CN111970073B - Method and device for determining network load state - Google Patents
Method and device for determining network load state Download PDFInfo
- Publication number
- CN111970073B CN111970073B CN202010797307.4A CN202010797307A CN111970073B CN 111970073 B CN111970073 B CN 111970073B CN 202010797307 A CN202010797307 A CN 202010797307A CN 111970073 B CN111970073 B CN 111970073B
- Authority
- CN
- China
- Prior art keywords
- state
- determining
- network load
- concave
- resource utilization
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000005315 distribution function Methods 0.000 claims abstract description 11
- 230000001186 cumulative effect Effects 0.000 claims abstract description 9
- 238000005070 sampling Methods 0.000 claims description 29
- 238000012545 processing Methods 0.000 claims description 19
- 238000004891 communication Methods 0.000 abstract description 16
- 230000006870 function Effects 0.000 description 17
- 238000004590 computer program Methods 0.000 description 6
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000006386 memory function Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The embodiment of the application provides a method and a device for determining a network load state, relates to the technical field of communication, and solves the technical problem of how to evaluate the load state of a system physical channel of a cell in the prior art. The method for determining the network load state comprises the following steps: acquiring the resource utilization rate of a first channel of a cell; determining the concave-convex state of the CDF curve of the cumulative distribution function of the resource utilization rate according to the resource utilization rate; determining the network load state of the cell according to the concave-convex state of the CDF curve; wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method and an apparatus for determining a network load state.
Background
With the development of communication technology and the rapid growth of network users, the demand of users on network resources is increasing, and the load of network cells is also increasing. Especially, in a data hotspot area and a party type scene, the network cell load is too high, and in such a situation, the network cell needs to be effectively expanded. How to reasonably evaluate the load state of the system physical channel of the cell is the basis for judging the network quality and the network state and is also the premise for effectively expanding the capacity of the network cell.
Disclosure of Invention
The application provides a method and a device for determining a network load state, which solve the technical problem of how to evaluate the load state of a system physical channel of a cell in the prior art.
In order to achieve the purpose, the technical scheme is as follows:
in a first aspect, a method for determining a network load status is provided, including: acquiring the resource utilization rate of a first channel of a cell; determining the concave-convex state of the CDF curve of the cumulative distribution function of the resource utilization rate according to the resource utilization rate; determining the network load state of the cell according to the concave-convex state of the CDF curve; wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH.
In the embodiment of the application, the resource utilization rate of the first channel of the cell can be obtained; determining the concave-convex state of the CDF curve of the cumulative distribution function of the resource utilization rate according to the resource utilization rate; determining the network load state of the cell according to the concave-convex state of the CDF curve; wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH. By the scheme, the network load state of the cell can be determined according to the concave-convex state of the CDF curve, so that the system capacity and the load can be further analyzed and processed according to the network load state of the cell.
In a second aspect, an apparatus for determining a network load status is provided, including: an acquisition unit and a processing unit; an obtaining unit, configured to obtain a resource utilization rate of a first channel of a cell; the processing unit is used for determining the concave-convex state of the CDF curve of the accumulative distribution function of the resource utilization rate according to the resource utilization rate acquired by the acquisition unit; determining the network load state of the cell according to the concave-convex state of the CDF curve; wherein the first channel is any one of the following: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH.
In a third aspect, an apparatus for determining a network load status is provided and includes a memory and a processor. The memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus. When the network load status determining apparatus is operating, the processor executes computer-executable instructions stored in the memory, so that the network load status determining apparatus performs the network load status determining method provided in the first aspect.
The network load state determining device may be a terminal device, or may be a part of a device in the terminal device, such as a system on chip in the terminal device. The system on chip is configured to support the terminal device to implement the functions related to the first aspect and any one of the possible implementations thereof, for example, to determine and transmit data and/or information related to the method for determining the network load status. The chip system includes a chip and may also include other discrete devices or circuit structures.
In a fourth aspect, a computer-readable storage medium is provided, which includes computer-executable instructions, when the computer-executable instructions are executed on a computer, the computer is caused to execute the method for determining a network load status provided in the first aspect.
In a fifth aspect, a computer program product is provided, which comprises computer instructions that, when run on a computer, cause the computer to perform the method for determining a network load status as provided in the first aspect and its various possible implementations.
It should be noted that all or part of the computer instructions may be stored on the computer readable storage medium. The computer readable storage medium may be packaged with the processor of the network load status determining apparatus, or may be packaged separately from the processor of the network load status determining apparatus, which is not limited in this application.
For the descriptions of the second aspect, the third aspect, the fourth aspect, and the fifth aspect in the present application, reference may be made to the detailed description of the first aspect, which is not described herein again; in addition, for the beneficial effects described in the second aspect, the third aspect, the fourth aspect and the fifth aspect, reference may be made to the beneficial effect analysis of the first aspect, and details are not repeated here.
In the present application, the names of the above-mentioned network load state determining means do not limit the devices or function modules themselves, and in actual implementation, these devices or function modules may appear by other names. Insofar as the functions of the respective devices or functional modules are similar to those of the present application, they fall within the scope of the claims of the present application and their equivalents.
These and other aspects of the present application will be more readily apparent from the following description.
Drawings
Fig. 1 is a schematic hardware structure diagram of a network load status determining apparatus according to an embodiment of the present disclosure;
fig. 2 is a second schematic hardware structure diagram of an apparatus for determining a network load status according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a method for determining a network load status according to an embodiment of the present disclosure;
fig. 4 is a second schematic flowchart of a method for determining a network load status according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a device for determining a network load state according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
For the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first" and "second" are used to distinguish the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first" and "second" are not used to limit the quantity and execution order.
The embodiment of the present application provides a method for determining a network load status, which may be applied to a device for determining a network load status as shown in fig. 1, where the device for determining a network load status includes a processor 11, a memory 12, a communication interface 13, and a bus 14. The processor 11, the memory 12 and the communication interface 13 may be connected by a bus 14.
The processor 11 is a control center of the network load status determination apparatus, and may be a single processor or a collective term for a plurality of processing elements. For example, the processor 11 may be a Central Processing Unit (CPU), or may be another general-purpose processor. Wherein a general purpose processor may be a microprocessor or any conventional processor or the like.
For one embodiment, processor 11 may include one or more CPUs, such as CPU 0 and CPU 1 shown in FIG. 1.
The memory 12 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that may store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that may store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In a possible implementation, the memory 12 may exist separately from the processor 11, and the memory 12 may be connected to the processor 11 via a bus 14 for storing instructions or program code. The processor 11 can implement the method for determining the network load status provided by the embodiment of the present application when calling and executing the instructions or program codes stored in the memory 12.
In another possible implementation, the memory 12 may also be integrated with the processor 11.
A communication interface 13 for connecting with other devices through a communication network. The communication network may be an ethernet network, a wireless access network, a Wireless Local Area Network (WLAN), or the like. The communication interface 13 may comprise a receiving unit for receiving data and a transmitting unit for transmitting data.
The bus 14 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 1, but that does not indicate only one bus or one type of bus.
It is noted that the structure shown in fig. 1 does not constitute a limitation of the determination means of the network load status. The means for determining the load status of the network may comprise more or less components than those shown in fig. 1, or some components may be combined, or a different arrangement of components.
Fig. 2 shows another hardware configuration of the network load status determination apparatus in the embodiment of the present application. As shown in fig. 2, the means for determining the network load status may comprise a processor 21 and a communication interface 22. The processor 21 is coupled to a communication interface 22.
The function of the processor 21 may refer to the description of the processor 11 above. The processor 21 also has a memory function, and the function of the memory 12 can be referred to.
The communication interface 22 is used to provide data to the processor 21. The communication interface 22 may be an internal interface of the network load state determination device, or may be an external interface (corresponding to the communication interface 13) of the network load state determination device.
It is noted that the structure shown in fig. 1 (or fig. 2) does not constitute a limitation of the determination means of the network load status, which may comprise more or less components than those shown in the figure, or a combination of some components, or a different arrangement of components than those shown in fig. 1 (or fig. 2).
As shown in fig. 3, an embodiment of the present application provides a method for determining a network load state, which may be applied to a device for determining a network load state, and the method for determining a network load state may include S301 to S303 described below.
S301, the determining device of the network load state obtains the resource utilization rate of the first channel of the cell.
The first channel may be any one of the following: a Physical Downlink Shared Channel (PDSCH), a Physical Uplink Shared Channel (PUSCH), a Physical Downlink Control Channel (PDCCH), a Physical Uplink Control Channel (PUCCH), a Physical Random Access Channel (PRACH), and the like.
And S302, determining the concave-convex state of the CDF curve of the cumulative distribution function of the resource utilization rate according to the resource utilization rate by a network load state determining device.
The determining device of the network load state can determine a plurality of sampling points of the CDF curve according to the resource utilization rate, wherein each sampling point comprises a value of the resource utilization rate and a proportion which is not more than the value of the resource utilization rate in the CDF curve; and then, determining the concave-convex state of each sub-section in the plurality of sub-sections according to the relative position between the plurality of sampling points and the preset CDF threshold, and finally obtaining the concave-convex state of the CDF curve.
Taking the first channel as the PDSCH as an example, the determining device of the network load state may count the resource utilization rate of the PDSCH through the network management system, generate a Cumulative Distribution Function (CDF) curve of the PDSCH resource utilization rate, and output N sampling points (α) of the CDF curven，βn) Wherein N is 1, 2, 3 … … N, alphanValue, beta, representing PDSCH resource utilizationnRepresents that the resource utilization rate of the PDSCH takes the value of alphanCorresponding CDF distribution value, namely beta exists in the sampled PDSCH resource utilization rate samplenThe sampling point value of the proportion is less than or equal to alphan. Need to make sure thatIn the specification, 0<β1＜β2＜β3＜…＜βN<1。
The network load status determining device may set 2M +3 predetermined CDF thresholds, where M is an odd number greater than or equal to 3. The 2M +3 predetermined CDF thresholds may be respectively expressed as: mu.s1、μ2、……、μM+1、μM+2、……、μ2M+3. It should be noted that the 2M +3 preset CDF thresholds may satisfy the following requirements:
1、0<μ1＜μ2＜...＜μM+1＜μM+2＜…＜μ2M+3<1；
2、μM+2＝0.5；
3、μ1≤0.1；
4、μ2M+3≥0.9；
5、
it should be noted that, in the initial state, the default value of M may be 3, and the default value of the preset CDF threshold may be μ1＝0.1、μ2＝0.2、μ3＝0.3、μ4＝0.4、μ5＝0.5、μ6＝0.6、μ7＝0.7、μ8＝0.8、μ90.9. Then, based on the above requirement, M and the preset CDF threshold may be continuously adjusted along with the final output result.
After obtaining N sampling points, the determining apparatus of the network load state may perform difference point taking on a CDF curve according to 2M +3 preset CDF thresholds, which specifically includes: determining a point λ on a CDF curveiLet point λ on the CDF curveiCorresponding to a predetermined CDF threshold muiCarrying out subtraction to obtain a point lambda on the CDF curveiCorresponding to a predetermined CDF threshold μiDifference Δ y therebetweeni。
In particular, the method comprises the following steps of,
wherein i is 1, 2, 3 … … 2M + 3; k has a value of muiAnd beta1，β2，β3，…，βNAfter comparing in sequence, the first ratio mu is obtainediA large index. For example, if μi＝0.3，β1＝0.1、β2＝0.25、β3When k is 0.35, the value of k is β3I.e., k is 3.
The CDF curve may include a plurality of sub-segments, and thus, Δ yiMay be divided into a plurality of sub-block sections. For example,. DELTA.yiCan be divided into three sub-interval segments, the threshold corresponding to the first sub-interval segment comprises delta y2,...,ΔyM+1(ii) a The threshold corresponding to the second subinterval segment comprises deltayM+2(ii) a The threshold corresponding to the third subinterval segment comprises delta yM+3,ΔyM+4,...,Δy2M+2. For the first sub-interval segment and the third sub-interval segment, Δ y in the sub-interval segment needs to be determined firstiA number L of 0 or more, where L is greater than or equal to
In the case of (3), it may be determined that the subinterval segment is in a convex state; at L is less than
In this case, it can be determined that the subinterval segment is in a concave state. For the second sub-segment, at Δ yM+2If the value is greater than or equal to 0, the sub-interval segment can be determined to be in a convex state; at Δ yM+2If the value is less than 0, the subinterval segment may be determined to be in a concave state.
S303, the network load status determining device determines the network load status of the cell according to the concave-convex status of the CDF curve.
In the case where the plurality of sub-section segments are sub-section segments in a concave state, the network load state determination device may determine that the network load state of the cell is a first distribution state, which is a distribution state in which the high load ratio is greater than or equal to the medium-low load ratio.
In the case where the plurality of sub-section segments are all sub-section segments in the convex state, the network load state determination device may determine that the network load state of the cell is a second distribution state, where the second distribution state is a distribution state in which the high load ratio is smaller than the medium-low load ratio.
The multiple subinterval segments include a concave subinterval segment and a convex subinterval segment, and the last sampling point λ of the CDF curve2M+3And the first sample point λ1Is greater than or equal to a preset threshold lambdaTHIn this case, the network load status determining device may determine that the network load status of the cell is a third distribution status, which is a distribution status of load balancing.
The multiple subinterval segments include a concave subinterval segment and a convex subinterval segment, and the last sampling point λ of the CDF curve2M+3And the first sample point λ1Is less than a preset threshold lambdaTHIn this case, the network load state determination device may determine that the network load state of the cell is a fourth distribution state, which is a distribution state in which loads are concentrated.
Optionally, as shown in fig. 4, the method for determining a network load state provided in the embodiment of the present application may further include S304.
S304, the determining device of the network load state determines the capacity expansion requirement of the first channel according to the resource load mean value of the first channel under different network load states.
The first channel is still taken as PDSCH as an example. If the mean value of the resource load of PDSCH is etameanThen, for different network load distribution states, the determination device of the network load state can pass the first threshold ηth_hSecond threshold ηth_mAnd a third threshold ηth_lDifferent capacity expansion requirements are determined.
Specifically, if η is the first distribution state of the PDSCH resource loadmeanIs greater than or equal to etath_hIf so, judging that the high resource utilization ratio of the PDSCH resources is high, and optimizing the system by combining the means of scheduling algorithm optimization and the like; if etameanGreater than or equal to ηth_mAnd is less than ηth_hIf so, the determining device of the network load state determines that the resource utilization ratio in the PDSCH resources is high, the network load state is still enough, and continuous observation is needed; if etameanLess than ηth_lThe network load state determining device determines that the network load is mostly in the medium-low load state. Wherein etath_hMay be 0.6, ηth_mMay be 0.5, etath_lMay be 0.3 by default.
If η is the second distribution state of PDSCH resource loadmeanGreater than or equal to ηth_hIf so, judging that the medium-low degree resource utilization ratio of the PDSCH resources is higher and the network capacity expansion requirement exists; if etameanGreater than or equal to ηth_mAnd is less than ηth_hIf so, the determination device of the network load state determines that the resource utilization rate of the PDSCH resources is concentrated in the medium load state, and the network load state is very good; if etameanLess than ηth_lThen, the network load state determining device determines that the resource utilization rate of the PDSCH resources is concentrated in a low load state and the network is in a less idle state. Wherein etath_hMay be 0.4, ηth_mMay be set to 0.3, etath_lMay be 0.2 by default.
If η is the third distribution state of PDSCH resource loadmeanGreater than or equal to ηth_hIf the network load state is determined to be heavier, the network needs to be subjected to capacity expansion; if etameanGreater than or equal to ηth_mAnd is less than ηth_hIf the network load state is in the good state, the network load state determining device judges that the network load is in the good state; if etameanLess than ηth_lThe determination device of the network load status determines that the network load is light. Wherein eta isth_hOfThe value can be considered to be 0.5, etath_mMay be 0.35, etath_lMay be 0.2 by default.
If η is the case where the PDSCH resource load is in the fourth distribution statemeanGreater than or equal to ηth_hIf yes, judging that the PDSCH resources are continuously in a high-load state, and urgently needing capacity expansion; if etameanIs greater than or equal to etath_mAnd is less than ηth_hIf so, the determination device of the network load state determines that the resource utilization rate of the PDSCH resources is concentrated in the medium load state, and the network load state is very good; if etameanLess than etath_lThen, the network load state determining device determines that the resource utilization rate of the PDSCH resources is concentrated in a low load state and the network is in a less idle state. Wherein eta isth_hMay be 0.7, ηth_mMay be 0.4, etath_lMay be 0.2 by default.
The embodiment of the application provides a method for determining a network load state, which can obtain a resource utilization rate of a first channel of a cell; determining the concave-convex state of the CDF curve of the cumulative distribution function of the resource utilization rate according to the resource utilization rate; determining the network load state of the cell according to the concave-convex state of the CDF curve; wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH. By the scheme, the network load state of the cell can be determined according to the concave-convex state of the CDF curve, so that the system capacity and the load can be further analyzed and processed according to the network load state of the cell.
The scheme provided by the embodiment of the application is mainly introduced from the perspective of a method. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the method for determining a network load status provided in the embodiment of the present application, the execution subject may be a device for determining a network load status, or a control module in the device for determining a network load status, which is used for executing an electronic card management service. In the embodiment of the present application, a method for determining a network load state performed by a determination device of a network load state is taken as an example, and an electronic card management service execution device provided in the embodiment of the present application is described.
It should be noted that, in the embodiment of the present application, the determining apparatus of the network load status may perform the division of the functional modules according to the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. Optionally, the division of the modules in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
As shown in fig. 5, an apparatus for determining a network load status according to an embodiment of the present application is provided. The network load status determination apparatus 500 may include an acquisition unit 501 and a processing unit 502. The obtaining unit 501 may be configured to obtain a resource utilization rate of a first channel of a cell; for example, in conjunction with fig. 3, the obtaining unit 501 may be configured to perform S301. The processing unit 502 is configured to determine an uneven state of a CDF curve of the cumulative distribution function of the resource utilization according to the resource utilization obtained by the obtaining unit 501, and determine a network load state of the cell according to the uneven state of the CDF curve; for example, in conjunction with fig. 3, processing unit 502 may be configured to perform S302 and S303; wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH.
Optionally, the CDF curve includes a plurality of sub-segments; the processing unit 502 may specifically be configured to: determining a plurality of sampling points of a CDF curve according to the resource utilization rate acquired by the acquiring unit 501, where each sampling point includes a value of the resource utilization rate and a proportion of the value of the CDF curve that is not greater than the resource utilization rate; and determining the concave-convex state of each sub-interval section in the plurality of sub-interval sections according to the relative position between the plurality of sampling points and a preset CDF threshold, so as to obtain the concave-convex state of the CDF curve.
Optionally, the processing unit 502 may be specifically configured to: under the condition that the plurality of subinterval sections are all the subinterval sections in the concave state, determining that the network load state of the cell is a first distribution state, wherein the first distribution state is a distribution state that the high load ratio is greater than or equal to the medium-low load ratio; under the condition that the plurality of subinterval sections are all in convex state, determining that the network load state of the cell is a second distribution state, wherein the second distribution state is a distribution state that the high load ratio is smaller than the medium-low load ratio; determining the network load state of the cell to be a third distribution state under the condition that the plurality of subinterval sections comprise subinterval sections in a concave state and subinterval sections in a convex state, and the difference value between the last sampling point and the first sampling point of the CDF curve is greater than or equal to a preset threshold, wherein the third distribution state refers to a distribution state of load balance; and under the condition that the plurality of subinterval segments comprise subinterval segments in a concave state and subinterval segments in a convex state, and the difference value between the last sampling point and the first sampling point of the CDF curve is smaller than a preset threshold, determining that the network load state of the cell is a fourth distribution state, wherein the fourth distribution state is a distribution state in which loads are concentrated.
Optionally, the processing unit 502 may be further configured to determine an expansion requirement of the first channel according to the resource load average of the first channel in different network load states; for example, in connection with fig. 4, the processing unit 502 may be configured to execute S304.
Of course, the network load status determination apparatus 500 provided in the embodiment of the present application includes, but is not limited to, the above modules.
In actual implementation, the processing unit 502 may be implemented by the processor 11 shown in fig. 1 calling the program code in the memory 12. For a specific implementation process, reference may be made to the description of the method for determining a network load status shown in fig. 3 or fig. 4, which is not described herein again.
The embodiment of the application provides a device for determining a network load state, which can acquire the resource utilization rate of a first channel of a cell; determining the concave-convex state of the CDF curve of the cumulative distribution function of the resource utilization rate according to the resource utilization rate; determining the network load state of the cell according to the concave-convex state of the CDF curve; wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH. By the scheme, the network load state of the cell can be determined according to the concave-convex state of the CDF curve, so that the system capacity and the load can be further analyzed and processed according to the network load state of the cell.
Embodiments of the present application also provide a computer-readable storage medium, which includes computer-executable instructions. When the computer executes the instructions to run on the computer, the computer is caused to execute the steps executed by the network load state determining device in the network load state determining method provided by the above embodiment.
The embodiments of the present application further provide a computer program product, where the computer program product is directly loadable into a memory and contains a software code, and the computer program product is loaded and executed by a computer, so as to implement the steps executed by the network load status determining apparatus in the network load status determining method provided in the foregoing embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented using a software program, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The processes or functions according to the embodiments of the present application are generated in whole or in part when the computer-executable instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). Computer-readable storage media can be any available media that can be accessed by a computer or can comprise one or more data storage devices, such as servers, data centers, and the like, that can be integrated with the media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described device embodiments are merely illustrative, and for example, the division of the above modules or units is only one logical function division, and there may be other division ways in actual implementation. For example, various elements or components may be combined or may be integrated into another device, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. A method for determining a network load status, comprising:
acquiring the resource utilization rate of a first channel of a cell;
determining the concave-convex state of the CDF curve of the cumulative distribution function of the resource utilization rate according to the resource utilization rate;
determining the network load state of the cell according to the concave-convex state of the CDF curve;
wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH;
the CDF curve comprises a plurality of sub-segments; the determining the concave-convex state of the CDF curve according to the resource utilization rate comprises the following steps:
determining a plurality of sampling points of a CDF curve according to the resource utilization rate, wherein each sampling point comprises a value of the resource utilization rate and a proportion of the value of the CDF curve, which is not more than the resource utilization rate;
determining the concave-convex state of each sub-interval section in the plurality of sub-interval sections according to the relative position between the plurality of sampling points and a preset CDF threshold to obtain the concave-convex state of the CDF curve;
the determining the network load state of the cell according to the concave-convex state of the CDF curve includes:
determining that the network load state of the cell is a first distribution state under the condition that the plurality of sub-block periods are all sub-block periods in a concave state, wherein the first distribution state is a distribution state that the high load ratio is greater than or equal to the medium-low load ratio;
determining that the network load state of the cell is a second distribution state under the condition that the plurality of sub-block sections are all in convex states, wherein the second distribution state is a distribution state in which the high load ratio is smaller than the medium-low load ratio;
determining that the network load state of the cell is a third distribution state under the condition that the plurality of subinterval sections comprise subinterval sections in a concave state and subinterval sections in a convex state, and the difference value between the last sampling point and the first sampling point of the CDF curve is greater than or equal to a preset threshold, wherein the third distribution state is a distribution state of load balance;
and under the condition that the plurality of subinterval segments comprise subinterval segments in a concave state and subinterval segments in a convex state, and the difference value between the last sampling point and the first sampling point of the CDF curve is smaller than a preset threshold, determining that the network load state of the cell is a fourth distribution state, wherein the fourth distribution state is a distribution state with concentrated load.
2. The method of determining a network load status as claimed in claim 1, wherein the method further comprises:
and determining the capacity expansion requirement of the first channel according to the resource load mean value of the first channel in different network load states.
3. An apparatus for determining a network load status, comprising: an acquisition unit and a processing unit;
the acquiring unit is configured to acquire a resource utilization rate of a first channel of a cell;
the processing unit is configured to determine, according to the resource utilization rate acquired by the acquisition unit, an uneven state of a CDF curve of an accumulated distribution function of the resource utilization rate, and determine a network load state of the cell according to the uneven state of the CDF curve;
wherein the first channel is any one of: a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, a physical downlink control channel PDCCH, a physical uplink control channel PUCCH and a physical random access channel PRACH;
the CDF curve comprises a plurality of sub-segments;
the processing unit is specifically configured to determine multiple sampling points of a CDF curve according to the resource utilization rate acquired by the acquiring unit, where each sampling point includes a value of the resource utilization rate and a proportion of the value of the CDF curve that is not greater than the resource utilization rate; determining the concave-convex state of each sub-interval section in the plurality of sub-interval sections according to the relative position between the plurality of sampling points and a preset CDF threshold to obtain the concave-convex state of the CDF curve;
the processing unit is specifically configured to:
determining that the network load state of the cell is a first distribution state under the condition that the plurality of sub-block periods are all sub-block periods in a concave state, wherein the first distribution state is a distribution state that the high load ratio is greater than or equal to the medium-low load ratio;
determining that the network load state of the cell is a second distribution state under the condition that the plurality of sub-block sections are all in convex states, wherein the second distribution state is a distribution state in which the high load ratio is smaller than the medium-low load ratio;
determining that the network load state of the cell is a third distribution state under the condition that the plurality of subinterval sections comprise subinterval sections in a concave state and subinterval sections in a convex state, and the difference value between the last sampling point and the first sampling point of the CDF curve is greater than or equal to a preset threshold, wherein the third distribution state is a distribution state of load balance;
and under the condition that the plurality of subinterval sections comprise subinterval sections in a concave state and subinterval sections in a convex state, and the difference value between the last sampling point and the first sampling point of the CDF curve is smaller than a preset threshold value, determining that the network load state of the cell is a fourth distribution state, wherein the fourth distribution state is a concentrated distribution state of loads.
4. The apparatus according to claim 3, wherein the processing unit is further configured to determine a capacity expansion requirement of the first channel according to a resource load average of the first channel in different network load states.
5. An apparatus for determining a network load state, comprising a memory and a processor; the memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus;
the processor executes the computer-executable instructions stored by the memory to cause the network load state determining apparatus to perform the network load state determining method of claim 1 or 2 when the network load state determining apparatus is operating.
6. A computer-readable storage medium, comprising computer-executable instructions that, when executed on a computer, cause the computer to perform the method of determining a network load status of claim 1 or 2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010797307.4A CN111970073B (en) | 2020-08-10 | 2020-08-10 | Method and device for determining network load state |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010797307.4A CN111970073B (en) | 2020-08-10 | 2020-08-10 | Method and device for determining network load state |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111970073A CN111970073A (en) | 2020-11-20 |
| CN111970073B true CN111970073B (en) | 2022-07-08 |
Family
ID=73364254
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010797307.4A Active CN111970073B (en) | 2020-08-10 | 2020-08-10 | Method and device for determining network load state |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111970073B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101854665A (en) * | 2009-04-03 | 2010-10-06 | 大唐移动通信设备有限公司 | Method, device and system for controlling load of LTE system |
| CN108235337A (en) * | 2016-12-15 | 2018-06-29 | ***通信有限公司研究院 | Utilization rate baseline value method of estimation and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160286425A1 (en) * | 2015-03-23 | 2016-09-29 | Nokia Solutions And Networks Oy | Method and system for wireless network optimization |
-
2020
- 2020-08-10 CN CN202010797307.4A patent/CN111970073B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101854665A (en) * | 2009-04-03 | 2010-10-06 | 大唐移动通信设备有限公司 | Method, device and system for controlling load of LTE system |
| CN108235337A (en) * | 2016-12-15 | 2018-06-29 | ***通信有限公司研究院 | Utilization rate baseline value method of estimation and device |
Non-Patent Citations (1)
| Title |
|---|
| IP/MPLS网络路由规划工具的设计与实现;杨娟;《中国优秀硕士学位论文全文数据库》;20170615;第14-16页，附图3-3 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111970073A (en) | 2020-11-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112752302A (en) | Power service time delay optimization method and system based on edge calculation | |
| CN111669792B (en) | Cell switching method and device | |
| CN112465359A (en) | Calculation power calling method and device | |
| CN111159195A (en) | Data storage control method and equipment in block chain system | |
| CN114816738A (en) | Method, device and equipment for determining calculation force node and computer readable storage medium | |
| CN111866902B (en) | Resource utilization rate evaluation method and device | |
| CN111970073B (en) | Method and device for determining network load state | |
| CN113438678B (en) | Method and device for distributing cloud resources for network slices | |
| CN112492635B (en) | Determination method and device for scheduling priority | |
| WO2015035901A1 (en) | Method and device for determining program performance interference model | |
| CN111866951B (en) | Service processing method and device | |
| CN115576661A (en) | Data processing system, method and controller | |
| CN112020073A (en) | Cell classification method and device | |
| US9479579B2 (en) | Grouping processing method and system | |
| CN111092817A (en) | Data transmission method and device | |
| CN111885625B (en) | Method and device for determining resource utilization rate | |
| CN112203354A (en) | Service processing method and device | |
| CN111885638B (en) | Method and device for determining number of busy hour service transmission layers | |
| CN112004249B (en) | Method and device for determining channel resource load distribution state | |
| CN117135081A (en) | Fault determination method, device and computer readable storage medium | |
| CN112004248B (en) | Method and device for determining channel resource load distribution state | |
| CN112601252B (en) | Energy-saving control method and device | |
| CN113923224B (en) | Electric power internet of things task unloading method, server and terminal | |
| CN110401519B (en) | Pilot frequency distribution method and device | |
| CN112995129A (en) | Electric power business safety transmission method and system based on edge calculation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |