CN112787948B - Traffic load balancing method and related device - Google Patents
Traffic load balancing method and related device Download PDFInfo
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- CN112787948B CN112787948B CN202011622367.9A CN202011622367A CN112787948B CN 112787948 B CN112787948 B CN 112787948B CN 202011622367 A CN202011622367 A CN 202011622367A CN 112787948 B CN112787948 B CN 112787948B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/12—Avoiding congestion; Recovering from congestion
- H04L47/125—Avoiding congestion; Recovering from congestion by balancing the load, e.g. traffic engineering
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5083—Techniques for rebalancing the load in a distributed system
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/50—Reducing energy consumption in communication networks in wire-line communication networks, e.g. low power modes or reduced link rate
Abstract
The application discloses a traffic load balancing method, which comprises the following steps: the routing gateway distributes routing weights to each node according to the preset total weights; load balancing is carried out according to the routing weight; when the throughput performance of the node is increased, updating the routing weights of all the nodes according to a preset value to obtain new routing weights, wherein the sum of all the new routing weights is the total weight; and carrying out load balancing according to the new routing weight. By configuring the routing weight for each node and updating the routing weight according to the throughput performance of the node, the effect of dynamically adjusting the load balance according to the throughput performance of the node and improving the load balance is realized. The application also discloses a traffic load balancing device, a computing device and a computer readable storage medium, which have the beneficial effects.
Description
Technical Field
The present disclosure relates to the field of network technologies, and in particular, to a traffic load balancing method, a traffic load balancing device, a computing device, and a computer readable storage medium.
Background
Load balancing, which means that loads (work tasks) are balanced and distributed to a plurality of operation units to run, such as FTP (File Transfer Protocol ) servers, web servers, enterprise core application servers, other main task servers, and the like, so as to cooperatively complete the work tasks. The load balancing is built on the original network structure, and the method is transparent, low in cost and effective, and can expand the bandwidth of the server and the network equipment, strengthen the data processing capacity of the network, increase the throughput and improve the usability and flexibility of the network. Where nmginx is commonly used as a load balancing service.
In the prior art, the client flow balance needs fixed configuration and cannot be automatically changed according to the change of the back-end service capacity. Without manual intervention, the overall throughput cannot be improved. Taking the balance policy of the nginix agent as an example, the nginix balance policy has 6 kinds of methods, namely polling, weighting, a minimum connection mode according to an ip allocation mode, a response time mode and an allocation mode according to a URL (Uniform Resource Locator ), which are all statically configured. The manner of traffic distribution is fixed with the number and configuration of backend services unchanged. If the processing capacity of the back-end service is changed, the traffic routing mode of the back-end service can generate an imbalance problem, the response cannot be changed dynamically, the effect of load balancing is reduced, and the load of the node is increased under the dynamic change of the traffic.
Therefore, how to make the load balancing process dynamically changeable according to the node situation is a major concern for those skilled in the art.
Disclosure of Invention
The purpose of the application is to provide a traffic load balancing method, a traffic load balancing device, a computing device and a computer readable storage medium, wherein routing weights are configured for each node, the routing weights are updated according to the throughput performance of the node, and load balancing is performed through the updated routing weights, so that the load balancing is dynamically adjusted, and the effect of load balancing is improved.
In order to solve the above technical problems, the present application provides a traffic load balancing method, including:
the routing gateway distributes routing weights to each node according to the preset total weights;
load balancing is carried out according to the routing weight;
when the throughput performance of the node is increased, updating the routing weights of all the nodes according to a preset value to obtain new routing weights, wherein the sum of all the new routing weights is the total weight;
and carrying out load balancing according to the new routing weight.
Optionally, when the throughput performance of the node increases, updating the routing weights of all the nodes according to a preset value to obtain new routing weights, where the sum of all the new routing weights is the total weight, including:
when the throughput performance of the node is increased, the preset value is increased to the routing weight of the node, so that a corresponding new routing weight is obtained;
subtracting the preset value from the total routing weight of one or more nodes in the other nodes to obtain a corresponding new routing weight, so that the sum of the routing weights of all the nodes is the total weight.
Optionally, the step of determining that the throughput performance of the node is increased includes:
s1, increasing the preset value for the routing weight of the node and subtracting the preset value for the weight routing of another node when the load balancing operates for a time period;
s2, judging whether the throughput of the node is increased or not; if yes, executing S3; if not, executing S4;
s3, judging that the throughput performance of the node is increased;
s4, selecting the next node to execute S1 until the routing weight of each node is kept unchanged after a plurality of time periods.
Optionally, the routing gateway allocates routing weights to each node according to a preset total weight, including:
constructing a routing gateway;
distributing default weight values to the routing weights of all nodes according to the preset total weight; wherein all default weight value additions are equal to the total weight.
Optionally, the step of performing load balancing according to the routing weight includes:
determining the processing request proportion of the corresponding node according to the routing weight of each node;
and distributing flow requests according to the corresponding nodes of the processing request proportion of each node.
The application also provides a traffic load balancing device, comprising:
the weight configuration module is used for distributing routing weights to all nodes according to the preset total weights by the routing gateway; load balancing is carried out according to the routing weight;
the weight dynamic adjustment module is used for updating the routing weights of all the nodes according to a preset value to obtain new routing weights when the throughput performance of the nodes is increased, and the sum of all the new routing weights is the total weight;
and the load balancing adjustment module is used for carrying out load balancing according to the new routing weight.
Optionally, the weight dynamic adjustment module includes:
a weight increasing unit, configured to increase the routing weight of the node by the preset value when the throughput performance of the node increases, so as to obtain a corresponding new routing weight;
and the weight reduction unit is used for subtracting the preset value from the total routing weight of one or more nodes in the other nodes to obtain a corresponding new routing weight, so that the sum of the routing weights of all the nodes is the total weight.
Optionally, the method further comprises:
the performance judging module is used for executing the following steps:
s1, increasing the preset value for the routing weight of the node and subtracting the preset value for the weight routing of another node when the load balancing operates for a time period;
s2, judging whether the throughput of the node is increased or not; if yes, executing S3; if not, executing S4;
s3, judging that the throughput performance of the node is increased;
s4, selecting the next node to execute S1 until the routing weight of each node is kept unchanged after a plurality of time periods.
The present application also provides a computing device comprising:
a memory for storing a computer program;
and a processor for implementing the steps of the traffic load balancing method as described above when executing the computer program.
The present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the traffic load balancing method as described above.
The traffic load balancing method provided by the application comprises the following steps: the routing gateway distributes routing weights to each node according to the preset total weights; load balancing is carried out according to the routing weight; when the throughput performance of the node is increased, updating the routing weights of all the nodes according to a preset value to obtain new routing weights, wherein the sum of all the new routing weights is the total weight; and carrying out load balancing according to the new routing weight.
The routing weight is configured for each node, the routing weight is updated according to the throughput performance of the node, and load balancing is carried out through the updated routing weight, so that the load balancing is dynamically adjusted, and the load balancing effect is improved.
The application further provides a traffic load balancing device, a computing device and a computer readable storage medium, which have the above beneficial effects and are not described herein.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings may be obtained according to the provided drawings without inventive effort to a person skilled in the art.
Fig. 1 is a flowchart of a traffic load balancing method provided in an embodiment of the present application;
fig. 2 is a schematic diagram of a flow load balancing method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a traffic load balancing device according to an embodiment of the present application.
Detailed Description
The core of the application is to provide a traffic load balancing method, a traffic load balancing device, a computing device and a computer readable storage medium, wherein the routing weight is configured for each node, the routing weight is updated according to the throughput performance of the node, and the load balancing is performed through the updated routing weight, so that the load balancing is dynamically adjusted, and the effect of the load balancing is improved.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
In the prior art, the client flow balance needs fixed configuration and cannot be automatically changed according to the change of the back-end service capacity. Without manual intervention, the overall throughput cannot be improved. Taking the equilibrium policy of the ng ix agent as an example, the n ginx equilibrium policies are 6, namely polling, weighting, according to the ip allocation mode, the minimum connection mode, the response time mode and according to the URL allocation mode, which are all statically configured. The manner of traffic distribution is fixed with the number and configuration of backend services unchanged. If the processing capacity of the back-end service is changed, the traffic routing mode of the back-end service can generate an imbalance problem, the response cannot be changed dynamically, the effect of load balancing is reduced, and the load of the node is increased under the dynamic change of the traffic.
Therefore, the traffic load balancing method is provided, by configuring the routing weight for each node, updating the routing weight according to the throughput performance of the node, and then carrying out load balancing through the updated routing weight, so as to dynamically adjust the load balancing and improve the load balancing effect.
The following describes, by way of an embodiment, a traffic load balancing method provided in the present application.
Referring to fig. 1, fig. 1 is a flowchart of a traffic load balancing method according to an embodiment of the present application.
In this embodiment, the method may include:
s101, a routing gateway distributes routing weights to all nodes according to preset total weights;
s102, load balancing is carried out according to the routing weight;
the method aims at distributing routing weights to all nodes according to preset total weights by a routing gateway and starting load balancing.
The routing gateway is a gateway with a routing function. The gateway is also called an intersystem connector and a protocol converter. The gateway realizes network interconnection above the network layer, is a complex network interconnection device, and is only used for network interconnection with two different higher-layer protocols. The gateway may be used for both wide area network and local area network interconnections. A gateway is a computer system or device that acts as a translation rendition. The gateway is a translator for use between two systems of different communication protocols, data formats or languages, even with disparate architectures. Rather than simply conveying the information, the gateway repacks the received information to accommodate the needs of the destination system.
Wherein the total weight is a fixed value that is constant, and the total weight is assigned to each node. The weight value addition of the routing weights of all nodes is equal to the total weight. Further, in the process of load balancing, in order to maintain the stability of load balancing, the addition of the weight values of the routing weights of all the nodes needs to be kept always equal to the total weight.
Further, the step may include:
step 1, constructing a routing gateway;
step 2, distributing default weight values to the routing weights of all the nodes according to preset total weights; wherein all default weight values add to equal the total weight.
It can be seen that this alternative is mainly illustrative of the configuration process. In the alternative scheme, a routing gateway is firstly constructed; then, a default weight value is set for the routing weight of each node according to the preset total weight.
Further, the step of load balancing according to the routing weight may include:
determining the processing request proportion of the corresponding node according to the routing weight of each node; and distributing the flow requests to the corresponding nodes according to the processing request proportion of each node.
S103, when the throughput performance of the node is increased, updating the routing weights of all the nodes according to a preset value to obtain new routing weights, wherein the sum of all the new routing weights is the total weight;
on the basis of S102, this step aims at updating the routing weights of all nodes according to a preset value to obtain new routing weights when the throughput performance of the nodes increases, and the sum of all the new routing weights is the total weight.
Therefore, the step is mainly to modify the weight of each node when the performance of the node changes, so that dynamic adjustment can be performed when the performance changes, and dynamic load balancing is realized.
Further, the step may include:
step 1, when the throughput performance of a node is increased, a preset value is added to the routing weight of the node to obtain a corresponding new routing weight;
and 2, subtracting a preset value from the total routing weight of one or more nodes in other nodes to obtain a corresponding new routing weight, wherein the sum of all the new routing weights is the total weight.
It can be seen that this alternative is mainly to illustrate how the weight update is performed. In the alternative scheme, when the throughput performance of the node is increased, a preset value is added to the routing weight of the node to obtain a corresponding new routing weight, the preset value is subtracted from the total routing weight of one or more nodes in other nodes to obtain a corresponding new routing weight, and the sum of all the new routing weights is the total weight. The number of the nodes for reducing the routing weight may be one or more. When a plurality of nodes, subtracting the preset value from the total routing weight of the plurality of nodes, wherein the routing weight of each node is subtracted by a corresponding value.
Further, the method for determining whether the throughput performance of any node is increased in this embodiment may include:
s1, when load balancing operates for a time period, adding a preset value to the routing weight of a node, and subtracting the preset value from the weight routing of another node;
s2, judging whether the throughput of the node is increased; if yes, executing S3; if not, executing S4;
s3, judging that the throughput performance of the node is increased;
s4, selecting the next node to execute S1 until the routing weight of each node is kept unchanged after a plurality of time periods.
Therefore, in the alternative scheme, whether the throughput performance of any node is increased is tested in a continuous circulation mode, and the routing weight of each node is kept unchanged after a plurality of time periods, so that the fluctuation of the whole network is avoided.
S104, load balancing is carried out according to the new routing weight.
On the basis of S103, this step aims at load balancing according to the new routing weights. That is, corresponding load balancing is performed according to the adoption of the new routing weight so as to dynamically adjust the throughput performance.
Further, the step may include:
determining the processing request proportion of the corresponding node according to the routing weight of each node; and distributing the flow requests to the corresponding nodes according to the processing request proportion of each node.
It can be seen that the traffic requests allocated to each node can be adjusted by the new routing weights through the present alternative.
In summary, in this embodiment, by configuring a routing weight for each node, updating the routing weight according to the throughput performance of the node, and performing load balancing by using the updated routing weight, dynamic adjustment is performed on load balancing, so as to improve the effect of load balancing.
The flow load balancing method provided by the application is further described below through a specific embodiment.
In this embodiment, the method may include:
weight-based request routing mechanism: and setting the total flow of the system, namely the total weight as 1, and each back-end service. The routing weight of each node is a fraction between 0 and 1, which means that the node is processing the proportional relation between the request and the total request, and the sum of the weights of all nodes is 1, which is the total flow currently processed by the system. The scheduler routes the new request to the node with high free coefficient, and the free coefficient is the ratio of the routing weight value to the current node processing flow. For example, if a routing weight is 0.3 and the proportion of the current processing request to the total request is 0.1, the spare factor is 0.2.
The self-adaptive process of the routing weight has a parameter when the system is initialized, and represents a modifiable weight value, for example, 0.05, and the weight of a pair of nodes is respectively added or subtracted by 0.05 every one clock period, and the weights of other nodes are kept unchanged. So that the sum of the weights of all nodes remains 1. After the pairing operation of the weights is completed, the change of the total throughput of the system is monitored, and if the total throughput is improved compared with the last statistical period, the same weight change is continuously carried out on the pair of nodes. Until the throughput is no longer improved. If the throughput is not obviously increased or reduced, the back-off weight is changed, the next time slice rotates other paired nodes to change the weight, and the process is repeated. Wherein, the time slice refers to the period of calculating the weight.
Wherein the routing weights have the opportunity to change and are changing. The pair of changes and measurements make the weight change directly reflect the flow change and make it easy to measure the node. The frequency of the change of the weights is high, and even if there is an error and noise, the weight configuration moves toward a high throughput as a whole. The weight of a single node and the total weight of the system are balanced in one period, and large fluctuation is not easy to generate.
Referring to fig. 2, fig. 2 is a schematic diagram of a flow load balancing method according to an embodiment of the present application.
The method may include:
step 1, constructing a routing gateway and distributing default routing weight;
step 2, establishing and calculating real-time routing information of each node; the route information is the traffic request task quantity;
step 3, configuring the time slice length, and changing the routing weight by the balance matrix;
step 4, calculating the throughput in the time slice by the stream, and continuously modifying the same weight of the modified node when the throughput is increased; when the throughput is unchanged, the balance matrix is moved so as to modify other nodes, and the total weight is kept unchanged;
and 5, repeating the processes from the step 3 to the step 4.
Wherein the balancing matrix is used for keeping the routing weight of each node unchanged after a plurality of time slice lengths when the throughput is unchanged.
The method and the device realize real-time load state management of the service nodes, balance matrix rolling modifies the routing weight of each node, flow calculation is used for detecting throughput changes of the routing gateway and each node, and the routing weight is modified to the node with high throughput, so that the routing weight of the node is gradually increased.
Therefore, in this embodiment, the routing weight may be configured for each node, updated according to the throughput performance of the node, and then load balancing is performed by using the updated routing weight, so as to dynamically adjust the load balancing, and improve the effect of the load balancing.
The flow load balancing device provided in the embodiments of the present application is described below, and the flow load balancing device described below and the flow load balancing method described above may be referred to correspondingly.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a traffic load balancing device according to an embodiment of the present application.
In this embodiment, the apparatus may include:
the weight configuration module 100 is configured to allocate a routing weight to each node by the routing gateway according to a preset total weight; load balancing is carried out according to the routing weight;
the weight dynamic adjustment module 200 is configured to update route weights of all nodes according to a preset value to obtain new route weights when throughput performance of the nodes increases, and a sum of all the new route weights is a total weight;
the load balancing adjustment module 300 is configured to perform load balancing according to the new routing weight.
Optionally, the weight dynamic adjustment module 200 may include:
the weight increasing unit is used for increasing the routing weight of the node by a preset value when the throughput performance of the node is increased, so as to obtain a corresponding new routing weight;
the weight reduction unit is used for subtracting a preset value from the total routing weight of one or more nodes in other nodes to obtain a corresponding new routing weight, and the sum of all the new routing weights is the total weight.
Optionally, the apparatus may further include:
the performance judging module is used for executing the following steps:
s1, when load balancing operates for a time period, adding a preset value to the routing weight of a node, and subtracting the preset value from the weight routing of another node;
s2, judging whether the throughput of the node is increased; if yes, executing S3; if not, executing S4;
s3, judging that the throughput performance of the node is increased;
s4, selecting the next node to execute S1 until the routing weight of each node is kept unchanged after a plurality of time periods.
Optionally, the weight configuration module 100 may include:
a gateway construction unit for constructing a routing gateway;
the weight matching unit is used for distributing default weight values to the routing weights of all the nodes according to the preset total weight; wherein all default weight values add to equal the total weight.
Embodiments of the present application also provide a computing device, comprising:
a memory for storing a computer program;
and a processor, configured to implement the steps of the traffic load balancing method according to the above embodiment when executing the computer program.
The present application also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the traffic load balancing method according to the above embodiments.
In the description, each embodiment is described in a progressive manner, and each embodiment is mainly described by the differences from other embodiments, so that the same similar parts among the embodiments are mutually referred. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The flow load balancing method, the flow load balancing device, the computing device and the computer readable storage medium provided by the application are described in detail above. Specific examples are set forth herein to illustrate the principles and embodiments of the present application, and the description of the examples above is only intended to assist in understanding the methods of the present application and their core ideas. It should be noted that it would be obvious to those skilled in the art that various improvements and modifications can be made to the present application without departing from the principles of the present application, and such improvements and modifications fall within the scope of the claims of the present application.
Claims (6)
1. A traffic load balancing method, comprising:
the routing gateway distributes routing weights to each node according to the preset total weights;
load balancing is carried out according to the routing weight;
when the throughput performance of the node is increased, updating the routing weights of all the nodes according to a preset value to obtain new routing weights, wherein the sum of all the new routing weights is the total weight; a step of determining an increase in throughput performance of a node, comprising: s1, increasing the preset value for the routing weight of the node and subtracting the preset value for the weight routing of another node when the load balancing operates for a time period; s2, judging whether the throughput of the node is increased or not; if yes, executing S3; if not, executing S4; s3, judging that the throughput performance of the node is increased; s4, selecting the next node to execute S1 until the routing weight of each node is kept unchanged after a plurality of time periods;
load balancing is carried out according to the new routing weight;
when the throughput performance of the node is increased, updating the routing weights of all the nodes according to a preset value to obtain new routing weights, wherein the sum of all the new routing weights is the total weight, and the method comprises the following steps:
when the throughput performance of the node is increased, the preset value is increased to the routing weight of the node, so that a corresponding new routing weight is obtained;
subtracting the preset value from the total routing weight of one or more nodes in other nodes to obtain a corresponding new routing weight, so that the sum of the routing weights of all the nodes is the total weight.
2. The traffic load balancing method according to claim 1, wherein the routing gateway assigns routing weights to the nodes according to a preset total weight, comprising:
constructing a routing gateway;
distributing default weight values to the routing weights of all nodes according to the preset total weight; wherein all default weight value additions are equal to the total weight.
3. The traffic load balancing method according to claim 1, wherein the step of load balancing according to the routing weight comprises:
determining the processing request proportion of the corresponding node according to the routing weight of each node;
and distributing flow requests according to the corresponding nodes of the processing request proportion of each node.
4. A traffic load balancing apparatus, comprising:
the weight configuration module is used for distributing routing weights to all nodes according to the preset total weights by the routing gateway; load balancing is carried out according to the routing weight;
the weight dynamic adjustment module is used for updating the routing weights of all the nodes according to a preset value to obtain new routing weights when the throughput performance of the nodes is increased, and the sum of all the new routing weights is the total weight; the performance judging module is used for executing the following steps: s1, increasing the preset value for the routing weight of the node and subtracting the preset value for the weight routing of another node when the load balancing operates for a time period; s2, judging whether the throughput of the node is increased or not; if yes, executing S3; if not, executing S4; s3, judging that the throughput performance of the node is increased; s4, selecting the next node to execute S1 until the routing weight of each node is kept unchanged after a plurality of time periods;
the load balancing adjustment module is used for carrying out load balancing according to the new routing weight;
wherein, the weight dynamic adjustment module includes:
a weight increasing unit, configured to increase the routing weight of the node by the preset value when the throughput performance of the node increases, so as to obtain a corresponding new routing weight;
and the weight reduction unit is used for subtracting the preset value from the total routing weight of one or more nodes in other nodes to obtain a corresponding new routing weight, so that the sum of the routing weights of all the nodes is the total weight.
5. A computing device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the traffic load balancing method according to any one of claims 1 to 3 when executing said computer program.
6. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the traffic load balancing method according to any of claims 1 to 3.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005057514A (en) * | 2003-08-05 | 2005-03-03 | Nec Corp | Multi-homing load sharing method and device therefor |
| CN105809924A (en) * | 2016-03-09 | 2016-07-27 | 吉林大学 | Real-time transmission system for microseism fracturing monitoring |
| CN109408211A (en) * | 2018-09-28 | 2019-03-01 | 桂林电子科技大学 | A kind of equity network flow medium system data scheduling algorithm of multiple-objection optimization |
| CN109617826A (en) * | 2018-12-29 | 2019-04-12 | 南京航空航天大学 | A kind of storm dynamic load balancing method based on cuckoo search |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101753444B (en) * | 2009-12-31 | 2012-01-18 | 卓望数码技术（深圳）有限公司 | Method and device for load balancing |
| CN105553872A (en) * | 2015-12-25 | 2016-05-04 | 浪潮(北京)电子信息产业有限公司 | Multipath data traffic load equalizing method |
| CN105491150A (en) * | 2015-12-28 | 2016-04-13 | 中国民航信息网络股份有限公司 | Load balance processing method based on time sequence and system |
| US20170223572A1 (en) * | 2016-01-29 | 2017-08-03 | Lilee Systems, Ltd. | Method and Apparatus of Dynamic Weighted Load-balancing System |
| CN107295048B (en) * | 2016-04-01 | 2021-03-23 | 百度在线网络技术（北京）有限公司 | Load balancing method and device |
| CN108762924A (en) * | 2018-05-28 | 2018-11-06 | 郑州云海信息技术有限公司 | A kind of method, apparatus and computer readable storage medium of load balancing |
| CN108809848A (en) * | 2018-05-28 | 2018-11-13 | 北京奇艺世纪科技有限公司 | Load-balancing method, device, electronic equipment and storage medium |
-
2020
- 2020-12-30 CN CN202011622367.9A patent/CN112787948B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005057514A (en) * | 2003-08-05 | 2005-03-03 | Nec Corp | Multi-homing load sharing method and device therefor |
| CN105809924A (en) * | 2016-03-09 | 2016-07-27 | 吉林大学 | Real-time transmission system for microseism fracturing monitoring |
| CN109408211A (en) * | 2018-09-28 | 2019-03-01 | 桂林电子科技大学 | A kind of equity network flow medium system data scheduling algorithm of multiple-objection optimization |
| CN109617826A (en) * | 2018-12-29 | 2019-04-12 | 南京航空航天大学 | A kind of storm dynamic load balancing method based on cuckoo search |
Non-Patent Citations (1)
| Title |
|---|
| 基于信息资源地址的Web集群分配策略;李兰英;蒋维成;何勇;李晓芳;;科学技术与工程;第16卷(第20期);第228-232页 * |
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