Node resource planning method and device, electronic equipment and readable storage medium

Abstract

The invention relates to the technical field of content distribution networks, and provides a node resource planning method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining the historical reference information of a target region containing a plurality of target nodes, the historical reference information comprises the sum of the upper limits of the target nodes and the sum of the lowest planning lines of the target nodes, the sum of bandwidth peak values of target nodes located in the user area is obtained; determining bandwidth hyper-planning points based on the sum of the upper limits of the target nodes and the sum of the bandwidth peak values; determining a planning value sum of the target large area from the bandwidth peak sum according to the bandwidth hyper-planning point number; and determining a target planning line of the target node based on a comparison result of the planning value sum and preset conditions, the preset conditions including a node upper limit condition and a node lowest planning line condition. According to the technical scheme provided by one or more embodiments of the invention, the node planning line can be quickly and accurately calculated, and the bandwidth cost is reduced while the node service quality is ensured.

Description

Technical Field

[0001] The present disclosure relates to the technical field of content distribution networks, and in particular to a node resource planning method, device, electronic device and readable storage medium. Background Art

[0002] Content Delivery Network (CDN) is a new type of network content service system. CDN is built on IP network and provides content distribution and services based on the efficiency requirements, quality requirements and content order of content access and application.

[0003] A node is the smallest unit for bandwidth billing and settlement between CDN vendors and operators. Due to the different network construction architectures of different operators in different provinces, there are many different node bandwidth billing methods. In order to control node bandwidth costs, concepts such as node upper limit, node billing line, node minimum planning line, and node planning line are usually involved. Among them, the node upper limit is the bandwidth line at which the node can provide normal services; the node billing line is the bandwidth line that the CDN vendor actually settles with the operator; the node bottom line is the minimum billing bandwidth line signed by the CDN vendor and the operator; the node planning line can represent a bandwidth line that is planned in advance for scheduling, reference, and cost control based on past customer resource demands and future customer resource demands.

[0004] The operating costs of CDN generally include the operating costs of the computer room, bandwidth costs, etc., and bandwidth costs usually account for a large proportion. Therefore, in the field of content distribution network technology, the planning and control of node bandwidth costs is particularly important. Summary of the invention

[0005] In view of this, one or more embodiments of the present disclosure provide a node resource planning method, device, electronic device and readable storage medium, which can quickly and accurately calculate the node planning line, ensure the node service quality while reducing bandwidth costs.

[0006] On the one hand, the present disclosure provides a node resource planning method, the method comprising: obtaining historical reference information of a target region including multiple target nodes, the historical reference information comprising the sum of target node upper limits of each of the target nodes, the sum of target node lowest planning lines of each of the target nodes, and the bandwidth peak sum of the target nodes located in the user area, the bandwidth peak sum being a data group divided according to a preset time granularity, the target node lowest planning line being determined based on a target node bottom line, a target node charging line, and a target node upper limit; determining bandwidth over-planning points based on the sum of the target node upper limits and the bandwidth peak sum; determining the total planning value of the target region from the bandwidth peak sum according to the bandwidth over-planning points; determining the target planning line of the target node based on a comparison result of the total planning value and a preset condition, the preset condition comprising a node upper limit condition and a node lowest planning line condition.

[0007] On the other hand, the present disclosure also provides a node resource planning device, the device comprising: an information acquisition unit, used to acquire historical reference information of a target region including multiple target nodes, the historical reference information comprising the sum of target node upper limits of each of the target nodes, the sum of target node lowest planning lines of each of the target nodes, and the bandwidth peak sum of the target nodes located in the user area, the bandwidth peak sum being a data group divided according to a preset time granularity, the target node lowest planning line being determined based on the target node bottom line, the target node billing line and the target node upper limit; a first planning unit, used to determine the number of bandwidth over-planning points based on the sum of the target node upper limits and the bandwidth peak sum; a second planning unit, used to determine the total planning value of the target region from the bandwidth peak sum according to the bandwidth over-planning points; a third planning unit, used to determine the target planning line of the target node based on a comparison result of the planning value sum with a preset condition, the preset condition comprising a node upper limit condition and a node lowest planning line condition.

[0008] On the other hand, the present disclosure further provides an electronic device, which includes a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the above-mentioned node resource planning method is implemented.

[0009] On the other hand, the present disclosure further provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the above-mentioned node resource planning method is implemented.

[0010] The technical solution provided by one or more embodiments of the present disclosure can obtain historical reference information of the target region, and obtain the performance characteristics and billing characteristics of each target node in the region, as well as the bandwidth usage characteristics of the user area. Using specific algorithm rules, the number of bandwidth over-planning points can be determined, and then the appropriate sum of bandwidth planning values ​​can be determined. According to the comparison result of the sum of planning values ​​and preset conditions, the planning line of each target node can be quickly given.

[0011] The technical solution provided by one or more embodiments of the present disclosure can quickly provide a node planning line adjustment plan that is beneficial to bandwidth cost control while ensuring quality, and can promptly provide an optimal node resource plan when needed. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The features and advantages of the embodiments of the present disclosure may be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the present disclosure in any way. In the accompanying drawings:

[0013] Figure 1 A schematic diagram showing the steps of a node resource planning method in one embodiment of the present disclosure is shown;

[0014] Figure 2 A schematic diagram showing a flow chart of a node resource planning method in one embodiment of the present disclosure is shown;

[0015] Figure 3 A schematic diagram of functional units of a node resource planning device in one embodiment of the present disclosure is shown;

[0016] Figure 4 A schematic structural diagram of an electronic device in one embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0018] In related technologies, under the premise of ensuring node service quality, it is generally necessary to manually plan existing resources based on past node bandwidth usage and future customer resource needs. Manual planning is demanding, time-consuming and labor-intensive, and resource coverage and actual customer bandwidth requirements vary greatly, making it impossible to give the best plan for overall resources.

[0019] In view of this, a node resource planning method provided in one embodiment of the present disclosure can quickly and accurately calculate the node planning line, thereby ensuring the node service quality while reducing the bandwidth cost. Figure 1 , a node resource planning method provided by an embodiment of the present disclosure may include the following multiple steps.

[0020] S1: Obtain historical reference information of a target area including multiple target nodes, the historical reference information includes the sum of target node upper limits of each target node, the sum of target node lowest planning lines of each target node, and the bandwidth peak sum of the target nodes located in the user area, the bandwidth peak sum is a data group divided according to a preset time granularity, and the target node lowest planning line is determined based on the target node bottom line, the target node billing line and the target node upper limit.

[0021] In this embodiment, the target region may be a collection of related CDN acceleration regions, and the target node may be each service node of the CDN acceleration region. Obtaining historical reference information of the target region may be obtaining reference information within a certain time range, such as one day, one week, one month, etc. The historical reference information may include node upper limit information of each target node, thereby characterizing the performance characteristics of the target node. The historical reference information may include node minimum planning line information of each target node, thereby characterizing the billing characteristics of the target node. The historical reference information may also include the sum of the bandwidth peaks of the target nodes in the user area, thereby characterizing the bandwidth usage characteristics of the user area.

[0022] In a practical application example, the sum of the node upper limits and the sum of the node minimum planning lines at the operator's regional granularity can be obtained and calculated, as well as the sum of the customer area bandwidth peaks at each 5-minute granularity within the calculation date.

[0023] In some implementations, for any target node, the target node bottom line, the target node charging line, and the target node upper limit can be obtained. The larger value of the target node bottom line and the target node charging line is selected as the first comparison result. The smaller value of the first comparison result and the target node upper limit is selected as the second comparison result. The second comparison result can be determined as the lowest planning line of the target node.

[0024] For example, it can be calculated by the following formula: Node minimum planning line = MIN (MAX (node ​​bottom line, node charging line), node upper limit). The MIN symbol indicates the minimum value of the data, and the MAX symbol indicates the maximum value of the data.

[0025] S2: Determine the number of bandwidth over-planning points based on the sum of the upper limits of the target nodes and the sum of the bandwidth peaks.

[0026] In this implementation manner, specific algorithm rules may be used to determine the number of bandwidth over-planning points based on the sum of the upper limits of the target nodes, the sum of the bandwidth peaks, and some pre-acquired fixed parameters.

[0027] In some implementations, the first coefficient may be determined based on the sum of the upper limits of the target nodes, the stress test bandwidth discount coefficient, the number of the preset time granularities per unit time, the monthly free duration of the billing node, and the utilization ratio of the free duration. The second coefficient may be determined based on the maximum value of the bandwidth peak value and the bandwidth over-planning points may be determined based on the ratio of the first coefficient to the second coefficient. The calculated point value may be rounded up.

[0028] In an actual application example, the number of points where the customer area bandwidth exceeds the planning line is calculated = the sum of the upper limit of the operator's regional nodes * 0.9 * 12 * 36 * 0.7 / MAX (the sum of the peak bandwidth of the customer area at a 5-minute granularity). Among them, 0.9 is the stress test bandwidth discount coefficient, 12 is the number of 5 minutes per hour, 36 is the monthly free time of 95 billing nodes (in hours), and 0.7 is the utilization ratio of the node free time.

[0029] S3: According to the number of bandwidth over-planning points, determine the total planned value of the target area from the bandwidth peak value sum.

[0030] In this embodiment, the bandwidth excess planning points are used to determine the appropriate sum of bandwidth planning values. For example, the bandwidth peak sums can be sorted in descending order according to the value size. For the sorted bandwidth peak sums, the bandwidth peak sums at the positions corresponding to the bandwidth excess planning points can be selected as the sum of planning values. In this way, it can be ensured that the selected sum of bandwidth planning values ​​meets the actual needs of users, and it can avoid selecting excessive broadband planning values ​​to prevent waste of resources.

[0031] In an actual application example, the peak sum of customer area bandwidth at 5-minute granularity can be sorted in descending order. Then, the peak sum of customer area bandwidth at the position of "the number of points where the customer area bandwidth exceeds the planning line" is taken as the sum of the operator's regional planning values.

[0032] S4: Determine the target planning line of the target node based on the comparison result of the sum of the planning values ​​and the preset conditions, wherein the preset conditions include a node upper limit condition and a node minimum planning line condition.

[0033] In this embodiment, the planning line of each target node can be quickly given according to the comparison result of the total planning value and the preset conditions. The preset conditions include the node upper limit condition and the node minimum planning line condition, so that the final target planning line can take into account both the lower node bandwidth cost and the higher node service quality.

[0034] In some implementations, when the sum of the planning values ​​is greater than the sum of the upper limits of the target nodes, the upper limit of the target node is determined as the target planning line of the target node.

[0035] For example, if the sum of the operator's regional planning values ​​is greater than the sum of the operator's regional node upper limits, it means that the regional node resources are insufficient, and the node planning line can be set to the node upper limit.

[0036] In some embodiments, when the sum of the planning values ​​is not greater than the sum of the upper limits of the target nodes, and the sum of the planning values ​​is less than the sum of the lowest planning lines of the target nodes, the lowest planning line of the target node is determined as the target planning line of the target node.

[0037] For example, if the sum of the operator region planning values ​​is less than or equal to the sum of the operator region node upper limits, and the sum of the operator region planning values ​​is less than the sum of the operator region node lowest planning lines, the node planning line can be set to the node lowest planning line.

[0038] In some embodiments, when the sum of the planning values ​​is not greater than the sum of the upper limits of the target nodes, and the sum of the planning values ​​is not less than the sum of the lowest planning lines of the target nodes, the planning value to be allocated is determined based on the sum of the planning values ​​and the sum of the lowest planning lines of the target nodes, and the target planning line of the target node is determined based on the planning value to be allocated.

[0039] For example, the sum of the operator's regional planning values ​​minus the sum of the operator's regional nodes' lowest planning lines can be used as the regional planning value to be allocated.

[0040] In some embodiments, the target planning line is determined based on the planning value to be allocated, including: sorting the target nodes in ascending order according to the node bandwidth price; calculating the sum of the planning value to be allocated and the lowest planning line of the first node for the first node of the sorted target nodes; comparing the sum with the upper limit of the first node; determining the first planning line of the first node according to the comparison result; subtracting the first node difference from the planning value to be allocated, and updating the planning value to be allocated, wherein the first node difference is determined by the upper limit of the first node and the lowest planning line of the first node; iteratively processing the next node of the first node until the planning value to be allocated is zero.

[0041] In some embodiments, determining the first planning line of the first node based on the comparison result includes: if the added value is greater than or equal to the first node upper limit, determining the first node upper limit as the first planning line of the first node; if the added value is less than the first node upper limit, determining the added value as the first planning line of the first node.

[0042] In a practical application example, the nodes to be planned can be sorted in ascending order (cheaper ones in front) according to the node bandwidth price (determined by the network operator). If the planning value to be allocated is > 0, then determine whether the "node minimum planning line + planning value to be allocated" is >= the node upper limit; if yes, then the node planning line = node upper limit; if not, then the node planning line = node minimum planning line + planning value to be allocated. After deducting the allocated value from the planning value to be allocated, the next node can be processed until the planning value to be allocated = 0. If the planning value to be allocated = 0, the node has not been processed yet, and the node planning line of the remaining nodes = the node minimum planning line.

[0043] See also Figure 2 , a node resource planning method provided in one embodiment of the present disclosure can be implemented through the following steps.

[0044] Step S201: Calculate the peak bandwidth sum of each customer area at the operator-region granularity within the calculation date for each 5-minute granularity. For example, for operator A-region B, the peak bandwidth sum of each customer area at each 5-minute granularity for one month is 288*30=1440 values ​​in total.

[0045] Step S202: Calculate the sum of the upper limits of the nodes at the operator-region granularity. For example, operator A-region B, 10 nodes, the sum of the upper limits is 500 Gbps.

[0046] In this embodiment, the node upper limit is the stress test bandwidth of the node. If the node bandwidth is greater than the upper limit, it is considered that the node cannot provide normal or complete services, which will affect the service quality of customer acceleration.

[0047] Step S203: Calculate the sum of the minimum planning line of the node at the operator-region granularity. For example, in operator A-region B, the minimum planning line of the node = MIN (MAX (node ​​guarantee line 200Gbps, node billing line 230Gbps), node upper limit 500Gbps) = 230Gbps.

[0048] In this embodiment, the node guarantee line is the minimum billing bandwidth line signed with the operator, and the node billing line is the bandwidth line actually settled with the operator.

[0049] Step S204: Calculate the number of points where the customer area bandwidth exceeds the planning line = [operator - sum of the upper limits of the regional nodes] * 0.9 * 12 * 36 * 0.7 / MAX (sum of the peak bandwidth of the customer area at 5-minute granularity). Among them, 0.9 is the stress test bandwidth discount coefficient, 12 is the number of 5 minutes per hour, 36 is the monthly free time of 95 billing nodes (in hours), and 0.7 is the utilization ratio of the node free time. The point value can be rounded up. For example, the number of points exceeding the planning line in operator A-region B = 1368.

[0050] Step S205: Sort the peak sum of customer area bandwidth at 5-minute granularity in descending order, and take the peak sum of customer area bandwidth at the position [number of points where customer area bandwidth exceeds the planning line] in step S204 as the [sum of operator-region planning values]. For example, for operator A-region B, take the bandwidth value corresponding to the 1368th point = 360 Gbps.

[0051] Step S206: Determine whether [operator-region planning value sum]>[operator-region node upper limit sum]. For example, operator A-region B, planning value sum = 360, upper limit sum = 500, because 360<500, proceed to the next step S207.

[0052] Step S207: Determine whether [operator-region planning value sum]>=[operator-region node minimum planning line sum]. For example, operator A-region B, planning value sum=360, minimum planning line sum=230, because 360>230, proceed to next step S208.

[0053] Step S208: At this time, the planning value to be allocated in the region = [operator - total planning value of the region] - [operator - sum of the lowest planning lines of the region granular nodes]. For example, for operator A and region B, the total planning value = 360, the sum of the lowest planning lines = 230, and the planning value to be allocated = 360-230 = 130.

[0054] Step S209: The nodes to be planned are sorted in ascending order (cheaper ones are at the front) according to the node bandwidth price (determined by the network operator). For example, in operator A-region B, there are 10 nodes, which are sorted as node 1, node 2, ..., node 10.

[0055] Step S210: If the planning value to be allocated is > 0, determine whether "node minimum planning line + planning value to be allocated" > = node upper limit; if yes, node planning line = node upper limit; if no, node planning line = node minimum planning line + planning value to be allocated. Subtract the allocated value from the planning value to be allocated, and then process the next node until the planning value to be allocated = 0.

[0056] For example, in operator A-region B, node 1: the lowest planning line = 20, the upper limit = 100, and the planning value to be allocated = 130, then 20+130=150>100, the planning line of node 1 = 100, and the value to be allocated = 130-(100-20) = 50;

[0057] Node 2: The lowest planning line = 20, the upper limit = 100, then 20 + 50 = 70 < 100, the planning line of node 2 = 70, and the value to be allocated = 0;

[0058] If the node has not been processed yet, proceed to the next step S211.

[0059] Step S211: If the planning value to be allocated = 0, and the node has not been processed, then the node planning line = the lowest planning line of the node. For example, in operator A-region B, the planning value to be allocated = 0, and there are 8 nodes that have not been processed, so the planning lines of nodes 3 to 10 are all equal to the lowest planning line of the node.

[0060] In this implementation, while ensuring quality, the billing cost characteristics of the node, the bandwidth characteristics of the operator region and the customer area are combined, and a special super-planning point algorithm and special allocation rules are used to quickly provide a cost control planning line adjustment plan. Calculations and planning line adjustments can be performed at any time when necessary to provide the optimal node plan.

[0061] The technical solution provided by one or more embodiments of the present disclosure can obtain historical reference information of the target region, and obtain the performance characteristics and billing characteristics of each target node in the region, as well as the bandwidth usage characteristics of the user area. Using specific algorithm rules, the number of bandwidth over-planning points can be determined, and then the appropriate sum of bandwidth planning values ​​can be determined. According to the comparison result of the sum of planning values ​​and preset conditions, the planning line of each target node can be quickly given.

[0062] The technical solution provided by one or more embodiments of the present disclosure can quickly provide a node planning line adjustment plan that is beneficial to bandwidth cost control while ensuring quality, and can promptly provide an optimal node resource plan when needed.

[0063] See also Figure 3 The present disclosure also provides a node resource planning device, the device comprising:

[0064] The information acquisition unit 100 is used to acquire historical reference information of a target region including multiple target nodes, the historical reference information including the sum of target node upper limits of each target node, the sum of target node lowest planning lines of each target node, and the bandwidth peak sum of the target nodes located in the user area, the bandwidth peak sum is a data group divided according to a preset time granularity, and the target node lowest planning line is determined based on the target node guarantee line, the target node billing line and the target node upper limit;

[0065] The first planning unit 200 is used to determine the number of bandwidth over-planning points based on the sum of the upper limits of the target nodes and the sum of the bandwidth peak values;

[0066] The second planning unit 300 is used to determine the total planning value of the target large area from the bandwidth peak value sum according to the bandwidth over-planning points;

[0067] The third planning unit 400 is used to determine the target planning line of the target node based on the comparison result of the total planning value and the preset conditions, and the preset conditions include the node upper limit condition and the node minimum planning line condition.

[0068] In one embodiment, the information acquisition unit 100 includes a minimum planning line acquisition subunit 101, which is used to obtain the target node bottom line, the target node billing line, and the target node upper limit for any target node; select the larger value of the target node bottom line and the target node billing line as the first comparison result; select the smaller value of the first comparison result and the target node upper limit as the second comparison result; and determine the second comparison result as the minimum planning line of the target node.

[0069] In one embodiment, the first planning unit 200 is specifically used to determine the first coefficient based on the sum of the upper limits of the target nodes, the stress test bandwidth discount coefficient, the number of the preset time granularities per unit time, the monthly free time of the billing node, and the free time utilization ratio; determine the second coefficient based on the maximum value of the sum of the bandwidth peak values; and determine the bandwidth over-planning points based on the ratio of the first coefficient to the second coefficient.

[0070] In one embodiment, the second planning unit 300 is specifically used to sort the bandwidth peak sums in descending order according to numerical values; for the sorted bandwidth peak sums, the bandwidth peak sums at the positions corresponding to the bandwidth exceeding planning points are selected as the sum of the planned values.

[0071] In one embodiment, the third planning unit 400 includes a first judging subunit 401. The first judging subunit 401 is configured to determine the upper limit of the target node as the target planning line of the target node when the sum of the planning values ​​is greater than the sum of the upper limits of the target nodes.

[0072] In one embodiment, the third planning unit 400 includes a second judgment subunit 402. The second judgment subunit 402 is used to determine the lowest planning line of the target node as the target planning line of the target node when the sum of the planning values ​​is not greater than the sum of the upper limits of the target node and the sum of the planning values ​​is less than the sum of the lowest planning lines of the target node.

[0073] In one embodiment, the third planning unit 400 includes a third judgment subunit 403. The third judgment subunit 403 is used to determine the planning value to be allocated based on the sum of the planning values ​​and the sum of the lowest planning lines of the target nodes when the sum of the planning values ​​is not greater than the sum of the upper limits of the target nodes and the sum of the lowest planning lines of the target nodes, and determine the target planning line of the target node based on the planning value to be allocated.

[0074] In one embodiment, the third judgment subunit 403 is specifically used to sort the target nodes in ascending order according to the node bandwidth price; for the first node of the sorted target nodes, calculate the sum of the planning value to be allocated and the lowest planning line of the first node; compare the sum with the upper limit of the first node; determine the first planning line of the first node according to the comparison result; deduct the first node difference from the planning value to be allocated, and update the planning value to be allocated, wherein the first node difference is determined by the upper limit of the first node and the lowest planning line of the first node; iteratively process the next node of the first node until the planning value to be allocated is zero.

[0075] In one embodiment, determining the first-place planning line of the first node based on the comparison result includes: if the added value is greater than or equal to the first-place node upper limit, determining the first-place node upper limit as the first-place planning line of the first node; if the added value is less than the first-place node upper limit, determining the added value as the first-place planning line of the first node.

[0076] Each unit described in the above embodiments may be implemented by a computer chip or a product having a certain function. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0077] For the convenience of description, the above devices are described in terms of functions and are described separately in various units. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0078] See also Figure 4 The present disclosure also provides an electronic device, which includes a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the above-mentioned node resource planning method is implemented.

[0079] The present disclosure also provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the above-mentioned node resource planning method is implemented.

[0080] The processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0081] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory, that is, implementing the method in the above method embodiment.

[0082] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0083] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0084] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0085] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

[0086] Although the embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A node resource planning method, characterized in that: The method comprises: Acquire historical reference information of a target region including multiple target nodes, the historical reference information including the sum of target node upper limits of each target node, the sum of target node lowest planning lines of each target node, and the bandwidth peak sum of the target nodes located in the user area, the bandwidth peak sum is a data group divided according to a preset time granularity, and the target node lowest planning line is determined based on the target node guarantee line, the target node billing line, and the target node upper limit; Determine the number of bandwidth over-planning points based on the sum of the upper limits of the target nodes and the sum of the bandwidth peaks; According to the number of bandwidth over-planning points, determine the total planned value of the target area from the bandwidth peak value sum; Based on the comparison result of the sum of the planning values ​​and the preset conditions, the target planning line of the target node is determined, and the preset conditions include a node upper limit condition and a node minimum planning line condition.

2. The method according to claim 1, characterized in that The target node minimum planning line is determined based on the target node guarantee line, the target node charging line and the target node upper limit, including: For any of the target nodes, obtain the target node guarantee line, the target node billing line, and the target node upper limit; Selecting a larger value between the target node guarantee line and the target node charging line as the first comparison result; Selecting the smaller value between the first comparison result and the upper limit of the target node as the second comparison result; The second comparison result is determined as the lowest planning line of the target node.

3. The method according to claim 1 or 2, characterized in that: The determining the number of bandwidth over-planning points based on the sum of the upper limits of the target nodes and the sum of the bandwidth peaks includes: Determine the first coefficient based on the sum of the upper limits of the target nodes, the stress test bandwidth discount coefficient, the number of the preset time granularities per unit time, the monthly free time of the billing node, and the free time utilization ratio; Determining a second coefficient based on the maximum value of the bandwidth peak sum; The number of bandwidth excess planning points is determined based on a ratio of the first coefficient to the second coefficient.

4. The method according to claim 1 or 2, characterized in that: The step of determining the total planned value of the target region from the bandwidth peak value sum according to the bandwidth exceeding planning points includes: According to the magnitude of the values, the bandwidth peak sums are sorted in descending order; For the sorted bandwidth peak sums, the bandwidth peak sums at positions corresponding to the bandwidth exceeding planning points are selected as the planned value sums.

5. The method according to claim 1 or 2, characterized in that: The determining of the target planning line of the target node based on the comparison result of the sum of the planning values ​​and the preset condition comprises at least one of the following: When the sum of the planning values ​​is greater than the sum of the upper limits of the target node, the upper limit of the target node is determined as the target planning line of the target node; When the sum of the planning values ​​is not greater than the sum of the upper limits of the target node, and the sum of the planning values ​​is less than the sum of the lowest planning lines of the target node, the lowest planning line of the target node is determined as the target planning line of the target node; When the sum of the planning values ​​is not greater than the sum of the upper limits of the target nodes, and the sum of the planning values ​​is not less than the sum of the lowest planning lines of the target nodes, the planning value to be allocated is determined based on the sum of the planning values ​​and the sum of the lowest planning lines of the target nodes, and the target planning line of the target node is determined based on the planning value to be allocated.

6. The method according to claim 5, characterized in that The step of determining the target planning line of the target node based on the to-be-allocated planning value comprises: According to the node bandwidth price, the target nodes are sorted in ascending order; For the first node of the sorted target node, calculate the sum of the to-be-allocated planning value and the lowest planning line of the first node; Compare the added value with the upper limit of the first node; Determining the first planning line of the first node according to the comparison result; Subtract the difference value of the first node from the planning value to be allocated, and update the planning value to be allocated, wherein the difference value of the first node is determined by the upper limit of the first node and the lowest planning line of the first node; Iteratively process the next node of the first node until the to-be-allocated planning value is zero.

7. The method according to claim 6, characterized in that Determining the first planning line of the first node according to the comparison result includes: If the added value is greater than or equal to the upper limit of the first node, the upper limit of the first node is determined as the first planning line of the first node; If the added value is less than the upper limit of the first node, the added value is determined as the first planning line of the first node.

8. A node resource planning device, characterized in that: The device comprises: An information acquisition unit, used to acquire historical reference information of a target region including a plurality of target nodes, the historical reference information including the sum of target node upper limits of each of the target nodes, the sum of target node lowest planning lines of each of the target nodes, and the bandwidth peak sum of the target nodes located in the user area, the bandwidth peak sum being a data group divided according to a preset time granularity, and the target node lowest planning line being determined based on the target node guarantee line, the target node charging line, and the target node upper limit; A first planning unit, configured to determine a number of bandwidth over-planning points based on a sum of the upper limits of the target nodes and a sum of the bandwidth peak values; A second planning unit is used to determine the total planning value of the target large area from the bandwidth peak value sum according to the bandwidth over-planning points; The third planning unit is used to determine the target planning line of the target node based on the comparison result of the total planning value and the preset conditions, and the preset conditions include the node upper limit condition and the node minimum planning line condition.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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