CN114448812A - Convergence node distribution method and device and computer equipment - Google Patents

Convergence node distribution method and device and computer equipment Download PDF

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Publication number
CN114448812A
CN114448812A CN202111608612.5A CN202111608612A CN114448812A CN 114448812 A CN114448812 A CN 114448812A CN 202111608612 A CN202111608612 A CN 202111608612A CN 114448812 A CN114448812 A CN 114448812A
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bandwidth
service
sink node
obtaining
weight ratio
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林铠
陈秋松
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Tianyi Cloud Technology Co Ltd
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Tianyi Cloud Technology Co Ltd
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/08Configuration management of networks or network elements
    • H04L41/0896Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities

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Abstract

The invention discloses a sink node distribution method, a sink node distribution device and computer equipment, wherein the method comprises the steps of acquiring current service information, wherein the current service information comprises a service type, a service cold and hot degree and regional information; obtaining a bandwidth weight ratio of the current service based on the service type; obtaining peak value redundant bandwidth of the region based on the peak value bandwidth and the bandwidth weight ratio of the region information; acquiring a convergence layer bandwidth required by the service based on the service cold and hot degree; obtaining the available sink node resources of the current service based on the service type and the area information; and allocating the sink nodes based on the available sink node resources, the peak redundancy bandwidth and the required sink layer bandwidth. The bandwidth actually required by the service can be accurately obtained by obtaining the corresponding bandwidth weight ratio through obtaining the type of the service, the problem of high load running of the sink node is avoided, and the sink node bandwidth is ensured to be sufficient and not to become a bottleneck of the service loading through screening the redundant bandwidth of the sink node in the area where the service is located.

Description

Aggregation node distribution method and device and computer equipment
Technical Field
The invention relates to the technical field of internet, in particular to a sink node distribution method, a sink node distribution device and computer equipment.
Background
The main focus of the existing CDN on the convergence layer bandwidth is on the back-source bandwidth and the back-source region, but the main resource requirement (or resource bottleneck) of the convergence layer is not on the back-source bandwidth, but on the entry bandwidth when the edge bandwidth is converged.
Currently, a CDN service has a partial convergence layer node selection scheme, such as selecting a convergence node according to a source station area; the sink nodes are selected according to the back source bandwidth, but the selection schemes are not considered comprehensively, so that the sink nodes are prone to high load and poor quality after the service is on line, or too many sink nodes are selected to form the sink scheme, so that resource idle running waste is caused, the bandwidth cannot be effectively converged, and the service hit rate is increased.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defect that in the prior art, only the sink layer resources are considered from the back source bandwidth, and the selected sink node combination scheme is not accurate enough, so that after the traffic is loaded, the resource runs empty or the resource is overloaded, and the like may occur, thereby providing a sink node allocation method, device and computer equipment.
According to a first aspect, an embodiment of the present invention discloses a sink node allocation method, including: acquiring current service information, wherein the current service information comprises a service type, a service cold and hot degree and regional information; obtaining the bandwidth weight ratio of the current service based on the service type; obtaining the peak value redundant bandwidth of the region based on the peak value bandwidth of the region information and the bandwidth weight ratio; obtaining the convergence layer bandwidth required by the convergence layer of the service based on the service cold and hot degree; obtaining available sink node resources of the current service based on the service type and the area information; and allocating the sink nodes based on the available sink node resources, the peak redundancy bandwidth and the required sink layer bandwidth.
Optionally, the obtaining the bandwidth weight ratio of the current service based on the service type includes: performing incremental pressure measurement on the current service every first preset time, and recording a pressure measurement result after the incremental pressure measurement; judging whether the pressure measurement result reaches a preset abnormal condition or not; if the preset abnormal condition is met, recording the peak bandwidth of the last measured voltage increase; and obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service.
Optionally, the method further comprises: and if the preset abnormal condition is not met, continuing to perform the measurement of the incremental pressure until the preset abnormal condition is met, and executing the step of recording the peak bandwidth of the last measurement of the incremental pressure to the step of obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service.
Optionally, the obtaining the peak redundancy bandwidth of the region based on the peak bandwidth of the region information and the bandwidth weight ratio includes: acquiring the peak bandwidth of the region information within a second preset time; and obtaining the peak value redundant bandwidth of the region information based on the peak value bandwidth in the second preset time and the bandwidth weight ratio of the existing service in the region information in the second preset time.
Optionally, obtaining available sink node resources of the current service based on the service type and the area information includes: screening first available sink node resources in each region information based on the region information; and obtaining the available sink node resources based on the service type and the first available sink node resources.
Optionally, the allocating a sink node based on the available sink node resource, the peak redundancy bandwidth, and the required sink layer bandwidth includes: obtaining the redundant bandwidth of each region based on the required convergence layer bandwidth of the current service and the bandwidth weight ratio of the current service; and obtaining a sink node group meeting the required sink layer bandwidth based on the redundant bandwidth, the peak value redundant bandwidth and the available sink node resources.
Optionally, the method further comprises: determining remaining available sink node resources based on the available sink node resources, bandwidth capacity of sink node groups, and redundant bandwidth; and taking the residual available sink node resources as a standby sink node group.
According to a second aspect, an embodiment of the present invention further discloses a sink node selecting apparatus, including: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring current service information, and the current service information comprises a service type, a service cold and hot degree and area information; the bandwidth weight ratio module is used for obtaining the bandwidth weight ratio of the current service based on the service type and a preset service information database; the peak value redundant bandwidth module is used for obtaining the peak value redundant bandwidth of the region based on the peak value bandwidth of the region information and the bandwidth weight ratio; a required convergence layer bandwidth module, configured to obtain a convergence layer bandwidth required by a convergence layer of the service based on the service cooling and heating level; the available sink node resource module is used for obtaining the available sink node resources of the current service based on the service type and the area information; and the distribution module is used for carrying out sink node distribution based on the available sink node resources, the peak value redundancy bandwidth and the required sink layer bandwidth.
According to a third aspect, an embodiment of the present invention further discloses a computer device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the sink node allocation method according to the first aspect or any one of the optional embodiments of the first aspect.
According to a fourth aspect, the present invention further discloses a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the sink node allocation method according to the first aspect or any one of the optional embodiments of the first aspect.
The technical scheme of the invention has the following advantages:
the invention provides a sink node distribution method, a sink node distribution device and computer equipment, wherein the method comprises the following steps: acquiring current service information, wherein the current service information comprises service types, service cold and hot degrees and regional information; obtaining the bandwidth weight ratio of the current service based on the service type; obtaining the peak value redundant bandwidth of the region based on the peak value bandwidth of the region information and the bandwidth weight ratio; obtaining the convergence layer bandwidth required by the convergence layer of the service based on the service cold and hot degree; obtaining available sink node resources of the current service based on the service type and the area information; and allocating the sink nodes based on the available sink node resources, the peak redundancy bandwidth and the required sink layer bandwidth. The corresponding bandwidth weight ratio can be obtained by obtaining the type of the service needing node distribution, the actually required bandwidth of the service can be accurately obtained, the problem of high load running of the sink node is avoided, and the sufficient bandwidth of the sink node is ensured by screening the redundant bandwidth of the sink node in the area where the service is located, so that the bandwidth of the sink node cannot become the bottleneck of the service loading.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of a sink node allocation method according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a specific example of an aggregation node allocation apparatus according to an embodiment of the present invention;
FIG. 3 is a diagram showing a specific example of a computer device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a specific example of a sink node allocation method in the embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment of the invention discloses a sink node distribution method, as shown in figure 1, the method comprises the following steps:
step 101: and acquiring current service information, wherein the current service information comprises service types, service cold and hot degrees and region information.
Illustratively, the service information is various information of specific services which need to be distributed by the sink node, wherein the service types can be live broadcast, on-demand broadcast, web page or download, etc.; the regional information may be a geographic location where the service is located, such as a north China area or a middle China area; the service hot and cold degree can be the hit rate of the service edge node. The embodiment of the present invention does not limit the specific content of the service information, and those skilled in the art can determine the content according to actual needs.
Step 102: and obtaining the bandwidth weight ratio of the current service based on the service type.
Illustratively, the bandwidth weight ratio of a service is a quotient of an egress bandwidth of an aggregation node corresponding to the service and an actual service bandwidth that can be carried by the node, for example, in a normal case, the traffic load is 10G, and if the bandwidth occupancy of the aggregation node is 10G, the bandwidth weight ratio is 1:1, but a part of the service occupies a higher physical resource such as a CPU, an IO, or a memory of the aggregation node, and the egress bandwidth of the aggregation node is 100G, and can run 100G in a normal case, but if a certain type of service runs 80G on the aggregation node, a machine CPU runs beyond, and then the service is abnormal due to a machine performance problem, the actual bandwidth weight ratio of the service is: 1:100/80 is 1:1.25 (this service runs 1G of bandwidth, calculated as the sink bandwidth occupying 1.25G).
Step 103: and obtaining the peak redundancy bandwidth of the region based on the peak bandwidth of the region information and the bandwidth weight ratio. Illustratively, the peak bandwidth of the region information may be the maximum bandwidth of the region where the service is located, the occupied bandwidth number in the region information may be obtained according to the bandwidth weight ratio of the existing service in the region information, the peak redundancy bandwidth is the maximum remaining bandwidth amount in the region information, and the occupied bandwidth is subtracted from the peak bandwidth in the region information to obtain the peak redundancy bandwidth.
Step 104: and obtaining the required convergence layer bandwidth of the service based on the service cold and hot degree.
Illustratively, the required convergence layer bandwidth of the service cannot be directly obtained, and the convergence layer bandwidth actually required by the service can be calculated according to the service cold and hot degree (also called the hit rate of the service edge node) and the actual edge layer bandwidth of the service. Specifically, if the actual edge layer bandwidth of a service is 100Gbps and the average hit rate of the service is 60%, the convergence layer bandwidth is expected to be 100Gbps x (1-60%) or 40 Gbps.
Step 105: and obtaining the available sink node resources of the current service based on the service type and the area information. Illustratively, all available aggregation nodes of the service in the area information can be obtained according to the service type and the area information of the service, thereby ensuring that the aggregation nodes distributed by the service are all in the area information with the closest distance.
Step 106: and allocating the sink nodes based on the available sink node resources, the peak redundancy bandwidth and the required sink layer bandwidth. Illustratively, in the sink node resources screened out according to step 105, sink node allocation is obtained according to the sink layer bandwidth required by the service and the peak bandwidth redundancy in the information of the area to which the service belongs, so that the problem of high load running of the sink node is avoided under the condition that the required bandwidth of the service is met, and the sufficient bandwidth of the sink node is ensured by screening the redundant bandwidth of the sink node in the area to which the service belongs, and the sink node cannot become a bottleneck of the traffic load.
The sink node distribution method provided by the invention comprises the following steps: acquiring current service information, wherein the current service information comprises a service type, a service cold and hot degree and regional information; obtaining the bandwidth weight ratio of the current service based on the service type; obtaining the peak value redundant bandwidth of the region based on the peak value bandwidth of the region information and the bandwidth weight ratio; obtaining the required convergence layer bandwidth of the service based on the service cold and hot degree; obtaining available sink node resources of the current service based on the service type and the area information; and allocating the sink nodes based on the available sink node resources, the peak redundancy bandwidth and the required sink layer bandwidth. The corresponding bandwidth weight ratio can be obtained by obtaining the type of the service needing node distribution, the actually required bandwidth of the service can be accurately obtained, the problem of high load running of the sink node is avoided, and the sufficient bandwidth of the sink node is ensured by screening the redundant bandwidth of the sink node in the area where the service is located, so that the bandwidth of the sink node cannot become the bottleneck of the service loading.
As an optional implementation manner of the present invention, the step 102 includes: performing incremental pressure measurement on the current service every first preset time, and recording a pressure measurement result after the incremental pressure measurement; judging whether the pressure measurement result reaches a preset abnormal condition or not; if the preset abnormal condition is met, recording the peak bandwidth of the last measured voltage increase; and obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service. And if the preset abnormal condition is not met, continuing to perform the measurement of the incremental pressure until the preset abnormal condition is met, and executing the step of recording the peak bandwidth of the last measurement of the incremental pressure to the step of obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service.
For example, the calculation manner of the traffic bandwidth weight ratio may be obtained by performing incremental pressure measurement on the corresponding traffic, where the first preset time may be 5 minutes, that is, performing pressure measurement on the corresponding traffic every 5 minutes. The preset abnormal condition may be that the pressure measurement junction abnormal ratio exceeds 1%. The embodiment of the invention does not limit the duration and the condition content of the first preset time and the preset abnormal condition, and can be determined by a person skilled in the art according to actual needs.
Specifically, the process of acquiring the bandwidth weight ratio is introduced by the following example, that is, firstly, incremental pressure measurement is performed on the service every 5 minutes, and a pressure measurement result is recorded after each pressure measurement period; if the abnormal ratio of the pressure measurement result in the previous period exceeds 1%, the service is normal, the peak value of the pressure measurement bandwidth is recorded, and the automatic addition test is continued (10% of the previous test); if the ratio of the abnormal pressure measurement in the previous period exceeds 1%, the system stops the pressure measurement process and records the bandwidth peak value of the last normal pressure measurement period as the maximum bandwidth value which can be borne by the service sink node, if the ratio of the abnormal pressure measurement in the previous period exceeds 1%, the service pressure measurement reaches the maximum value; thirdly, obtaining a service bandwidth weight value according to the maximum bandwidth value which can be borne by the service aggregation node and the machine exit bandwidth capacity obtained by pressure measurement; the service bandwidth weight is the outlet bandwidth of the sink node ÷ the actual service bandwidth that the sink node can bear.
As an alternative embodiment of the present invention, the step 103 includes: acquiring the peak bandwidth of the region information within a second preset time; and obtaining the peak value redundant bandwidth of the region information based on the peak value bandwidth in the second preset time and the bandwidth weight ratio of the existing service in the region information in the second preset time.
For example, the second preset time may be the past 7 days, the peak bandwidth of the area information in the past 7 days and the bandwidth occupation amount corresponding to the existing service in the area information in the past 7 days are obtained, and the actual peak redundant bandwidth in the area information is obtained according to the ratio of the occupation amount to the weighted bandwidth of the existing service, where the peak redundant bandwidth is all available bandwidths when the current service is allocated by the sink node. Therefore, the bandwidth requirement of the current service is met, and the conflict with the previous service can be avoided, so that the phenomenon of service operation error is caused.
As an alternative embodiment of the present invention, the step 105 includes: screening first available sink node resources in each region information based on the region information; and obtaining the available sink node resources based on the service type and the first available sink node resources.
Illustratively, when screening available sink node resources, selection needs to be performed according to area information and service types of a current service, a first available sink node is selected according to an area where the current service is located, for example, if the area to which the current service belongs is a chinese area, a sink node in the chinese area is selected, and when selecting a sink node in the same area, it needs to be satisfied that the selected node belongs to the same operator, for example, the operator of the sink node belonging to the same operator is telecommunications. And selecting again according to the service type on the basis of the first available convergent node, wherein the service type is considered when the convergent node is selected because different service types correspond to different convergent node types, so that the error probability of service operation is reduced.
As an alternative embodiment of the present invention, the step 106 includes: obtaining the redundant bandwidth of each region based on the required convergence layer bandwidth of the current service and the bandwidth weight ratio of the current service; and obtaining a sink node group meeting the required sink layer bandwidth based on the redundant bandwidth, the peak value redundant bandwidth and the available sink node resources.
As an optional implementation manner of the present invention, the step 106 further includes: determining remaining available sink node resources based on the available sink node resources, bandwidth capacity of sink node groups, and redundant bandwidth; and taking the remaining available sink node resources as a standby sink node group.
Illustratively, the sink node group meeting the current service is selected from the available sink nodes obtained in the above step 105, and the basic principle of selecting the sink node group is to meet the bandwidth requirement of the service without causing resource waste, and to implement candidates of other available sink nodes when the selected sink node group fails.
The process of the above aggregation node selection method is explained in detail by the following example, as shown in fig. 4, the bandwidth of the aggregation layer back to the expected edge of the received service is 45G, and at the same time, a bandwidth redundancy value of 30% is considered (actually reserved bandwidth of the aggregation layer is 45G minus 1.3: 58.5G), where the required bandwidth of the aggregation layer of the service is 45G, so that a certain redundancy is left in the actual application, and a network congestion situation occurring during the service operation is avoided, so that the actually required bandwidth of the aggregation layer of the service is 58.5G; the operator of the region information is telecom, the region information is located in the Huazhong region, the service type is on-demand acceleration, the residual bandwidth of a first sink node is 21G, the residual bandwidth of a second sink node is 28G, the residual bandwidth of a third sink node is 23G, the residual bandwidth of a fourth sink node is 25G, the residual bandwidth of a fifth sink node is 21G, the selected sink node groups are the first sink node, the second sink node and the third sink node, and the standby sink node groups are the fourth sink node and the fifth sink node
Through the service information and the node weighted redundancy information obtained in the internal training process of the company, a reasonable and effective main and standby combination scheme of the nodes of the convergence layer is calculated.
The embodiment of the present invention also discloses a sink node selecting device, as shown in fig. 2, the device includes:
the acquiring module 201 is configured to acquire current service information, where the current service information includes a service type, a service cold and hot degree, and area information. For example, the details are the contents of step 101 in the above method embodiment, and are not described here again.
A bandwidth weight ratio module 202, configured to obtain a bandwidth weight ratio of the current service based on the service type and a preset service information database. For example, the details are given in the above-mentioned step 102 of the method embodiment, and are not described herein again.
A peak redundancy bandwidth module 203, configured to obtain a peak redundancy bandwidth of the region based on the peak bandwidth of the region information and the bandwidth weight ratio. For example, the details are the contents of step 103 in the above method embodiment, and are not described here again.
A required convergence layer bandwidth module 204, configured to obtain a convergence layer bandwidth required by a convergence layer of the service based on the service cold and hot degrees. For example, the details are given in the above-mentioned step 104 of the method embodiment, and are not described herein again.
An available sink node resource module 205, configured to obtain an available sink node resource of the current service based on the service type and the area information. For example, the details are the contents of step 105 in the above method embodiment, and are not described herein again.
An allocating module 206, configured to allocate the sink node based on the available sink node resource, the peak redundancy bandwidth, and the required sink layer bandwidth. For example, the details are given in the above step 106 of the method embodiment, and are not described herein again.
The device for selecting the sink node comprises an acquisition module 201, a selection module and a selection module, wherein the acquisition module is used for acquiring current service information, and the current service information comprises a service type, a service cold and hot degree and area information; a bandwidth weight ratio module 202, configured to obtain a bandwidth weight ratio of the current service based on the service type and a preset service information database; a peak redundancy bandwidth module 203, configured to obtain a peak redundancy bandwidth of the region based on the peak bandwidth of the region information and the bandwidth weight ratio; a required convergence layer bandwidth module 204, configured to obtain a convergence layer bandwidth required by a convergence layer of the service based on the service cold and hot degrees; an available sink node resource module 205, configured to obtain an available sink node resource of the current service based on the service type and the area information; an allocating module 206, configured to allocate the sink node based on the available sink node resource, the peak redundancy bandwidth, and the required sink layer bandwidth. The corresponding bandwidth weight ratio can be obtained by obtaining the type of the service needing node distribution, the actually required bandwidth of the service can be accurately obtained, the problem of high load running of the sink node is avoided, and the sufficient bandwidth of the sink node is ensured by screening the redundant bandwidth of the sink node in the area where the service is located, so that the bandwidth of the sink node cannot become the bottleneck of the service loading.
As an optional implementation manner of the present invention, the bandwidth weight ratio module 202 includes: the pressure measurement module is used for carrying out incremental pressure measurement on the current service every other first preset time and recording a pressure measurement result after the incremental pressure measurement; the judging module is used for judging whether the pressure measurement result reaches a preset abnormal condition or not; the recording module is used for recording the peak bandwidth of the last measured voltage increase measurement if the preset abnormal condition is reached; and the calculation module is used for obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service. For example, the details are given in the above-mentioned step 102 of the method embodiment, and are not described herein again.
As an optional embodiment of the present invention, the bandwidth weight ratio module 202 further includes: and the continuous measurement module is used for continuously carrying out the incremental pressure measurement if the preset abnormal condition is not met until the preset abnormal condition is met, and executing the step of recording the peak bandwidth of the last incremental pressure measurement to the step of obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service. For example, the details are given in the above-mentioned step 102 of the method embodiment, and are not described herein again.
As an optional embodiment of the present invention, the peak redundancy bandwidth module 203 includes: the acquisition submodule is used for acquiring the peak bandwidth of the area information within a second preset time; and the peak redundancy bandwidth submodule is used for obtaining the peak redundancy bandwidth of the region information based on the peak bandwidth in the second preset time and the bandwidth weight ratio of the existing service in the region information in the second preset time. For example, the details are the contents of step 103 in the above method embodiment, and are not described here again.
As an optional embodiment of the present invention, the available sink node resource module 205 includes: a first available sink node resource module, configured to screen, based on the region information, first available sink node resources in each of the region information; and the second available sink node resource module is used for obtaining the available sink node resources based on the service type and the first available sink node resources. For example, the details are the contents of step 105 in the above method embodiment, and are not described herein again.
As an optional embodiment of the present invention, the allocating module 206 includes: the redundant bandwidth submodule is used for obtaining the redundant bandwidth of each area based on the bandwidth of the required convergence layer of the current service and the bandwidth weight ratio of the current service; and the first sink node group module is used for obtaining a sink node group meeting the required sink layer bandwidth based on the redundant bandwidth, the peak value redundant bandwidth and the available sink node resources. For example, the details are given in the above step 106 of the method embodiment, and are not described herein again.
As an optional implementation manner of the present invention, the allocating module 206 further includes: a residual sink node resource module, configured to determine a residual available sink node resource based on the available sink node resource, the bandwidth capacity of the sink node group, and the redundant bandwidth; and the second sink node group module is used for taking the residual available sink node resources as a standby sink node group. For example, the details are given in the above step 106 of the method embodiment, and are not described herein again.
An embodiment of the present invention further provides a computer device, as shown in fig. 3, the computer device may include a processor 301 and a memory 302, where the processor 301 and the memory 302 may be connected by a bus or in another manner, and fig. 3 takes the example of being connected by a bus as an example.
Processor 301 may be a Central Processing Unit (CPU). The Processor 301 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof.
The memory 302, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the sink node allocation method in the embodiments of the present invention. The processor 301 executes various functional applications and data processing of the processor by running non-transitory software programs, instructions and modules stored in the memory 302, that is, implements the aggregation node allocation method in the above method embodiment.
The memory 302 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor 301, and the like. Further, the memory 302 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 302 may optionally include memory located remotely from the processor 301, which may be connected to the processor 301 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 302 and, when executed by the processor 301, perform the sink node allocation method in the embodiment shown in fig. 1.
The details of the computer device can be understood with reference to the corresponding related descriptions and effects in the embodiment shown in fig. 1, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims (10)

1. A sink node allocation method, comprising:
acquiring current service information, wherein the current service information comprises service types, service cold and hot degrees and regional information;
obtaining the bandwidth weight ratio of the current service based on the service type;
obtaining the peak value redundant bandwidth of the region based on the peak value bandwidth of the region information and the bandwidth weight ratio;
obtaining the required convergence layer bandwidth of the service based on the service cold and hot degree;
obtaining available sink node resources of the current service based on the service type and the area information;
and allocating the sink nodes based on the available sink node resources, the peak redundancy bandwidth and the required sink layer bandwidth.
2. The method of claim 1, wherein the deriving the bandwidth-to-weight ratio of the current service based on the service type comprises:
performing incremental pressure measurement on the current service every first preset time, and recording a pressure measurement result after the incremental pressure measurement;
judging whether the pressure measurement result reaches a preset abnormal condition or not;
if the preset abnormal condition is met, recording the peak bandwidth of the last measured voltage increase;
and obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service.
3. The method of claim 2, further comprising:
and if the preset abnormal condition is not met, continuing to perform the pressure increase measurement until the preset abnormal condition is met, and executing the step of recording the peak bandwidth of the last pressure increase measurement to the step of obtaining the bandwidth weight ratio of the current service based on the peak bandwidth and the outlet bandwidth of the current service.
4. The method of claim 1, wherein obtaining the peak redundancy bandwidth of the region based on the peak bandwidth of the region information and the bandwidth weight ratio comprises:
acquiring the peak bandwidth of the region information within a second preset time;
and obtaining the peak value redundant bandwidth of the region information based on the peak value bandwidth in the second preset time and the bandwidth weight ratio of the existing service in the region information in the second preset time.
5. The method of claim 1, wherein the obtaining the available sink node resources of the current service based on the service type and the area information comprises:
screening first available sink node resources in each region information based on the region information;
and obtaining the available sink node resources based on the service type and the first available sink node resources.
6. The method of claim 1, wherein the performing sink node allocation based on the available sink node resources, peak redundancy bandwidth, and required sink layer bandwidth comprises:
obtaining the redundant bandwidth of each region based on the required convergence layer bandwidth of the current service and the bandwidth weight ratio of the current service;
and obtaining a sink node group meeting the required sink layer bandwidth based on the redundant bandwidth, the peak value redundant bandwidth and the available sink node resources.
7. The method of claim 6, further comprising:
determining remaining available sink node resources based on the available sink node resources, bandwidth capacity of sink node groups, and redundant bandwidth;
and taking the residual available sink node resources as a standby sink node group.
8. An apparatus for selecting sink nodes, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring current service information, and the current service information comprises a service type, a service cold and hot degree and area information;
a bandwidth weight ratio module, configured to obtain a bandwidth weight ratio of the current service based on the service type;
the peak value redundant bandwidth module is used for obtaining the peak value redundant bandwidth of the region based on the peak value bandwidth of the region information and the bandwidth weight ratio;
the required convergence layer bandwidth module is used for obtaining the convergence layer bandwidth required by the convergence layer of the service based on the service cold and hot degree;
the available sink node resource module is used for obtaining the available sink node resources of the current service based on the service type and the area information;
and the distribution module is used for carrying out sink node distribution based on the available sink node resources, the peak value redundancy bandwidth and the required sink layer bandwidth.
9. A computer device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the sink node allocation method according to any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the sink node allocation method according to any one of claims 1 to 7.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014082538A1 (en) * 2012-11-30 2014-06-05 中兴通讯股份有限公司 Business scheduling method and apparatus and convergence device
WO2017088393A1 (en) * 2015-11-26 2017-06-01 乐视控股(北京)有限公司 Bandwidth allocation method and system
CN107465708A (en) * 2016-06-02 2017-12-12 腾讯科技(深圳)有限公司 A kind of CDN bandwidth scheduling systems and method
CN108234632A (en) * 2017-12-29 2018-06-29 北京奇虎科技有限公司 A kind of data distributing method and device of content distributing network CDN
WO2020125539A1 (en) * 2018-12-20 2020-06-25 华为技术有限公司 Node device selecting method and related device thereof
CN111800486A (en) * 2020-06-22 2020-10-20 山东大学 Cloud edge cooperative resource scheduling method and system
WO2021051457A1 (en) * 2019-09-20 2021-03-25 网宿科技股份有限公司 Method for preheating resource file, and central management system
CN113296924A (en) * 2020-04-28 2021-08-24 阿里巴巴集团控股有限公司 Content distribution method, device, system and storage medium

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014082538A1 (en) * 2012-11-30 2014-06-05 中兴通讯股份有限公司 Business scheduling method and apparatus and convergence device
WO2017088393A1 (en) * 2015-11-26 2017-06-01 乐视控股(北京)有限公司 Bandwidth allocation method and system
CN107465708A (en) * 2016-06-02 2017-12-12 腾讯科技(深圳)有限公司 A kind of CDN bandwidth scheduling systems and method
CN108234632A (en) * 2017-12-29 2018-06-29 北京奇虎科技有限公司 A kind of data distributing method and device of content distributing network CDN
WO2020125539A1 (en) * 2018-12-20 2020-06-25 华为技术有限公司 Node device selecting method and related device thereof
WO2021051457A1 (en) * 2019-09-20 2021-03-25 网宿科技股份有限公司 Method for preheating resource file, and central management system
CN113296924A (en) * 2020-04-28 2021-08-24 阿里巴巴集团控股有限公司 Content distribution method, device, system and storage medium
CN111800486A (en) * 2020-06-22 2020-10-20 山东大学 Cloud edge cooperative resource scheduling method and system

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
AO AL-ABBASI: ""EdgeCache: An optimized algorithm for CDN-based over-the-top video streaming services"", 《IEEE》, 31 December 2018 (2018-12-31) *
乐光学;戴亚盛;杨晓慧;刘建华;游真旭;朱友康;: "边缘计算可信协同服务策略建模", 计算机研究与发展, no. 05, 15 May 2020 (2020-05-15) *
郑凯月: ""内容中心网络路由和缓存技术研究"", 《中国优秀硕士学位论文全文数据库》, 16 December 2018 (2018-12-16) *

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