CN113784363A

CN113784363A - Machine room planning method and device based on service estimation and storage medium

Info

Publication number: CN113784363A
Application number: CN202111323870.9A
Authority: CN
Inventors: 蚁泽纯; 张优训; 刘小春; 张宇; 梁永红; 李�昊
Original assignee: Guangdong Planning and Designing Institute of Telecommunications Co Ltd
Current assignee: Guangdong Planning and Designing Institute of Telecommunications Co Ltd
Priority date: 2021-11-10
Filing date: 2021-11-10
Publication date: 2021-12-10
Anticipated expiration: 2041-11-10
Also published as: CN113784363B

Abstract

The invention discloses a method, a device and a storage medium for planning a machine room based on service estimation, wherein the method comprises the following steps: acquiring service basic data of a target area; the service basic data comprises user current data and/or future development data; determining the total bandwidth requirement of a predicted convergence layer of the target area in a target future time period according to the service basic data and a preset bandwidth calculation model; determining the expected machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area; and determining the planned number of the predicted convergence machine rooms of the target area in the target future time period according to the predicted total bandwidth demand of the convergence layer and the predicted machine room bearing bandwidth demand. Therefore, the method and the device can achieve a more accurate and more reasonable machine room construction estimation effect, are beneficial to more comprehensive machine room construction early-stage planning, and are beneficial to improving the efficiency of subsequent machine room construction and the effect of infrastructure construction.

Description

Machine room planning method and device based on service estimation and storage medium

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for planning a machine room based on service estimation, and a storage medium.

Background

Due to the development of communication equipment, the space and power requirements of the current high-end high-capacity equipment on a communication convergence machine room become higher, and in addition, the difficulty in selecting points of the machine room, complaints of surrounding residents and the like, the construction scheme of the convergence machine room needs to be more carefully considered, and more complex challenges are faced. In the construction of the existing convergence machine room, the future construction scheme of the convergence machine room is reasonably planned without considering the service requirement level and the development trend, and obviously, the defects of the prior art exist and the solution is needed urgently.

Disclosure of Invention

The technical problem to be solved by the invention is to provide a machine room planning method, device and storage medium based on service estimation, which can realize more accurate and more reasonable machine room construction estimation effect, facilitate more comprehensive machine room construction early-stage planning, and facilitate improvement of efficiency of subsequent machine room construction and infrastructure effect.

In order to solve the above technical problem, a first aspect of the present invention discloses a method for planning a machine room based on service estimation, where the method includes:

acquiring service basic data of a target area; the service basic data comprises user current data and/or future development data;

determining the total bandwidth requirement of a predicted convergence layer of the target area in a target future time period according to the service basic data and a preset bandwidth calculation model;

determining the expected machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area;

and determining the planned number of the predicted convergence machine rooms of the target area in the target future time period according to the predicted total bandwidth demand of the convergence layer and the predicted machine room bearing bandwidth demand.

As an optional implementation manner, in the first aspect of the present invention, the user presence data includes at least one of the number of opened home wide users, the number of opened subscriber collecting users, the existing number of LTE base stations, and the existing number of 5G base stations; the future development data comprises at least one of the number of expected family wide users, the number of expected customer collecting users, the number of expected LTE base stations and the number of expected 5G base stations.

As an optional implementation manner, in the first aspect of the present invention, the determining, according to the service basic data and a preset bandwidth calculation model, a predicted aggregate layer total bandwidth requirement of the target area in a target future time period includes:

determining the current bandwidth requirement of the target area according to the current user data and a preset bandwidth estimation rule;

determining future bandwidth requirements of the target area according to the future development data and the bandwidth estimation rule;

determining the total bandwidth demand of the target area in the target future time period according to the current bandwidth demand and the future bandwidth demand;

and determining the total bandwidth demand of the target region on the predicted convergence layer in the target future time period according to a preset bandwidth grading model and the total bandwidth demand of the predicted region.

As an optional implementation manner, in the first aspect of the present invention, the determining a predicted machine room bearer bandwidth requirement corresponding to a single aggregated machine room in the target area includes:

determining the current machine room bearing requirement and service development trend information corresponding to a single converged machine room in the target area;

and determining the predicted machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area according to the current machine room bearing requirement and the service development trend information.

As an optional implementation manner, in the first aspect of the present invention, the determining, according to the predicted aggregate layer total bandwidth requirement and the predicted machine room load bandwidth requirement, the predicted aggregate machine room planning number of the target area in the target future time period includes:

dividing the predicted total bandwidth requirement of the convergence layer by the predicted machine room bearing bandwidth requirement to obtain a calculation result;

and determining the calculation result as the predicted aggregate machine room planning number of the target area in the target future time period.

As an alternative implementation, in the first aspect of the present invention, the method further includes:

acquiring the current number of the converged machine rooms in the target area;

determining the predicted number of newly added machine rooms in the target area according to the difference between the predicted number of the aggregated machine rooms and the current number of the aggregated machine rooms;

and determining a machine room construction scheme corresponding to the target area according to the estimated number of the newly added machine rooms.

As an optional implementation manner, in the first aspect of the present invention, the determining, according to the estimated number of newly added machine rooms, a machine room construction scheme corresponding to the target area includes;

determining the machine room construction operation tendency of the target area;

and determining the machine room construction cost corresponding to the target area according to the machine room construction operation tendency, the estimated number of newly added machine rooms and the preset cost corresponding to different construction operations.

The second aspect of the present invention discloses a machine room planning device based on service estimation, which comprises:

the acquisition module is used for acquiring the service basic data of the target area; the service basic data comprises user current data and/or future development data;

the calculation module is used for determining the total bandwidth requirement of the expected convergence layer of the target area in the target future time period according to the service basic data and a preset bandwidth calculation model;

the determining module is used for determining the expected machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area;

and the planning module is used for determining the planned number of the predicted convergence machine rooms of the target area in the target future time period according to the predicted total bandwidth demand of the convergence layer and the predicted machine room bearing bandwidth demand.

As an optional implementation manner, in the second aspect of the present invention, the user presence data includes at least one of the number of opened home wide users, the number of opened subscriber collecting users, the existing number of LTE base stations, and the existing number of 5G base stations; the future development data comprises at least one of the number of expected family wide users, the number of expected customer collecting users, the number of expected LTE base stations and the number of expected 5G base stations.

As an optional implementation manner, in the second aspect of the present invention, the specific manner of determining the total bandwidth requirement of the aggregation layer expected in the target future time period in the target area according to the service basic data and a preset bandwidth calculation model by the calculation module includes:

As an optional implementation manner, in the second aspect of the present invention, a specific manner in which the determining module determines a load bandwidth requirement of an expected machine room corresponding to a single aggregated machine room in the target area includes:

As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the planning module determines the planned number of the predicted aggregated machine rooms of the target area in the target future time period according to the predicted aggregated layer total bandwidth requirement and the predicted machine room load bandwidth requirement includes:

As an optional implementation manner, in the second aspect of the present invention, the obtaining module is further configured to obtain a current number of the converged machine rooms in the target area; the calculation module is further to:

As an optional implementation manner, in the second aspect of the present invention, the calculating module determines, according to the estimated number of the newly added machine rooms, a specific manner of a machine room construction scheme corresponding to the target area, including;

The third aspect of the present invention discloses another machine room planning device based on service estimation, wherein the device comprises:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute part or all of the steps of the method for planning the machine room based on the service estimation disclosed by the first aspect of the embodiment of the invention.

A fourth aspect of the present invention discloses a computer storage medium, where the computer storage medium stores computer instructions, and when the computer instructions are called, the computer instructions are used to perform part or all of the steps in the method for planning a machine room based on service estimation disclosed in the first aspect of the embodiments of the present invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

in the embodiment of the invention, the business basic data of a target area is obtained; the service basic data comprises user current data and/or future development data; determining the total bandwidth requirement of a predicted convergence layer of the target area in a target future time period according to the service basic data and a preset bandwidth calculation model; determining the expected machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area; and determining the planned number of the predicted convergence machine rooms of the target area in the target future time period according to the predicted total bandwidth demand of the convergence layer and the predicted machine room bearing bandwidth demand. Therefore, the method and the device can estimate the estimated bandwidth requirement of the target area by combining the current and future service data, and further calculate the estimated planning number of the machine room, thereby realizing more accurate and more reasonable machine room construction estimation effect, being beneficial to more comprehensive machine room construction early-stage planning, and being beneficial to improving the efficiency of subsequent machine room construction and the effect of infrastructure construction.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic flow chart of a method for planning a machine room based on service estimation according to an embodiment of the present invention;

fig. 2 is a schematic structural diagram of a machine room planning apparatus based on service estimation according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of another equipment room planning apparatus based on service estimation according to an embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or article.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The invention discloses a machine room planning method, a device and a storage medium based on service estimation, which can estimate the predicted bandwidth requirement of a target area by combining current and future service data and further calculate the predicted machine room planning number, thereby realizing more accurate and more reasonable machine room construction estimation effect, being beneficial to more comprehensive machine room construction early-stage planning and being beneficial to improving the efficiency of subsequent machine room construction and the effect of infrastructure construction. The following are detailed below.

Before explaining the various embodiments in detail, the technical terms abbreviations appearing in the present detailed description are explained, wherein:

LTE: long Term Evolution, 3G, is a Long Term Evolution of UMTS (Universal Mobile Telecommunications System) technical standard organized and formulated by 3GPP (The 3rd Generation Partnership Project), and introduces key technologies such as OFDM (Orthogonal Frequency Division Multiplexing) and MIMO (Multi-Input and Multi-Output), which significantly increases spectral efficiency and data transmission rate.

PTN: packet Transport Network, Packet Transport Network technology.

IPRAN: the IP Radio Access Network is an end-to-end service bearer Network which is based on an IP/MPLS protocol and a key technology, mainly faces to mobile service bearer, gives consideration to providing service bearers of two or three layers of channels, and relies on a CN2 backbone layer to form a province unit.

OTN: an optical transport network refers to a transport network that implements transport, multiplexing, routing, and monitoring of service signals in an optical domain, and ensures performance index and survivability thereof.

OLT: optical line terminal for connecting terminal equipment of an optical fiber trunk.

BNG: broadband network gateway control device.

BRAS: the Broadband Remote Access Server is a novel Access gateway facing Broadband network application.

SR: service router, full service router.

Example one

Referring to fig. 1, fig. 1 is a schematic flow chart of a method for planning a machine room based on service estimation according to an embodiment of the present invention. The method described in fig. 1 may be applied to a corresponding planning terminal, planning device, or planning server, and the server may be a local server or a cloud server. Specifically, as shown in fig. 1, the method for planning a machine room based on service estimation may include the following operations:

101. and acquiring service basic data of the target area.

Optionally, the service basic data includes user presence data and/or future development data. Optionally, the user presence data includes at least one of the number of opened home wide users, the number of opened subscriber collecting users, the current number of LTE base stations, and the current number of 5G base stations. Optionally, the future development data includes at least one of a predicted number of open-home-wide users, a predicted number of open-subscriber-collection users, a predicted number of LTE base stations, and a predicted number of 5G base stations.

102. And determining the total bandwidth requirement of the expected convergence layer of the target region in the target future time period according to the service basic data and a preset bandwidth calculation model.

103. And determining the expected machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area.

104. And determining the planned number of the predicted convergence machine rooms of the target area in the target future time period according to the predicted total bandwidth requirement of the convergence layer and the predicted machine room bearing bandwidth requirement.

Therefore, the method described by the embodiment of the invention can be used for estimating the predicted bandwidth requirements of the target area by combining the current and future service data and further calculating the predicted planning number of the machine rooms, thereby realizing a more accurate and more reasonable machine room construction estimation effect, facilitating more comprehensive machine room construction early-stage planning and improving the efficiency of subsequent machine room construction and the effect of infrastructure construction.

As an optional implementation manner, in the above step, determining the expected aggregate layer total bandwidth requirement of the target area in the target future time period according to the service basic data and a preset bandwidth calculation model includes:

determining the current bandwidth requirement of a target area according to the current data of a user and a preset bandwidth estimation rule;

determining the future bandwidth requirement of the target area according to the future development data and the bandwidth estimation rule;

determining the total bandwidth demand of a target area in a target future time period according to the current bandwidth demand and the future bandwidth demand;

and determining the total bandwidth demand of the target region in the target future time period according to the preset bandwidth grading model and the total bandwidth demand of the predicted region.

Optionally, the current user status data is classified and counted according to the type of a target user covered by a typical backbone convergence machine room in the area, and the current user status data mainly comprises the number of opened wide users, the number of opened customers, the current number of LTE base stations and the current number of 5G base stations, and other sporadic bandwidth requirements are temporarily ignored. Optionally, determining the current bandwidth requirement of the target area according to the current data of the user and a preset bandwidth estimation rule includes:

determining broadband flow data according to the current data of the user; the broadband flow data comprises common broadband flow, on-demand flow and live flow;

counting the current bandwidth requirement of a target area according to the broadband flow data; the current bandwidth requirements comprise the required bandwidth of a bearer network/data network, the required bandwidth of a core layer uplink of a PTN/IPRAN transmission network, the required bandwidth of an uplink of a convergence layer and the required bandwidth of an uplink of an access layer.

Optionally, the determining manner of the broadband traffic data includes:

common broadband flow = number of guests × bandwidth of single user × concurrency ratio;

and/or the presence of a gas in the gas,

on-demand flow = on-demand user concurrency number and on-demand single-user average bandwidth

The number of concurrent users on demand = number of home-wide users + video service home-wide permeability rate + video users is greater than the number of concurrent users on demand (unicast) users;

and/or the presence of a gas in the gas,

the live broadcast flow = number of standard definition channels + number of high definition channels + number of 4k high definition channels.

Optionally, according to the future service development trend and the main development target, determining a future service arrival value according to the market development condition in the region to count future development data, wherein the future development data mainly comprises the predicted number of the wide-width-for-home users, the predicted number of the customers, the predicted number of the LTE base stations and the predicted number of the 5G base stations. Optionally, determining the future bandwidth requirement of the target area according to the future development data and the bandwidth estimation rule includes:

determining future broadband flow data according to future development data; the future broadband flow data comprises future common broadband flow, future on-demand flow and future live flow;

according to the future broadband flow data, the future bandwidth requirement of the target area is counted; the current bandwidth requirements comprise future bearer network/data network required bandwidth, future PTN/IPRAN transmission network core layer uplink required bandwidth, future convergence layer uplink required bandwidth and future access layer uplink required bandwidth.

Optionally, the determination method of the future broadband traffic data is similar to the determination method of the broadband traffic data, and is not described herein again.

Therefore, by implementing the optional implementation mode, the current bandwidth requirement and the future bandwidth requirement can be calculated, the total bandwidth requirement of the target area in the predicted area in the target future time period is determined, and the total bandwidth requirement of the target area in the predicted convergence layer in the target future time period is further determined, so that the total bandwidth requirement of the predicted convergence layer in the target area can be accurately calculated, and the predicted effect of construction of the convergence machine room can be more accurately and reasonably realized in the follow-up process.

As an optional implementation manner, in the foregoing step, determining an expected machine room bearer bandwidth requirement corresponding to a single aggregated machine room in the target area includes:

determining the current machine room bearing requirement and service development trend information corresponding to a single convergence machine room in a target area;

and determining the expected machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area according to the current machine room bearing requirement and the service development trend information.

Optionally, the current machine room bearer requirement includes at least one of an average lower-band micro grid number, an average coverage micro grid area, an average total number of home-wide users, an average total number of guest users, and a number of LTE base stations. Optionally, the service development trend information includes at least one of a home-wide market share growth trend, a customer-collecting market share growth trend, an LTE base station number growth trend, and a home-wide single-user traffic growth trend. Optionally, determining a predicted machine room bearer bandwidth requirement corresponding to a single converged machine room in the target area according to the current machine room bearer requirement and the service development trend information, where the determining includes:

determining a service bearing target corresponding to a single convergence machine room in a target area according to the current machine room bearing requirement and service development trend information; the service bearing target comprises the number of LTE base stations, the number of 5G base stations, the number of home wide open users and the number of collected customers;

and determining a predicted machine room bearing bandwidth requirement corresponding to a single convergence machine room in the target area according to the service bearing target, wherein an OLT uplink bandwidth requirement and a PTN/IPRAN bandwidth requirement corresponding to the single convergence machine room can be determined firstly, and then the sum of the OLT uplink bandwidth requirement and the PTN/IPRAN bandwidth requirement is determined as a convergence layer bandwidth requirement so as to obtain the predicted machine room bearing bandwidth requirement.

Therefore, by implementing the optional implementation mode, the expected machine room bearing bandwidth requirement corresponding to a single converged machine room in the target area can be determined according to the current machine room bearing requirement and the service development trend information, so that the expected machine room bearing bandwidth requirement of the single converged machine room in the target area can be accurately calculated, and the estimation effect of more accurate and reasonable converged machine room construction can be conveniently realized subsequently.

As an optional implementation, the method may further include:

and determining configuration information corresponding to the single converged machine room in the target area according to the predicted machine room bearing bandwidth requirement corresponding to the single converged machine room in the target area.

Optionally, the configuration information includes information of the transmission device, the corollary device, the power supply device, and other requirements of the reserved portion. Specifically, the backbone convergence machine room requires that the external power is at least more than 60KW, a typical installation machine of the backbone convergence machine room can meet the basic requirement of 70T within a certain period, and installation resources facing 5G are reserved. According to the installation plan of the convergence machine room, at least transmission equipment (OTN, PTN/IPRAN and OLT), matching (air conditioner and the like), a power supply (a switching power supply and a storage battery) and other requirements of a reserved part are required. Optionally, the determining the configuration information corresponding to a single aggregated machine room in the target area specifically may include:

PTN/IPRAN: if there are an average of 5 sites per ring, the total bandwidth demand on the aggregation ring is 97.7G (bandwidth utilization is 70%). At least 1 end 100G-PTN/IPRAN should be installed in each backbone convergence machine room. Meanwhile, the machine room is 5G oriented, and the installation capacity of 100G-PTN/IPRAN at the 1 end is reserved.

OTN: considering the bearer requirements of the OLT dual uplink and PTN/IPRAN, at least 2 100 channels should be provided. Each backbone convergence machine room is provided with 1-end 80 × 100G-OTN equipment, and sufficient 100G channel resources are reserved for meeting the bandwidth increase requirement in a certain period.

OLT: each backbone convergence machine room is configured with 2 devices for service access.

BNG/BRAS/SR: and 1 device is configured in each backbone convergence machine room for service convergence.

Therefore, by implementing the optional implementation mode, the configuration information corresponding to a single converged machine room in the target area can be determined according to the expected machine room bearing bandwidth requirement corresponding to the single converged machine room in the target area, so that the configuration information of the single converged machine room in the target area can be accurately calculated, and the estimation effect of more accurate and reasonable converged machine room construction can be realized subsequently.

As an optional implementation manner, in the above step, determining the projected aggregate room planning number of the target area in the target future time period according to the projected aggregate layer total bandwidth demand and the projected room bearer bandwidth demand includes:

and determining the calculation result as the predicted amount of the aggregated machine room plans of the target area in the target future time period.

Therefore, by implementing the optional implementation mode, the calculation result of dividing the total bandwidth demand of the expected convergence layer by the load bandwidth demand of the expected machine room can be determined as the planned number of the expected convergence machine rooms in the target future time period of the target area, so that the planned number of the expected convergence machine rooms can be accurately calculated, and the estimation effect of more accurate and reasonable construction of the convergence machine rooms can be realized subsequently.

As an optional implementation, the method further comprises:

acquiring the number of current convergence machine rooms in a target area;

determining the predicted number of newly added machine rooms in the target area according to the difference between the predicted planned number of the converged machine rooms and the current number of the converged machine rooms;

Optionally, the machine room construction scheme may include at least one of the number of machine room constructions, the construction cost of the machine room, and the construction mode of the machine room.

Therefore, by implementing the optional implementation mode, the predicted newly-added machine room number of the target area can be determined according to the difference value between the predicted assembled machine room planning number and the current assembled machine room number, and the machine room construction scheme corresponding to the target area can be determined according to the predicted newly-added machine room number, so that the machine room construction scheme can be accurately determined, and the more accurate and more reasonable pre-estimation effect of the assembled machine room construction can be conveniently realized.

As an optional implementation manner, in the above step, determining a machine room construction scheme corresponding to the target area according to the estimated number of newly added machine rooms includes;

determining the machine room construction operation tendency of a target area;

Optionally, the machine room construction operation tendency may include a rental operation tendency and a purchase operation tendency. Optionally, the machine room construction operation tendency may be determined by data analysis from a historical machine room construction operation record of the target area. Specifically, taking a certain province as an example, the total bandwidth of the convergence layer reaches 227104G in 20XX years, which is 4.6 times of the bandwidth of the convergence layer in 2017, the total required number of backbone convergence machine rooms in 20XX years is calculated to be 3244, and in consideration of 2484 existing networks, 760 backbone convergence machine rooms are newly added, and if construction is performed according to the lease and purchase proportion (54% and 46%) of the current whole province, 77008 ten thousand yuan is required for 760 machine rooms (the purchased investment is 54652 ten thousand yuan, and the lease cost in 15 year deadline is 22356 ten thousand yuan).

The method steps of the invention are adopted to deploy the convergence machine rooms, and the analysis and confirmation of the number of the convergence machine rooms in the whole network are performed mainly from the current service situation, the service development trend, the analysis of the target service of the typical convergence machine room, the analysis of the target bandwidth of the typical convergence machine room and the analysis of the number of the targets of the convergence machine rooms in the region. On one hand, for the service carrying capacity of the machine room, the quantity and bandwidth of service requirements are measured and calculated in advance in the region, the service requirements are directly matched for building the machine room, and the carrying capacity of the subsequent machine room can be expected to completely meet the service requirements in the region; on the other hand, on the construction and investment distribution of the whole network, the number of machine rooms can be estimated at the initial stage of network planning, machine room point selection and deployment can be carried out in advance, machine room configuration can be completed within a certain time to the maximum extent, enough time is reserved for later-stage construction, the machine room deployment can be used as an effective foundation and a data point of network development, and the network integrity is improved.

Example two

Referring to fig. 2, fig. 2 is a schematic structural diagram of a machine room planning apparatus based on service estimation according to an embodiment of the present invention. The apparatus described in fig. 2 may be applied to a corresponding planning terminal, planning device, or planning server, and the server may be a local server or a cloud server, which is not limited in the embodiment of the present invention. Specifically, as shown in fig. 2, the apparatus may include:

the obtaining module 201 is configured to obtain service basic data of a target area.

And the calculating module 202 is configured to determine a predicted total bandwidth requirement of the convergence layer of the target region in the target future time period according to the service basic data and a preset bandwidth calculating model.

A determining module 203, configured to determine an expected machine room bearer bandwidth requirement corresponding to a single aggregated machine room in the target area.

And the planning module 204 is configured to determine a planned number of the predicted aggregated machine rooms of the target area in the target future time period according to the predicted total bandwidth demand of the aggregation layer and the predicted machine room bearing bandwidth demand.

Therefore, the device described by the embodiment of the invention can estimate the estimated bandwidth requirement of the target area by combining the current and future service data, and further calculate the estimated planning number of the machine room, thereby realizing more accurate and more reasonable machine room construction estimation effect, being beneficial to more comprehensive machine room construction early-stage planning, and being beneficial to improving the efficiency of subsequent machine room construction and the effect of infrastructure construction.

As an optional implementation manner, the specific manner of determining the total bandwidth demand of the predicted convergence layer of the target region in the target future time period by the calculation module 202 according to the service basic data and the preset bandwidth calculation model includes:

Optionally, the determining manner of the broadband traffic data includes:

and/or the presence of a gas in the gas,

As an optional implementation manner, the specific manner in which the determining module 203 determines the expected load-bearing bandwidth requirement of the single aggregated machine room in the target area includes:

As an optional implementation, the apparatus may further include:

and the configuration determining module is used for determining the configuration information corresponding to the single converged machine room in the target area according to the predicted machine room bearing bandwidth requirement corresponding to the single converged machine room in the target area.

As an optional implementation, the specific way for determining the planned number of the predicted aggregated machine rooms of the target area in the target future time period according to the predicted aggregate layer total bandwidth demand and the predicted machine room load bandwidth demand by the planning module 204 includes:

As an optional implementation manner, the obtaining module 201 is further configured to obtain the current number of the converged machine rooms in the target area; the calculation module 202 is further configured to:

acquiring the number of current convergence machine rooms in a target area;

As an optional implementation manner, the calculation module 202 determines a specific manner of the machine room construction scheme corresponding to the target area according to the estimated number of the newly added machine rooms, including;

determining the machine room construction operation tendency of a target area;

EXAMPLE III

Referring to fig. 3, fig. 3 is a schematic structural diagram of another machine room planning apparatus based on service estimation according to an embodiment of the present invention. As shown in fig. 3, the apparatus may include:

a memory 301 storing executable program code;

a processor 302 coupled to the memory 301;

the processor 302 calls the executable program code stored in the memory 301 to execute part or all of the steps in the method for planning the computer room based on the service estimation disclosed in the embodiment of the present invention.

Example four

The embodiment of the invention discloses a computer storage medium, which stores computer instructions, and when the computer instructions are called, the computer instructions are used for executing part or all of the steps in a computer room planning method based on service estimation disclosed by the embodiment of the invention.

While certain embodiments of the present disclosure have been described above, other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily have to be in the particular order shown or in sequential order to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus, device, and non-volatile computer-readable storage medium embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and in relation to the description, reference may be made to some portions of the description of the method embodiments.

The apparatus, the device, the nonvolatile computer readable storage medium, and the method provided in the embodiments of the present specification correspond to each other, and therefore, the apparatus, the device, and the nonvolatile computer storage medium also have similar advantageous technical effects to the corresponding method.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.

As will be appreciated by one skilled in the art, the present specification embodiments may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium which can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

Finally, it should be noted that: the method, apparatus and storage medium for planning a machine room based on service estimation disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used for illustrating the technical solutions of the present invention, rather than limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for planning a machine room based on service estimation is characterized by comprising the following steps:

2. The machine room planning method based on service estimation according to claim 1, wherein the user presence data includes at least one of a number of opened home wide users, a number of opened customer collecting users, an existing number of LTE base stations, and an existing number of 5G base stations; the future development data comprises at least one of the number of expected family wide users, the number of expected customer collecting users, the number of expected LTE base stations and the number of expected 5G base stations.

3. The method for planning a computer room based on service estimation according to claim 2, wherein the determining the predicted total bandwidth requirement of the convergence layer of the target area in the target future time period according to the service basic data and a preset bandwidth calculation model comprises:

4. The method of claim 1, wherein the determining the projected machine room bearer bandwidth requirements corresponding to a single aggregated machine room in the target area comprises:

5. The method of claim 1, wherein determining the projected aggregate room plan number for the target area over the target future time period based on the projected aggregate layer total bandwidth demand and the projected room bearer bandwidth demand comprises:

6. The method for planning a machine room based on traffic estimation according to claim 1, wherein the method further comprises:

acquiring the current number of the converged machine rooms in the target area;

7. The method for planning machine room based on service estimation according to claim 6, wherein the determining of the machine room construction scheme corresponding to the target area according to the estimated number of the newly added machine rooms comprises;

8. A machine room planning apparatus based on traffic estimation, the apparatus comprising:

9. A machine room planning apparatus based on traffic estimation, the apparatus comprising:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute the method for planning a machine room based on service estimation according to any one of claims 1 to 7.

10. A computer storage medium storing computer instructions for performing a method for service estimation based room planning as claimed in any of claims 1-7 when invoked.