CN114285770B - Full-link-detection-based pcdn node evaluation method, terminal and medium - Google Patents
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Abstract
The invention discloses a pcdn node evaluation method and a terminal based on full link detection, which take a scheduling request node as a center, search detected nodes around the scheduling request node, calculate the distance index and direction from each detected node to the scheduling request node and the multi-path detection comprehensive availability index of the detected node, search edge detection nodes around the detected nodes, combine the directions, the distances and the multi-paths, calculate the multi-path detection comprehensive availability index of each detected node, obtain the path weighting availability index of each detected node, select a proper detected node as a link node according to the path weighting availability index, and improve the scheduling success rate.
Description
Technical Field
The invention relates to the technical field of pcdn, in particular to a pcdn node evaluation method and terminal based on full link detection.
Background
In the pcdn system, a large number of edge nodes for customers exist, the edge nodes are either ordinary boxes or ordinary service single points, and due to cost factors, the number of the ordinary edge nodes distributed in the whole country is not enough, so that a certain edge node can be used by an extravagant scheduling request, the stability of the edge node is poorer than that of the traditional cdn IDC machine room resource, so that in the pcdn system, the evaluation of the availability of the edge nodes becomes an important technical link, and if a certain edge node is unavailable, the scheduling again uses the node, the scheduling request fails, and the scheduling success rate index is influenced. Meanwhile, even if the node is available, a link from different geographical locations in each province (large area) to an edge node may fail to be scheduled due to network delay and link problems.
The current scheduling request calling mode is carried out in a one-to-one mode of node and center service, in the detection information, the availability index of the line is only available or unavailable, and the data detected by the method has the problems of single result and low availability. If the central service is in Beijing and the node is in Shanghai, the single scheduling method can only indicate that the scheduling request is going out from the vicinity of Beijing and the node in Shanghai is probably successful. However, if a scheduling request of Zhejiang is received, under the condition that the node in the province is not enough, the node in the adjacent province needs to be selected for scheduling, and the detection mode cannot well reflect the availability of scheduling.
Therefore, how to evaluate the availability of the node and select the detected node according to the availability is an urgent problem to be solved at present.
Disclosure of Invention
The invention aims to provide a pcdn node evaluation method and a terminal based on full-link detection.
In a first aspect, the above object of the present invention is achieved by the following technical solutions:
a pcdn node evaluation method based on full link detection is characterized by taking a scheduling request node as a center, searching detected nodes around the scheduling request node, calculating a distance index and a direction from each detected node to the scheduling request node and a multi-path detection comprehensive availability index of the detected nodes, obtaining a path weighted availability index of each detected node, and selecting a proper detected node as a link node according to the path weighted availability index.
The invention is further configured to: and searching peripheral edge detection nodes by taking each detected node as a sub-center, and calculating the multi-path detection comprehensive availability index of each detected node by taking the directions of each edge detection node and the detected node as parameters.
The invention is further configured to: setting a direction coefficient for each edge detection node, setting the direction coefficient of the edge detection node consistent with the scheduling request direction as the maximum value by combining the availability index of each edge detection node, and calculating the multi-channel detection comprehensive availability index of the detected node.
The invention is further configured to: and setting the proportion of the distance index, the multi-path detection comprehensive availability index of each detected node and the central detection availability index in the path weighted availability, and calculating the path weighted availability index of each detected node.
The invention is further configured to: the sum of the distance index ratio, the multi-path detection comprehensive availability index ratio of each detected node and the center detection availability index ratio is 1, and the sum of the direction coefficients of all the edge detection nodes is 1.
The invention is further configured to: the calculation formula of the path weighted availability of the detected node is as follows:
path weighted availability = distance occupancy + multi-probe integrated availability index + multi-probe occupancy + central probe availability index + central probe occupancy.
The invention is further configured to: the maximum availability index value of all the detected nodes is taken as the link node, and the calculation formula of the multi-path detection comprehensive availability index is as follows: multi-path detection integrated availability index = edge detection node 1 detection availability x edge detection node 1 direction coefficient + edge detection node 2 detection availability x edge detection node 2 direction coefficient + … … + edge detection node n detection availability x edge detection node n direction coefficient; in the formula, n represents the number of edge detection nodes.
The invention is further configured to: the scheduling request node, the detected node and the edge detection node belong to different provinces respectively.
In a second aspect, the above object of the present invention is achieved by the following technical solutions:
a full link probing based pcdn node evaluation terminal comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the method.
In a third aspect, the above object of the present invention is achieved by the following technical solutions:
a computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, carries out the method of the present application.
Compared with the prior art, the beneficial technical effect of this application does:
1. according to the method, the detection result is evaluated by detecting a certain edge node through the detection points in different directions and different positions, and the scheduling success rate is improved;
2. further, different distance indexes are selected according to different distances between the detected nodes and the scheduling request nodes, the distances are taken into consideration, and the probability of selecting the detected nodes with the closer distances is improved;
3. furthermore, the multi-path detection comprehensive availability index of the detected node is determined according to the availability of the edge detection node to the detected node, the edge node factor of the detected node is considered, and the scheduling success probability of the detected node is improved.
Drawings
FIG. 1 is a schematic illustration of a scheduling application of an embodiment of the present application;
fig. 2 is a schematic diagram of a detection mode of an embodiment of the present application.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Detailed description of the preferred embodiment
According to the pcdn node evaluation method based on full link detection, a scheduling request node makes a request to a central service, the central service takes the scheduling request node as a center, and the central service sends the request to each detected node around the center and receives return information.
And selecting a plurality of detected nodes from different directions around the scheduling request node, wherein the distances between the detected nodes and the scheduling request node are different, and the detected nodes are selected according to the directions and the distances.
Setting a distance index and a multi-path detection comprehensive availability index for each detected node, then combining a central detection availability index of a central service for the detected node, calculating the path weighted availability of each detected node, and selecting one detected node as a link node according to the size of the path weighted availability index value.
Setting the occupation ratios of the distance index, the multi-path detection comprehensive availability index and the central detection availability index, wherein the sum of the occupation ratios is 1, and calculating the path weighted availability according to the occupation ratios of the indexes, wherein the calculation formula is as follows:
path weighted availability = distance index occupancy + multi-probe integrated availability index + multi-probe occupancy + central probe availability index.
At least one edge detection node is arranged around each detected node and is used for detecting the controlled node, and each edge detection node is used for detecting the detected node and generating detection data.
The relation between each detected node and a plurality of edge detection nodes is marked by a multi-path detection comprehensive availability index, a direction coefficient is set for each edge detection node, an availability parameter of each edge detection node is selected, if the availability parameter of each edge detection node is represented by 1 when available and is represented by 0 when unavailable, and the multi-path detection comprehensive availability index of each detected node is calculated, and the following formula is shown:
multi-path probing integrated availability index = edge probing node 1 probing availability × edge probing node 1 directional coefficient + edge probing node 2 probing availability × edge probing node 2 directional coefficient + … … + edge probing node n probing availability × edge probing node n directional coefficient.
The direction coefficient represents the consistency between the scheduling direction of the scheduling request node and the detection direction of the edge detection node, and the larger the direction coefficient is, the higher the consistency is.
In the formula, n represents the number of edge detection nodes.
And after the path weighted availability of each detected node is calculated, selecting the detected node with the maximum path weighted availability value as a link node.
In a specific embodiment of the present application, a case where a scheduling request node is located in one province, a detected node is located in a neighborhood province of the scheduling request node, and an edge detection node is located in a monitoring province of the detected node is taken as an example for explanation, and so on and description thereof are omitted for the case where each node is located in the same province or part of nodes are located in different provinces.
If a scheduling request is sent from the Anhui, but the central service does not find an available scheduling node in this province, the range of the scheduling node is expanded to the adjacent provinces, as shown in FIG. 1, 4 adjacent provinces are nearby to select a node set, which respectively is: and performing availability judgment on the adjacent nodes as detected nodes in Henan, Jiangsu, Hubei and Zhejiang. The closer the distance is, the higher the index value is, if the distances from the detected nodes in Hubei, Henan, Jiangsu and Zhejiang to the Anhui scheduling request node are successively higher, the distance index values are 0.6, 0.59, 0.58 and 0.57 respectively.
The multi-path detection comprehensive index ratio is 0.3, and the central detection ratio is 0.1.
Taking a northHu node as an example, calculating the availability of the detected node for the scheduling, and first establishing a schematic diagram of the northHu node being detected, as shown in fig. 2:
as the detected node, 4 edge detection nodes are arranged around the detected node and detect the detected node, namely Anhui, Shaanxi, Hunan and Jiangxi, because the trigger of the scheduling request is Anhui, the request of Anhui for detecting Hubei is most consistent with the scheduling direction of Hubei for scheduling Anhui in direction, the reference meaning is the largest, the reference proportion is the highest, the detection reference meanings of other three regions are lower, and the reference proportion is relatively lower.
When the availability of the Hubei node in the scheduling is calculated, the coefficient which is most consistent in direction is the highest, the detection direction coefficient from Anhui to Hubei is set to be 0.7, three edge detection nodes in Shaanxi, Hunan and Jiangxi are not matched in direction, and the direction coefficients are set to be 0.1; the detection availability index from Anhui to Hubei is 1, indicating availability. Where 1 is available and 0 is not. The detection availability in the two directions of shanxi and Hunan is 1, and the detection availability in the direction of Jiangxi is 0, so that the multi-path detection comprehensive availability index =0.7 × 1+0.1 × 0= 0.9.
Then the path weighted availability metric for the probed node north of hu =0.6+ (0.7 x 1+0.1 x 0) × 0.3+ 1 x 0.1= 0.97.
According to the same method, the path weighted availability index of the detected nodes in Henan, the path weighted availability index of the detected nodes in Jiangsu and the path weighted availability index of the detected nodes in Zhejiang are calculated.
And comparing the path weighted availability indexes of the detected nodes of Hubei, Henan, Jiangsu and Zhejiang, and taking the maximum path weighted availability index value as a link node.
The path weighted availability index of a certain detected node is 1 at the maximum value.
Detailed description of the preferred embodiment
An embodiment of the present invention provides a pcdn node evaluation terminal device based on full link probing, where the terminal device in the embodiment includes: a processor, a memory and a computer program, such as a path weighted availability calculation program, stored in the memory and executable on the processor, the processor implementing the method of embodiment 1 when executing the computer program.
Alternatively, the processor, when executing the computer program, implements the functions of the modules/units in the above device embodiments, for example: a calculating characteristic module and a judging module.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to implement the invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program in the full link probing based pcdn node evaluation terminal device. For example, the computer program may be divided into a plurality of modules, each module having the following specific functions:
1. the multi-channel detection comprehensive availability calculating module is used for calculating the multi-channel detection comprehensive availability;
2. and the path weighted availability calculating module is used for calculating a path weighted availability value.
The pcdn node evaluation terminal device based on full link detection can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing devices. The pcdn node evaluation terminal device based on full link probing may include, but is not limited to, a processor, and a memory. It will be appreciated by those skilled in the art that the above examples are merely examples of the evaluation terminal device for the full link probing-based pcdn node, and do not constitute a limitation of the evaluation terminal device for the full link probing-based pcdn node, and may include more or less components than those shown in the figures, or combine some components, or different components, for example, the evaluation terminal device for the full link probing-based pcdn node may further include an input/output device, a network access device, a bus, and the like.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor is a control center of the kind of full link probing based pcdn node evaluation terminal device, and various interfaces and lines are used to connect various parts of the whole kind of full link probing based pcdn node evaluation terminal device.
The memory can be used for storing the computer program and/or the module, and the processor can realize various functions of the pcdn node evaluation terminal device based on full link detection by running or executing the computer program and/or the module stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Detailed description of the preferred embodiment
The pcdn node evaluation terminal device integrated module/unit based on full link detection can be stored in a computer readable storage medium if being implemented in the form of a software functional unit and sold or used as an independent product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc.
The embodiments of the present invention are all preferred embodiments of the present invention, and the scope of the present invention is not limited thereby, so: equivalent changes made according to the structure, shape and principle of the invention shall be covered by the protection scope of the invention.
Claims (10)
1. A pcdn node evaluation method based on full link detection is characterized in that: after receiving a request of a scheduling request node, a central service searches a plurality of detected nodes in different directions around the scheduling request node by taking the scheduling request node as a center, the distances between the detected nodes and the scheduling request node are different, at least one edge detection node also detects the detected nodes around each detected node, a direction coefficient is set for each edge detection node around the detected node, an availability parameter of each edge detection node is selected, each edge detection node detects the detected node to generate detection availability data, a multi-path detection comprehensive availability index of each detected node is calculated based on the detection availability data of each edge detection node, and the central detection availability index of the detected node, the distance index from each detected node to the scheduling request node, the multi-path detection comprehensive availability index of each detected node are calculated based on the central detection availability index of the central service, The direction coefficients of each detected node and a plurality of edge detection nodes, the multi-path detection comprehensive availability index of each detected node, and the central service acquiring the path weighted availability index of each detected node, and selecting a proper detected node as a link node of the scheduling request node according to the path weighted availability index.
2. The pcdn node evaluation method according to claim 1, wherein: and taking each detected node as a sub-center, searching peripheral edge detection nodes, and calculating the multi-path detection comprehensive availability index of each detected node according to the direction coefficient of each edge detection node and the detected node and the availability parameter of each edge detection node.
3. The pcdn node evaluation method based on full link probing according to claim 2, wherein: setting a direction coefficient for each edge detection node, setting the direction coefficient of the edge detection node with the direction from the detected node to the edge detection node consistent with the scheduling request direction from the detected node to the scheduling request node as the maximum by combining the availability index of each edge detection node, and calculating the multi-path detection comprehensive availability index of the detected node.
4. The pcdn node evaluation method according to claim 3, wherein: and setting the ratio of the distance index, the multi-path detection comprehensive availability index of each detected node and the central detection availability index in the path weighted availability, and calculating the path weighted availability index of each detected node.
5. The pcdn node evaluation method based on full link probing according to claim 4, wherein: the sum of the distance index ratio, the multi-path detection comprehensive availability index ratio of each detected node and the center detection availability index ratio is 1, and the sum of the direction coefficients of all the edge detection nodes is 1.
6. The pcdn node evaluation method based on full link probing according to claim 4, wherein: the calculation formula of the path weighted availability of the detected node is as follows:
path weighted availability + integrated availability index for multi-path probing + central probing availability index for central probing.
7. The pcdn node evaluation method based on full link probing according to claim 1, wherein: the maximum availability index value of all the detected nodes is taken as the link node, and the calculation formula of the multi-path detection comprehensive availability index is as follows:
the multi-path detection integrated availability index is edge detection node 1 detection availability, edge detection node 1 direction coefficient, edge detection node 2 detection availability, edge detection node 2 direction coefficient, … …, and edge detection node n detection availability, edge detection node n direction coefficient; in the formula, n represents the number of edge detection nodes.
8. The pcdn node evaluation method according to claim 2, wherein: the scheduling request node, the detected node and the edge detection node belong to different provinces respectively.
9. A full link probing based pcdn node evaluation terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: the processor, when executing the computer program, implements the method of any of claims 1-8.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 8.
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Denomination of invention: A PCDN node evaluation method, terminal, and medium based on full link detection Effective date of registration: 20230810 Granted publication date: 20220923 Pledgee: Beijing Guohua Arts Financing Guarantee Co.,Ltd. Pledgor: Instant Wulian Technology (Beijing) Co.,Ltd. Registration number: Y2023990000403 |