CN115842784B - Multi-node adjustment method for ultra-large data volume transmission - Google Patents
Multi-node adjustment method for ultra-large data volume transmission Download PDFInfo
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Abstract
The invention relates to the field of data exchange, in particular to a multi-node adjustment method for ultra-large data volume transmission, which comprises the following steps: s1, classifying by using a data exchange node to obtain a data exchange dynamic classification base node; s2, performing differentiation processing based on real-time data exchange quantity according to the data exchange dynamic classification base node to obtain a data exchange dynamic classification node; s3, data exchange processing is carried out by utilizing the data exchange dynamic classification nodes, the real-time data volume change corresponding to the adjustment node types is met, meanwhile, redundant nodes are set, multi-node shunting is carried out on suddenly increased data streams, the node processing mode is iterated in the adjustment process, the method can be applied to the conditions of node increase or node decrease and the like, a solution method is provided for transmission exchange of large data volume, the application range is wide, and good practicability is achieved.
Description
Technical Field
The invention relates to the field of data exchange, in particular to a multi-node adjustment method for ultra-large data volume transmission.
Background
In multi-node data transmission, nodes are not classified clearly, or nodes are jammed caused by oversized data flow, and the oversized data volume is defined as data of hundred thousand lines or more or data of hundred GB level or even more, meanwhile, due to the difference of characteristics such as data content and the like, large data volume is often generated to squeeze small number of nodes under the condition of fixed nodes, and the small data volume nodes cannot be adjusted in real time to relieve the data transmission jam, so a feasible node dynamic adjustment method is needed to meet the real-time changing oversized data volume transmission method.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a multi-node adjustment method for ultra-large data volume transmission, which adjusts the data transmission speed by classifying and adjusting multiple nodes according to the real-time data volume, thereby relieving node blockage when the ultra-large data volume is generated.
In order to achieve the above object, the present invention provides a multi-node adjustment method for ultra-large data volume transmission, comprising:
s1, classifying by using a data exchange node to obtain a data exchange dynamic classification base node;
s2, performing differentiation processing based on real-time data exchange quantity according to the data exchange dynamic classification base node to obtain a data exchange dynamic classification node;
and S3, carrying out data exchange processing by utilizing the data exchange dynamic classification node.
Preferably, the classifying processing by the data exchange node to obtain a data exchange dynamic classification base node includes:
calculating the average value of the data exchange quantity of each data exchange node at the last moment by using the data exchange quantity of the data exchange node as a dynamic classification basic threshold;
judging whether the data exchange amount of the data exchange node is larger than a dynamic classification basic threshold value, if so, using the data exchange node as a high-flow node, otherwise, using the data exchange node as a low-flow node;
and acquiring the data exchange dynamic classification base node by using the high-flow node and the low-flow node.
Further, the obtaining the data exchange dynamic classification base node by using the high traffic node and the low traffic node includes:
calculating the change rate of the high-flow node by utilizing the real-time data flow of the high-flow node and the data flow of the adjacent last moment;
calculating the change rate of the low-flow node by using the real-time data flow of the low-flow node and the data flow of the adjacent last moment;
obtaining a data exchange dynamic classification high-flow basic node according to the high-flow node change rate by utilizing the high-flow node;
obtaining a data exchange dynamic classification low-flow basic node according to the low-flow node change rate by using the low-flow node;
and using the data exchange dynamic classification high-flow base node and the data exchange dynamic classification low-flow base node as the data exchange dynamic classification base nodes.
Further, the calculation formula for calculating the change rate of the high-flow node by using the real-time data flow of the high-flow node and the data flow at the last time is as follows:
wherein m is the change rate of the high-flow node, and x 1 And x is the real-time data traffic of the high-traffic node.
Further, the calculation formula for calculating the change rate of the low-traffic node by using the real-time data traffic of the low-traffic node and the data traffic of the adjacent last time is as follows:
wherein n is the low flow node change rate, y 1 And y is the real-time data traffic of the low-traffic node.
Further, the obtaining the data exchange dynamic classification high-traffic base node by the high-traffic node according to the high-traffic node change rate includes:
when the high-flow node change rate of the high-flow node is a positive value, the high-flow node is used as a data exchange dynamic backup node;
when the high-flow node change rate of the high-flow node is not positive, the high-flow node is used as a data exchange high-flow base node;
using the data exchange dynamic backup node and the data exchange high-flow base node as data exchange dynamic classification high-flow base nodes;
wherein the data exchange dynamic backup node is not enabled by default.
Further, the obtaining the data exchange dynamic classification low-traffic base node by the low-traffic node according to the low-traffic node change rate includes:
when the low-flow node change rate of the low-flow node is a positive value, the low-flow node is used as a data exchange dynamic backup node;
when the change rate of the low-flow node is not positive, the low-flow node is used as a data exchange low-flow base node;
using the data exchange dynamic backup node and the data exchange low-flow base node as data exchange dynamic classification low-flow base nodes;
wherein the data exchange dynamic backup node is not enabled by default.
Preferably, the step of performing differentiation processing based on the real-time data exchange amount according to the data exchange dynamic classification base node to obtain the data exchange dynamic classification node includes:
when the fluctuation of the real-time data exchange quantity at the time t exceeds the fluctuation threshold at the current time, judging whether the real-time data exchange quantity at the time t+1 exceeds the fluctuation threshold at the time t, if so, performing differentiation processing according to the fluctuation threshold at the time t+2 to obtain a data exchange dynamic classification node, otherwise, starting a single data exchange dynamic backup node, a data exchange high-flow base node and a data exchange low-flow base node as the data exchange dynamic classification nodes;
when the fluctuation of the real-time data exchange quantity at the time t does not exceed the fluctuation threshold value at the current time, keeping the dual-data exchange dynamic backup node not started;
the fluctuation is the difference between the real-time data exchange amount at the current moment and the real-time data exchange amount at the last moment, and the fluctuation threshold value is 10% of the real-time data exchange amount.
Further, the differentiating processing according to the fluctuation threshold at the time t+2 to obtain the data exchange dynamic classification node includes:
when the fluctuation threshold value at the time t+2 exceeds the fluctuation threshold value at the time t, simultaneously starting the double-data exchange dynamic backup node to obtain a data exchange dynamic classification node;
when the double-data exchange dynamic backup node is started, judging whether the real-time data exchange quantity at the time t+3 exceeds the fluctuation threshold at the time t+3, if so, returning to S1, otherwise, adjusting the double-data exchange dynamic backup node to obtain the data exchange dynamic classification node.
Further, the step of adjusting the dual data exchange dynamic backup node to obtain the data exchange dynamic classification node includes:
when the fluctuation of the real-time data exchange quantity at the time t+3 is larger than the fluctuation threshold at the time t and smaller than the fluctuation threshold at the time t+3, the dual-data exchange dynamic backup nodes are all adjusted to be data exchange dynamic classification high-flow basic nodes and serve as data exchange dynamic classification nodes;
and when the fluctuation of the real-time data exchange quantity at the time t+3 is smaller than the fluctuation threshold value at the time t, disabling the double-data exchange dynamic backup node in the data exchange dynamic classification node.
Compared with the closest prior art, the invention has the following beneficial effects:
the method has the advantages that the nodes can be classified according to the data quantity in real time, the real-time data quantity change is met, the node types are correspondingly adjusted, meanwhile, redundant nodes are arranged, multi-node shunting is carried out on suddenly increased data streams, the node processing mode is iterated in the adjustment process, the method can be applied to the conditions of node increase or node decrease, a solution method is provided for transmission and exchange of large data quantity, the application range is wide, and the method has good practicability.
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FIG. 1 is a flow chart of a multi-node adjustment method for ultra-large data volume transmission provided by the present invention.
Detailed Description
The following describes the embodiments of the present invention in further detail with reference to the drawings.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1: the invention provides a multi-node adjustment method for ultra-large data volume transmission, as shown in fig. 1, comprising the following steps:
s1, classifying by using a data exchange node to obtain a data exchange dynamic classification base node;
s2, performing differentiation processing based on real-time data exchange quantity according to the data exchange dynamic classification base node to obtain a data exchange dynamic classification node;
and S3, carrying out data exchange processing by utilizing the data exchange dynamic classification node.
S1 specifically comprises:
s1-1, calculating an average value of data exchange amounts of all data exchange nodes at the last moment by using the data exchange amounts of the data exchange nodes as a dynamic classification basic threshold;
s1-2, judging whether the data exchange amount of the data exchange node is larger than a dynamic classification basic threshold value, if so, using the data exchange node as a high-flow node, otherwise, using the data exchange node as a low-flow node;
s1-3, acquiring a data exchange dynamic classification base node by utilizing the high-flow node and the low-flow node.
S1-3 specifically comprises:
s1-3-1, calculating the change rate of the high-flow node by utilizing the real-time data flow of the high-flow node and the data flow of the adjacent last moment;
s1-3-2, calculating the change rate of the low-flow node by using the real-time data flow of the low-flow node and the data flow of the adjacent last moment;
s1-3-3, obtaining a data exchange dynamic classification high-flow base node by utilizing the high-flow node according to the high-flow node change rate;
s1-3-4, obtaining a data exchange dynamic classification low-flow basic node by utilizing the low-flow node according to the low-flow node change rate;
s1-3-5, using the data exchange dynamic classification high-flow base node and the data exchange dynamic classification low-flow base node as the data exchange dynamic classification base nodes.
The calculation formula of S1-3-1 is as follows:
wherein m is the change rate of the high-flow node, and x 1 And x is the real-time data traffic of the high-traffic node.
The calculation formula of S1-3-2 is as follows:
wherein n is the low flow node change rate, y 1 And y is the real-time data traffic of the low-traffic node.
S1-3-3 specifically comprises:
s1-3-3-1, when the high-flow node change rate of the high-flow node is a positive value, using the high-flow node as a data exchange dynamic backup node;
s1-3-3-2, when the change rate of the high-flow node is not a positive value, using the high-flow node as a data exchange high-flow base node;
s1-3-3-3, using the data exchange dynamic backup node and the data exchange high-flow base node as data exchange dynamic classification high-flow base nodes;
wherein the data exchange dynamic backup node is not enabled by default.
S1-3-4 specifically comprises:
s1-3-4-1, when the change rate of the low-flow node is a positive value, using the low-flow node as a data exchange dynamic backup node;
s1-3-4-2, when the change rate of the low-flow node is not a positive value, using the low-flow node as a data exchange low-flow base node;
s1-3-4-3, using the data exchange dynamic backup node and the data exchange low-flow base node as data exchange dynamic classification low-flow base nodes;
wherein the data exchange dynamic backup node is not enabled by default.
S2 specifically comprises:
s2-1, judging whether the real-time data exchange quantity at the time t+1 exceeds the fluctuation threshold at the time t when the fluctuation of the real-time data exchange quantity at the time t exceeds the fluctuation threshold at the current time, if yes, performing differentiation processing according to the fluctuation threshold at the time t+2 to obtain a data exchange dynamic classification node, otherwise, starting a single data exchange dynamic backup node, a data exchange high-flow base node and a data exchange low-flow base node to serve as the data exchange dynamic classification node;
s2-2, when the fluctuation of the real-time data exchange quantity at the time t does not exceed the fluctuation threshold value at the current time, keeping the dual-data exchange dynamic backup node not started;
the fluctuation is the difference between the real-time data exchange amount at the current moment and the real-time data exchange amount at the last moment, and the fluctuation threshold value is 10% of the real-time data exchange amount.
S2-1 specifically comprises:
s2-1-1, when the fluctuation threshold value at the time t+2 exceeds the fluctuation threshold value at the time t, simultaneously starting the double-data exchange dynamic backup node to obtain a data exchange dynamic classification node;
s2-1-2, judging whether the real-time data exchange quantity at the time t+3 exceeds the fluctuation threshold at the time t+3 when the double-data exchange dynamic backup node is started, if so, returning to S1, otherwise, adjusting the double-data exchange dynamic backup node to obtain the data exchange dynamic classification node.
S2-1-2 specifically comprises:
s2-1-2-1, when the fluctuation of the real-time data exchange quantity at the time t+3 is larger than the fluctuation threshold value at the time t and smaller than the fluctuation threshold value at the time t+3, regulating the dual-data exchange dynamic backup nodes to serve as data exchange dynamic classification nodes, wherein the dual-data exchange dynamic classification high-flow basic nodes are used as data exchange dynamic classification nodes;
s2-1-2-2, and when the fluctuation of the real-time data exchange quantity at the time t+3 is smaller than the fluctuation threshold value at the time t, disabling the double-data exchange dynamic backup node in the data exchange dynamic classification node.
In this embodiment, since the data exchange dynamic backup nodes corresponding to the high traffic and the low traffic are the same, when a single data exchange dynamic backup node is started, one data exchange dynamic backup node can be started at will, and similarly, when the dual data exchange dynamic classification node is started, two data exchange dynamic classification nodes are started at the same time.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (7)
1. A multi-node adjustment method for transmission of an ultra-large amount of data, comprising:
s1, classifying by using a data exchange node to obtain a data exchange dynamic classification base node;
s2, performing differentiation processing based on real-time data exchange quantity according to the data exchange dynamic classification base node to obtain a data exchange dynamic classification node;
s3, carrying out data exchange processing by utilizing the data exchange dynamic classification node;
s2 specifically comprises:
s2-1, judging whether the real-time data exchange quantity at the time t+1 exceeds the fluctuation threshold at the time t when the fluctuation of the real-time data exchange quantity at the time t exceeds the fluctuation threshold at the current time, if yes, performing differentiation processing according to the fluctuation threshold at the time t+2 to obtain a data exchange dynamic classification node, otherwise, starting a single data exchange dynamic backup node, a data exchange high-flow base node and a data exchange low-flow base node to serve as the data exchange dynamic classification node;
s2-2, when the fluctuation of the real-time data exchange quantity at the time t does not exceed the fluctuation threshold value at the current time, keeping the dual-data exchange dynamic backup node not started;
the fluctuation of the real-time data exchange amount at the time t is the difference value between the real-time data exchange amount at the current time and the real-time data exchange amount at the last time adjacent to the current time, and the fluctuation threshold value is 10% of the real-time data exchange amount;
the step of performing differentiation processing according to the fluctuation threshold value at the time t+2 to obtain the data exchange dynamic classification node comprises the following steps:
s2-1-1, when the fluctuation threshold value at the time t+2 exceeds the fluctuation threshold value at the time t, simultaneously starting the double-data exchange dynamic backup node to obtain a data exchange dynamic classification node;
s2-1-2, judging whether the real-time data exchange quantity at the time t+3 exceeds the fluctuation threshold at the time t+3 when the double-data exchange dynamic backup node is started, if so, returning to S1, otherwise, adjusting the double-data exchange dynamic backup node to obtain a data exchange dynamic classification node;
the step of adjusting the dual data exchange dynamic backup node to obtain the data exchange dynamic classification node comprises the following steps:
s2-1-3, when the fluctuation of the real-time data exchange quantity at the time t+3 is larger than the fluctuation threshold at the time t and smaller than the fluctuation threshold at the time t+3, regulating the dual-data exchange dynamic backup nodes to serve as data exchange dynamic classification nodes, wherein the dual-data exchange dynamic classification high-flow basic nodes are used as data exchange dynamic classification nodes;
s2-1-4, when the fluctuation of the real-time data exchange quantity at the time t+3 is smaller than the fluctuation threshold value at the time t, disabling the double-data exchange dynamic backup node in the data exchange dynamic classification node.
2. The multi-node adjustment method for ultra-large data volume transmission according to claim 1, wherein the classifying by the data switching node to obtain the data switching dynamic classification base node comprises:
calculating the average value of the data exchange quantity of each data exchange node at the last moment by using the data exchange quantity of the data exchange node as a dynamic classification basic threshold;
judging whether the data exchange amount of the data exchange node is larger than a dynamic classification basic threshold value, if so, using the data exchange node as a high-flow node, otherwise, using the data exchange node as a low-flow node;
and acquiring the data exchange dynamic classification base node by using the high-flow node and the low-flow node.
3. The multi-node adjustment method for ultra-large data volume transmission according to claim 2, wherein obtaining the data exchange dynamic classification base node by using the high-traffic node and the low-traffic node comprises:
calculating the change rate of the high-flow node by utilizing the real-time data flow of the high-flow node and the data flow of the adjacent last moment;
calculating the change rate of the low-flow node by using the real-time data flow of the low-flow node and the data flow of the adjacent last moment;
obtaining a data exchange dynamic classification high-flow basic node according to the high-flow node change rate by utilizing the high-flow node;
obtaining a data exchange dynamic classification low-flow basic node according to the low-flow node change rate by using the low-flow node;
and using the data exchange dynamic classification high-flow base node and the data exchange dynamic classification low-flow base node as the data exchange dynamic classification base nodes.
4. A multi-node adjustment method for ultra-large data volume transmission according to claim 3, wherein the calculation formula for calculating the rate of change of the high-traffic node using the real-time data traffic of the high-traffic node and the data traffic at the immediately preceding time is as follows:
wherein m is the change rate of the high-flow node, and x 1 And x is the real-time data traffic of the high-traffic node.
5. A multi-node adjustment method for ultra-large data volume transmission according to claim 3, wherein the calculation formula for calculating the rate of change of the low-traffic node using the real-time data traffic of the low-traffic node and the data traffic at the immediately preceding time is as follows:
wherein n is the low flow node change rate, y 1 And y is the real-time data traffic of the low-traffic node.
6. A multi-node adjustment method for ultra-large data volume transmission as recited in claim 3 wherein utilizing said high-traffic node to obtain a data exchange dynamic classification high-traffic base node according to said high-traffic node change rate comprises:
when the high-flow node change rate of the high-flow node is a positive value, the high-flow node is used as a data exchange dynamic backup node;
when the high-flow node change rate of the high-flow node is not positive, the high-flow node is used as a data exchange high-flow base node;
using the data exchange dynamic backup node and the data exchange high-flow base node as data exchange dynamic classification high-flow base nodes;
wherein the data exchange dynamic backup node is not enabled by default.
7. A multi-node adjustment method for ultra-large data volume transmission as recited in claim 3 wherein utilizing said low-traffic node to obtain a data exchange dynamic classification low-traffic base node from said low-traffic node change rate comprises:
when the low-flow node change rate of the low-flow node is a positive value, the low-flow node is used as a data exchange dynamic backup node;
when the change rate of the low-flow node is not positive, the low-flow node is used as a data exchange low-flow base node;
using the data exchange dynamic backup node and the data exchange low-flow base node as data exchange dynamic classification low-flow base nodes;
wherein the data exchange dynamic backup node is not enabled by default.
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| CN113038511B (en) * | 2021-03-12 | 2022-12-13 | 广东博智林机器人有限公司 | Control method and control device of communication system and communication system |
| CN113114517B (en) * | 2021-05-26 | 2022-07-01 | 广东电网有限责任公司电力调度控制中心 | Network resource dynamic backup method and system based on node characteristics under network slice |
| CN115225577B (en) * | 2022-09-20 | 2022-12-27 | 深圳市明源云科技有限公司 | Data processing control method and device, electronic equipment and readable storage medium |
| CN115695435A (en) * | 2022-10-26 | 2023-02-03 | 吉林亿联银行股份有限公司 | Method and device for dynamically adjusting node flow, electronic equipment and storage medium |
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| WO2019237797A1 (en) * | 2018-06-15 | 2019-12-19 | 华为技术有限公司 | Data backup method and apparatus |
| US11463367B1 (en) * | 2021-04-16 | 2022-10-04 | Versa Networks, Inc. | Methods and system for adaptively managing the distribution of network traffic |
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