideband activity incremental value and an ITV activity threshold.

In this example embodiment, the activity threshold of at least one group of the target scenes may be configured based on statistics of historical data over a specified period of time. Specifically, for a sudden increase scene of a startup user, in order to obtain the number of active users increased by a broadband and the number of active users increased by an ITV, an estimated scene threshold value needs to be set, and the threshold value includes an increase value of the broadband activity rate and an ITV activity rate threshold value. For example, according to data of a current year or a same scene, the method mainly sets two threshold scenes for an ITV active steep-rise scene (such as thirty years, a big reader, and the like). In a first scenario, the increment of the threshold value on the broadband activity rate is set to be 10%, and the ITV activity rate threshold value is set to be 80%; the increment of the scene two threshold value to the broadband activity rate is set to be 10%, and the ITV activity rate threshold value is set to be 100%. In addition, for the speed-up scene, the change of the signed bandwidth of the off-hook user before and after is directly calculated without setting a threshold value, and the increment of the signed bandwidth is obtained.

Alternatively, in some exemplary embodiments, the user may configure the broadband activity incremental value and the ITV activity threshold based on empirical values. Or, the comparison of the number of active users can be performed according to a plurality of statistical cycles of the same month in different years, and the broadband activity increment and the ITV activity threshold 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 threshold, and an association relationship between the startup user and traffic brought by the startup user; wherein the optical network traffic estimation result comprises: any one item or combination of any multiple items in the downlink flow average value estimated value, the downlink flow peak value estimated value, the uplink flow average value estimated value and the uplink flow peak value estimated value.

In the present exemplary embodiment, since the occupied bandwidth of the ITV has a fixed value characteristic, and the coverage areas of the OLT (typically 2000 multiple users) and the PON (60 users are suspended under the MAX), the audience user groups are substantially similar, so that the traffic brought by the internet access behavior of the ITV is considered to be substantially consistent. By utilizing the characteristics, the use flow relation of the ports caused by the total signed bandwidth of the on-hook users under various ports is calculated, namely the use flow of various ports is divided by the total signed bandwidth of the on-hook users under the ports, and the use flow caused by each signed bandwidth under each port is obtained.

Specifically, in this exemplary embodiment, determining a mean value of downlink traffic prediction value based on the intermediate data, the activity threshold, and an association relationship between a power-on user and traffic brought by the power-on user includes:

step S211, determining the downlink signed bandwidth sum increment according to the active rate threshold; the downlink signed 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 signed downlink bandwidths of the starting-up equipment and the downlink flow average value calculated based on a plurality of statistical period data; the starting-up equipment signed downlink bandwidth sum comprises a starting-up broadband signed downlink bandwidth sum and a starting-up ITV signed downlink bandwidth sum;

step S213, determining the mean increase value of the downlink traffic according to the first coefficient and the downlink signed bandwidth sum increment;

step S214, determining the downlink traffic mean pre-estimated value based on the downlink traffic mean added value and the downlink traffic mean calculated based on the plurality of statistical period data.

Specifically, the increment of the sum of the downlink contracted bandwidths may be calculated first. For the sudden increase scene of the starting user, the signed bandwidth increment is calculated by the following formula:

a broadband downlink sum increment (BAND _ incr _ down) — a default broadband downlink contracted bandwidth (100M: modifiable) x number of active users with increased broadband;

an ITV downlink sum increment (ITV _ incr _ down) — a default number of active users for increasing the ITV downlink contracted bandwidth (16M) x ITV;

the number of active users increased by the broadband is equal to the total number of users of the equipment under-hung broadband and multiplied by the active rate of the broadband; according to the past scene, the value of the broadband activity rate is increased by 10%;

the number of the active users increased by the ITV is equal to the total number of the users of the ITV hung below the device multiplied by the active rate of the ITV; for example, according to past scenarios, the ITV activity threshold is set to 80% or 100%;

the ITV activity increment is the average value of the ITV activity threshold value-the ITV activity in the previous 8 periods;

for the speed-up scene, the change condition before and after the signed bandwidth of the off-hook user can be directly calculated.

Then, a calculation of the coefficients, i.e. the usage traffic brought per contracted bandwidth, may be performed. To represent the relationship between the user who boots up each type of port and the traffic brought by the user, it can be referred to as DOWN _ r1, and is used as a coefficient for calculating the mean increase value of the downstream traffic, and the calculation formula is as follows:

starting up the broadband signed downlink bandwidth sum which is the broadband signed downlink bandwidth sum multiplied by the broadband open-time rate;

starting-up ITV signed downlink bandwidth sum (ITV signed downlink bandwidth sum multiplied by ITV open-time rate)

DOWN _ r1 ═ ADS _ tmp _ DOWN/(sum of signed downstream bandwidths for power-on broadband + sum of signed downstream bandwidths for power-on ITV);

the ADS _ tmp _ DOWN represents an average value of downlink flow averages in historical data in a plurality of continuous statistical periods, and data are acquired from a network manager of the OLT equipment.

Then, the downlink flow mean increase value p _ ADS _ DOWN can be calculated; the calculation formula may include:

p _ ADS _ DOWN ═ DOWN _ r1 × (wideband downlink sum increment BAND _ incr _ DOWN _ + ITV downlink sum increment ITV _ incr _ DOWN _);

then, a downlink flow mean estimate (e _ ADS _ DOWN) may be calculated; wherein the content of the first and second substances,

e_ADS_DOWN＝p_ADS_DOWN+ADS_tmp_DOWN。

specifically, in this exemplary embodiment, determining an uplink traffic mean value estimated value based on the intermediate data, the activity threshold, and the association relationship between the startup user and its brought traffic includes:

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

step S222, determining a second coefficient based on the uplink flow average value calculated by the plurality of statistical period data and the sum of the signed uplink bandwidth of the starting-up broadband;

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

and step S224, determining an uplink flow mean value pre-estimated value based on the uplink flow mean value increment value and the uplink flow mean value calculated based on a plurality of statistical period data.

For example, because there is no uplink contracted bandwidth due to the ITV service characteristics, the uplink traffic mean value estimation only needs to consider the broadband service. First, an increment of the sum of the upstream contracted bandwidths may be calculated. For a boot user ramp-up scenario, the calculation formula of the signed bandwidth increment may include:

broadband uplink sum increment (BAND _ incr _ up) — default broadband uplink contracted bandwidth (20M: modifiable) x number of active users with increased broadband;

the number of active users increased by the broadband is equal to the total number of users of the equipment under-hung broadband and multiplied by the active rate of the broadband; for example, the broadband activity increase may be 10% in a broadband activity steep increase scenario;

for the speed-up scene, the change condition before and after the signed bandwidth of the user to be hung is directly calculated.

Then, coefficient calculations, i.e. usage traffic per contracted bandwidth, may be performed. To show the relationship between each device power-on user and the traffic it brings, we will refer to it as UP _ r1, as a coefficient for calculating the average increase value of the uplink traffic, and the calculation formula may include:

starting up the broadband signed uplink bandwidth sum which is the broadband signed uplink bandwidth sum multiplied by the broadband open-time rate;

UP _ r1 is ADS _ tmp _ UP/startup broadband contracted uplink bandwidth sum;

the ADS _ tmp _ UP represents an average value of historical data uplink flow average values of a plurality of continuous statistical periods, and data are collected from a PON network manager of the equipment OLT.

Then, the uplink traffic mean increase value p _ ADS _ up may be calculated, and the calculation formula may include:

p _ ADS _ UP _ UP _ r1 × broadband uplink sum increment BAND _ incr _ UP

Then, an upstream flow mean 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 a predicted value of a peak downlink traffic value based on the intermediate data, the activity threshold, and an association relationship between a startup user and traffic brought by the startup user includes:

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

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

step S233, determining the peak value increment of the downlink flow according to the third coefficient and the sum increment of the downlink signed bandwidth;

step S234, determining the predicted value of the downlink traffic peak based on the increased value of the downlink traffic peak and the downlink traffic peak calculated based on the multiple statistical period data.

Specifically, in this exemplary embodiment, determining an upstream traffic peak estimation value based on the intermediate data, the activity threshold, and the association relationship between the startup user and the traffic brought by the startup user includes:

step S241, counting the bandwidth uplink sum increment according to the 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 startup broadband signed uplink bandwidth;

step S243, calculating the increasing value of the upstream flow direction peak value according to the fourth coefficient and the broadband upstream sum increment;

in step S244, an upstream peak prediction value is determined based on the upstream peak increment value and the upstream peak calculated based on the plurality of statistical period data.

In some exemplary embodiments, the method provided by the present disclosure estimates the uplink port traffic of the OLT during national celebration. First, the coefficient was calculated as historical data for data of 8 weeks before the holiday in the national day. Considering that part of students leave a holiday and return to the country in the national celebration holiday, the number of active users is higher than that of September, but the number of active users in summer holidays is not higher than that of higher users, and therefore 8.12 data of the number of active users in summer holidays and the like are taken as basic data. The new national day traffic is accumulated on the 8.12 cycle data.

Then, two pairs of threshold values are set for comparison and estimation, and the two pairs are respectively a scene threshold value pair: the increment of the broadband activity rate is 10 percent, and the threshold value of the ITV activity rate is 80 percent; scene two threshold pairs: the value of the broadband active rate is increased by 10%, the ITV active rate threshold value is 100%, the calculation is not carried out when the value exceeds the threshold value, and the value is directly increased to the threshold value when the value is lower than the threshold value. And outputting the result. The estimated results are as follows: the average value and the peak ratio of the uplink busy hours output by the threshold values of the two scenes are lower, and the ratio of the uplink traffic peak value resources of 1 OLT is less than 30% except that the ratio of the uplink traffic peak value resources of the OLT exceeds 30% (Yongchuan x.x.x is 38%). In the first scenario, 6 OLTs exist when the ratio of the average value of the downlink busy hour exceeds 60%, 29 OLTs exist when the ratio of the average value of the downlink busy hour exceeds 70%, 11 OLTs exist when the ratio of the average value of the downlink busy hour exceeds 60%, and 35 OLTs exist when the ratio of the average value of the downlink busy hour exceeds 70%, as shown in table 3.

TABLE 3

For scenario 1, 29 downlink peak occupancy exceeds 70%, and 13 OLTs are configured with only 1 link. As shown in table 4.

TABLE 4

For scenario two, there are 35 OLTs with a downstream peak ratio exceeding 70%, and only 1 link is configured for 17 OLTs, as shown in table 5.

TABLE 5

According to the estimation 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 the equipment with more major users or users in the OLT with the busy hour mean value exceeding 60% and the peak value exceeding 70%.

And (4) considering the long-term use condition of the user, and finally performing network resource expansion optimization by adopting a scene-threshold value. And after festival, performing post evaluation on the traffic, and meeting the flow demand of the user during the national celebration by adopting a scene one estimation method.

According to the optical network resource estimation 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 a downlink flow mean value estimated value, a downlink flow peak value estimated value, an uplink flow mean value estimated value and an uplink flow peak value estimated value of various equipment ports of the optical network resources through a calculation algorithm based on the incidence relation between the startup user and the brought flow. The method utilizes four types of historical data of optical network resources, including equipment configuration, equipment bandwidth flow, user use behavior and user value data, and 24 attributes in total, and performs special scene optical network resource flow estimation from the perspective of incidence relation between a startup user and the flow brought by the startup user for the first time. By using the signed bandwidth of the startup user hung below each type of port of the equipment OLT and the use flow of each type of port, the relation of the real flow brought by the startup user (including the broadband and the ITV) is set as a coefficient, the startup rate under a specific scene is correlated, and the downlink flow mean value estimated value, the downlink flow peak value estimated value, the uplink flow mean value estimated value and the uplink flow peak value estimated value of each type of port are output, so that the network flow of the optical network equipment is estimated. In addition, the method can provide a method for judging whether the network equipment and the port meet the requirements of the user in a specific scene; the network planning has the advantages that the number of the network planning can be determined, the user perception is excellent after the network is accelerated, and important communication is effectively guaranteed; and the optical network resources can be invested accurately, the targeted capacity expansion is advanced, and the user perception is improved. The technical scheme disclosed by the invention is applied to scenes such as rolling planning in telecom years, national celebration, spring festival, big reading soldier, 200M liter 400M and the like, and is applied and verified in each specific scene such as epidemic situation.

It is to be noted that the above-mentioned figures are only schematic illustrations of the processes involved in the method according to an exemplary embodiment of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

Further, referring to fig. 3, in an embodiment of the present invention, there is provided an optical network resource predicting 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 estimation processing module 304. Wherein the content of the first and second substances,

the historical data acquisition module 301 may be configured to acquire historical data of a preset statistical period as an estimated sample; the pre-estimated samples comprise OLT data and PON data.

The data preprocessing module 302 may be configured to preprocess the pre-estimated samples to obtain intermediate data; wherein the intermediate data comprises: OLT intermediate data and PON intermediate data.

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

The estimation processing module 304 may be configured to determine an optical network traffic estimation result based on the intermediate data, the activity threshold, and an association relationship between a boot-up user and traffic brought by the boot-up user; wherein the optical network traffic estimation result comprises: any one item or combination of any multiple items in the downlink flow average value estimated value, the downlink flow peak value estimated value, the uplink flow average value estimated value and the uplink flow peak value estimated 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: respectively accumulating the uplink and downlink bandwidth capabilities of all links, the signed bandwidth of each service of each user of the off-hook user and calculating the on-time rate by taking one OLT device as a unit to obtain OLT data intermediate data; the OLT intermediate data comprises: the downlink capacity of the total bandwidth of the OLT link, the uplink capacity of the total bandwidth of the OLT link, the downlink signed total bandwidth of the broadband of the downlink user, the uplink signed total bandwidth of the broadband of the downlink user, the total bandwidth of the ITV of the downlink user, the number of the incremental broadband users and the number of the incremental ITV users.

In this exemplary embodiment, acquiring PON intermediate data includes: respectively accumulating the signed bandwidth of each service of each user of the down-hanging user by taking a PON port as a unit, and calculating the operation rate of each service to obtain PON middle data; wherein the PON intermediate data comprises: any one or any combination of a plurality of broadband signed total bandwidth of the user to be hung down, ITV total bandwidth of the user to be hung down, the number of incremental broadband users and the number of incremental ITV users.

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

In this exemplary embodiment, the estimation processing module 304 may determine a mean value of downlink traffic based on the intermediate data, the activity 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 signed downlink bandwidth sum of the starting equipment and a downlink flow average value calculated based on a plurality of statistical period data; the starting-up equipment signed downlink bandwidth sum comprises a starting-up broadband signed downlink bandwidth sum and a starting-up ITV signed downlink bandwidth sum;

In this exemplary embodiment, the estimation processing module 304 may determine an uplink traffic mean value estimated value based on the intermediate data, the activity threshold, and an association relationship between the startup user and its brought traffic, including:

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

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

In this exemplary embodiment, the estimation processing module 304 may determine an upstream traffic peak estimation value based on the intermediate data, the activity threshold, and an association relationship between the startup user and its brought traffic, including:

The details of each module in the optical network resource estimation device are described in detail in the corresponding optical network resource estimation method, and therefore are not described herein again.

It should be noted that although in the above detailed description several modules or units of the 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, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

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

As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally 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 bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 4, the terminal device 400 is embodied in the form of a general purpose computing device. The components of the 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 couples 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 to cause the processing unit 610 to perform steps according to various exemplary embodiments of the present invention as described in the above section "exemplary methods" 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 memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.

The memory 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 of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 630 may be 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 a local bus 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.), with one or more devices that enable a user to interact with the computer system 600, and/or with any devices (e.g., router, modem, etc.) that enable the computer system 600 to communicate with one or more other computing devices. Such communication may occur via 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 (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network such as the Internet) via network adapter 660. As shown, network adapter 660 communicates with the other modules of computer system 600 via bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with computer system 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, 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 (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

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

Referring to fig. 5, a program product 500 for implementing the above 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 in this regard and, in the present 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. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. 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 for aspects 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 and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, 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., through the internet using an internet service provider).

Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple 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 variations, 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 will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the terms of the appended claims.

Claims

1. A method for pre-estimating optical network resources is characterized in that the method comprises the following steps:

2. The method of claim 1, wherein the OLT data comprises: first device configuration data, first device bandwidth traffic data, first user usage behavior data, and user value data;

3. The method of claim 1, wherein the obtaining the OLT intermediate data comprises:

respectively accumulating the uplink and downlink bandwidth capabilities of all links, the signed bandwidth of each service of each user of the off-hook user and calculating the on-time rate by taking one OLT device as a unit to obtain OLT data intermediate data; the OLT intermediate data comprises: the downlink capacity of the total bandwidth of the OLT link, the uplink capacity of the total bandwidth of the OLT link, the downlink signed total bandwidth of the broadband of the downlink user, the uplink signed total bandwidth of the broadband of the downlink user, the total bandwidth of the ITV of the downlink user, the number of the incremental broadband users and the number of the incremental ITV users.

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

5. The method according to claim 1, wherein the configuring the activity threshold of the target scenario comprises:

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

7. The method for estimating optical network resources according to claim 1, wherein determining the predicted value of the mean uplink traffic based on the intermediate data, the activity threshold, and the association relationship between the boot-up user and the traffic brought by the boot-up user comprises:

8. The method for estimating optical network resources according to claim 1, wherein determining a predicted value of a peak downlink traffic value based on the intermediate data, the activity threshold, and an association relationship between a startup user and traffic brought by the startup user comprises:

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

10. An optical network resource pre-estimation device, the device comprising:

the pre-estimation processing module is used for determining an optical network traffic pre-estimation result based on the intermediate data, the activity rate threshold value and the incidence relation between the startup user and the traffic brought by the startup user; wherein the optical network traffic estimation result comprises: any one item or combination of any multiple items in the downlink flow average value estimated value, the downlink flow peak value estimated value, the uplink flow average value estimated value and the uplink flow peak value estimated value.

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