CN113438164A - Dynamic multi-path optimization method, system and equipment based on cloud network fusion technology - Google Patents
Dynamic multi-path optimization method, system and equipment based on cloud network fusion technology Download PDFInfo
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/14—Routing performance; Theoretical aspects
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- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/24—Multipath
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/24—Multipath
- H04L45/245—Link aggregation, e.g. trunking
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/30—Routing of multiclass traffic
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/302—Route determination based on requested QoS
- H04L45/306—Route determination based on the nature of the carried application
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- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/12—Avoiding congestion; Recovering from congestion
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Abstract
A dynamic multi-path optimization method based on a cloud network fusion technology comprises the following steps: dynamically acquiring performance index information, application requirement information, application service priority information and link cost information in real time; according to the obtained dynamic information, executing dynamic multipath optimization selection aiming at each data packet, and guiding the data packet to an optimal link corresponding to the data packet; when dynamic multipath optimization selection is executed, instantly classifying and dynamically distributing flow to a link based on a preset application strategy and a service quality index; when dynamic multipath optimization selection is executed, broadband link information and leased line information are obtained, and a virtual high-bandwidth pipeline is established; when dynamic multi-path optimization selection is executed, application and link decoupling are executed based on link group strategy separation and a backup link strategy; the method comprises the steps of obtaining key application access priority level information of a user, determining real-time flow with higher service priority, and executing priority conversion.
Description
Technical Field
The invention relates to the field of computers, in particular to a dynamic multi-path optimization method, a dynamic multi-path optimization system and dynamic multi-path optimization equipment based on a cloud network fusion technology.
Background
Cloud network convergence is a technology of introducing a network into cloud computing and a technology of introducing cloud computing into a communication network. The service requirement and the technical innovation drive the accelerating network architecture to have deep revolution, and the cloud and the network are highly cooperative and are not independent. Cloud network convergence has become a development trend in the field of cloud computing. The development of cloud computing services needs strong network capability support, the optimization of network resources also needs to use the concept of cloud computing, and the concept of cloud network fusion is developed accordingly. The cloud network integration is a network architecture deep revolution brought by parallel drive based on business requirements and technical innovation, so that the cloud and the network are highly cooperative, mutually supported and mutually referenced, and meanwhile, a bearing network is required to open network capacity according to various cloud service requirements, agile opening and on-demand interconnection of the network and the cloud are realized, and the characteristics of intellectualization, self-service, high speed, flexibility and the like are embodied. The service capability of cloud network fusion is based on the capability of cloud access and basic connection provided by a cloud private network, cloud network products (such as a cloud private line and an SD-WAN) covering different scenes are provided outwards by combining with a cloud platform of a cloud service provider, and are deeply combined with other types of cloud services (such as computing, storage and safety cloud services), and finally extend to specific industrial application scenes, and a composite cloud network fusion solution is formed.
At present, many enterprises have a plurality of branches, the branches cannot access data of a headquarters, the headquarters cannot acquire the branched data, and the traditional special line gradually cannot deal with the problems, so that the price is high, the deployment time is long, and increasingly complex and continuously flexible business scenes of the enterprises cannot be met. More and more enterprise data or applications begin to appear in the cloud, and mutual access and intercommunication under the cloud also gradually become problems for enterprises.
With the development of informatization and diversified business requirements, more and more employees of enterprises cannot be used in offices, homes, coffee shops, tea rooms, hotels and other places to become more and more office or guest-meeting places of the employees of the enterprises. Personnel working outside cannot access the internal application of the enterprise, and no good network environment exists for working.
Disclosure of Invention
One of the purposes of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which can ensure key application experience and improve bandwidth utilization.
One of the purposes of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which optimizes a key application experience by using a key WOC algorithm.
One of the objectives of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which can perform one-hop cloud access and multi-branch-to-multi-cloud interconnection as required, thereby achieving an optimal IaaS (infrastructure as a service)/SaaS (software as a service) experience.
One of the objectives of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which can guide a data packet to an optimal link according to a performance index, an application requirement, an application service priority and a link cost.
One of the objectives of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which can create a virtual high bandwidth pipeline by using a plurality of cheap broadband links and leased lines, so as to improve WAN economic benefit and quality for customers.
One of the purposes of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which can improve the stability of the cloud network convergence application service guarantee, improve the quality of the application in use, and avoid an uncontrollable state.
One of the purposes of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which can improve the integrity of records and information of applications, and avoid data loss, such as record loss and specific field information loss.
One of the objectives of the present invention is to provide a dynamic multipath optimization method, system and device based on a cloud network convergence technology, which can improve the accuracy of information recorded in an application and reduce abnormal or erroneous information.
One of the purposes of the invention is to provide a dynamic multi-path optimization method, system and device based on a cloud network fusion technology, which can ensure the timely output of applications and ensure the value of data.
In order to achieve at least one of the objectives of the present invention, the present invention provides a dynamic multipath optimization method based on a cloud network convergence technology, including the following steps:
dynamically acquiring performance index information, application requirement information, application service priority information and link cost information in real time;
according to the obtained dynamic information, executing dynamic multipath optimization selection aiming at each data packet, and guiding the data packet to an optimal link corresponding to the data packet;
when dynamic multipath optimization selection is executed, instantly classifying and dynamically distributing flow to a link based on a preset application strategy and a service quality index;
when dynamic multipath optimization selection is executed, broadband link information and leased line information are obtained, and a virtual high-bandwidth pipeline is established;
when dynamic multi-path optimization selection is executed, application and link decoupling are executed based on link group strategy separation and a backup link strategy;
the method comprises the steps of obtaining key application access priority level information of a user, determining real-time flow with higher service priority, and executing priority conversion.
In some embodiments, the dynamic multipath optimization method based on the cloud network convergence technology further includes the following steps:
continuously monitoring paths and links;
automatically detecting the capacity and sensing the transmission state of each data packet; and
when the initial path is failed to be established or exceeds a set threshold value, the real-time flow is automatically switched to a second path;
wherein, the TCP flow is load balanced on at least two links based on each data packet, and link aggregation is executed; where the gateway and terminal reorder the packets where the application flow is aggregated over multiple internet links for higher throughput.
In some embodiments, the dynamic multipath optimization method based on the cloud network convergence technology further includes the following steps: and when the real-time flow with higher service priority is determined, performing on-demand forward error correction operation to reduce or eliminate packet loss.
In some embodiments, the dynamic multipath optimization method based on the cloud network convergence technology further includes the following steps: deep packet inspection and application layer identification is performed.
In some embodiments, the dynamic multipath optimization method based on the cloud network convergence technology further includes the following steps: and executing the setting of the priority of the key business application, wherein the path and the link are continuously monitored, when the key application information of the voice or video conference or the cloud service is monitored, the priority corresponding to the key application information is improved and set, and the path with the lowest packet loss rate is selected, so that the appointed application is ensured to be accessed to the available bandwidth to meet the requirement of the key business. .
In some embodiments, the dynamic multipath optimization method based on the cloud network convergence technology further includes the following steps: and establishing a WOC algorithm model of FillP and a WOC algorithm model of A-FEC, and dynamically optimizing the key service application in multipath.
In some embodiments, the dynamic multipath optimization method based on the cloud network convergence technology further includes the following steps: and creating a PBR policy route, instantly classifying and dynamically allocating traffic to the PBR policy route based on a preset application policy and a service quality index, wherein the service requirement and priority are contained in the policy to define the service level of the application, and for data-sensitive voice and video applications, a path with the lowest packet loss rate is selected.
According to another aspect of the present invention, a dynamic multipath optimization system based on a cloud network convergence technology is further provided, where the dynamic multipath optimization system based on the cloud network convergence technology is provided with an application guarantee module configured to perform dynamic multipath optimization, where the application guarantee module guides a data packet to an optimal link according to a performance index, an application requirement, an application service priority, and a link cost, determines a real-time traffic with a higher service priority, and then performs an on-demand forward error correction operation to reduce or eliminate packet loss, where the application guarantee module is further configured to define an application service guarantee policy according to a key application access priority level of a user based on a deep packet inspection and an application layer identification technology; wherein the application assurance module is further configured to: WOC algorithm of FillP and A-FEC is executed, and the dynamic multipath optimization is applied in a key way.
In some embodiments, wherein the application assurance module is further configured to: establishing decoupling between an application and a link; continuously monitoring the paths and the links, automatically detecting the capacity and sensing the transmission state of each data packet, and automatically switching the real-time flow to the second path when the initial path is failed to be established or exceeds a set threshold value; wherein TCP traffic performs link aggregation on a per packet basis with load balancing across at least two links; wherein the gateway and the terminal reorder the data packets; where critical application flows are aggregated over multiple internet links for higher throughput.
According to another aspect of the present invention, there is also provided a dynamic multipath optimization device based on a cloud network convergence technology, including:
a memory for storing a software application,
and the processor is used for executing the software application programs, and each program of the software application programs correspondingly executes the steps in the dynamic multipath optimization method based on the cloud network fusion technology.
Drawings
Fig. 1 is a schematic diagram of a dynamic multipath optimization method based on a cloud network convergence technology according to an embodiment of the present invention.
Detailed Description
The following description is presented to disclose the invention so as to enable any person skilled in the art to practice the invention. The preferred embodiments in the following description are given by way of example only, and other obvious variations will occur to those skilled in the art. The basic principles of the invention, as defined in the following description, may be applied to other embodiments, variations, modifications, equivalents, and other technical solutions without departing from the spirit and scope of the invention.
It is understood that the terms "a" and "an" should be interpreted as meaning that a number of one element or element is one in one embodiment, while a number of other elements is one in another embodiment, and the terms "a" and "an" should not be interpreted as limiting the number.
The present invention relates to a computer program. The invention discloses a dynamic multi-path optimization method based on a cloud network fusion technology, which explains a solution for solving the problems provided by the invention, and the solution is that on the basis of a computer program processing flow, a computer program compiled according to the flow is executed by a computer, and an external object or an internal object of the computer is controlled or processed. According to the dynamic multi-path optimization method based on the cloud network fusion technology, the data packet can be guided to the optimal link by using the computer system according to the performance index, the application requirement, the application service priority and the link cost. The technique can create a virtual high bandwidth pipe using inexpensive broadband links and leased lines to improve WAN economics and quality for customers. After real-time traffic with higher traffic priority (e.g., VOIP) is determined, on-demand forward error correction operations may be performed to reduce or eliminate packet loss. The deep packet inspection and application layer identification technology flexibly defines different application service guarantee strategies according to the key application access priority level of a user.
Specifically, as shown in fig. 1, the dynamic multipath optimization method based on the cloud network convergence technology includes the following steps:
dynamically acquiring performance index information, application requirement information, application service priority information and link cost information in real time;
according to the obtained dynamic information, executing dynamic multipath optimization selection aiming at each data packet, and guiding the data packet to an optimal link corresponding to the data packet;
when dynamic multipath optimization selection is executed, instantly classifying and dynamically distributing flow to a link based on a preset application strategy and a service quality index;
when dynamic multipath optimization selection is executed, broadband link information and leased line information are obtained, and a virtual high-bandwidth pipeline is established;
when dynamic multi-path optimization selection is executed, application and link decoupling are executed based on link group strategy separation and a backup link strategy;
the method comprises the steps of obtaining key application access priority level information of a user, determining real-time flow with higher service priority, and executing priority conversion.
Further, the dynamic multipath optimization method based on the cloud network fusion technology further comprises the following steps:
continuously monitoring paths and links;
automatically detecting the capacity and sensing the transmission state of each data packet; and
when the initial path is failed to be established or exceeds a set threshold value, the real-time flow is automatically switched to a second path;
wherein, the TCP flow is load balanced on at least two links based on each data packet, and link aggregation is executed; where the gateway and terminal reorder the packets where the application flow is aggregated over multiple internet links for higher throughput.
It should be noted that, the real-time traffic with higher service priority is determined according to the key application access priority information of the user, the priority conversion completely depends on the user, the user can create the priority of the access application in a customized manner, for example, when an individual website needs to be accessed, the user can set the website which the user wants to access as high priority, and the speed of accessing the website with high priority by the user in the same time period can be obviously faster than the speed of accessing other services by the user. Of course, if the user does not access the high priority application set by the user during the time period, the speed of the application currently accessed by the user at that time will be equal to the speed at the high priority.
Further, the dynamic multipath optimization method based on the cloud network fusion technology further comprises the following steps:
and when the real-time flow with higher service priority is determined, performing on-demand forward error correction operation to reduce or eliminate packet loss.
It should be noted that some services based on IP generally use UDP for transmission for real-time performance, so packet loss is inevitable, and for real-time performance, a mechanism that a receiving end finds that packet loss occurs and then notifies a transmitting end to retransmit the packet loss is generally not used, because packet loss detection and notification at an application layer are time-consuming for the transmitting end to retransmit the packet loss. The dynamic multi-path optimization method based on the cloud network fusion technology introduces a forward error correction mechanism, is a good mechanism for solving real-time service packet loss, and inserts the redundant packet when the sending end sends the data packet, so that all data packets can be restored even if the data received by the receiving end has packet loss (the packet loss number is not more than the redundant packet).
Further, the dynamic multipath optimization method based on the cloud network fusion technology further comprises the following steps:
deep packet inspection and application layer identification is performed.
Deep packet inspection is a computer network packet filtering technique used to examine the data portion (and possibly the header) of a data packet passing through an inspection point to search for out-of-specification protocols, viruses, spam, intrusions, or to determine whether the data packet can pass or needs to be routed to a different destination based on predetermined criteria. IP packets have many headers; in normal operation, the network device only needs to use the first header (IP header), and the second header (TCP, UDP, etc.) is usually used for deep packet inspection, which is called shallow packet inspection. There are a number of ways in which the packets for deep packet inspection can be obtained. The more common methods are port mirroring and fiber optic splitters. In any event, when a vulnerability exists at the network layer, that layer is not visible to the stateful firewall. The firewall cannot distinguish between allowed and prohibited users of legitimate access applications. It is worth mentioning that deep packet inspection allows information security personnel to set and run policies at any level, including the application level and the user level, to assist in fighting these threats.
Further, the dynamic multipath optimization method based on the cloud network fusion technology further comprises the following steps:
executing the setting of the priority of the key service application;
when the path and the link are continuously monitored, and key application information of a voice or video conference or cloud service is monitored, the priority corresponding to the key application information is improved and set, and the path with the lowest packet loss rate is selected, so that the appointed application is accessed to the available bandwidth to meet the key service requirement.
It is worth mentioning that the key application experience is guaranteed, and the bandwidth utilization rate can be improved to be within the range of 60% -90%.
It should be mentioned that the dynamic multipath optimization method based on the cloud network fusion technology further includes the following steps:
and establishing a WOC algorithm model of FillP and a WOC algorithm model of A-FEC, and dynamically optimizing the key service application in multipath.
Further, the dynamic multipath optimization method based on the cloud network fusion technology further comprises the following steps:
and creating a PBR policy route, instantly classifying and dynamically allocating traffic to the PBR policy route based on a preset application policy and a service quality index, wherein the service requirement and priority are contained in the policy to define the service level of the application, and for data-sensitive voice and video applications, a path with the lowest packet loss rate is selected.
As will be appreciated by one skilled in the art, 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.
Those skilled in the art will appreciate that the methods of the present invention can be implemented in hardware, software, or a combination of hardware and software. The present invention can be realized in a centralized fashion in at least one computer system, or in a distributed fashion where different elements are spread across several interconnected computer systems. Any kind of computer system or other apparatus adapted for carrying out the methods described herein is suited. A typical combination of hardware and software could be a general purpose computer system with a computer program that, when being loaded and executed, controls the computer system such that it carries out the methods described herein.
The present invention can be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein. The computer program product is embodied in one or more computer-readable storage media having computer-readable program code embodied therein. According to another aspect of the invention, there is also provided a computer-readable storage medium having stored thereon a computer program capable, when executed by a processor, of performing the steps of the method of the invention. Computer storage media is media in computer memory for storage of some discrete physical quantity. Computer storage media includes, but is not limited to, semiconductors, magnetic disk storage, magnetic cores, magnetic drums, magnetic tape, laser disks, and the like. It will be appreciated by persons skilled in the art that computer storage media are not limited by the foregoing examples, which are intended to be illustrative only and not limiting of the invention.
Corresponding to the embodiment of the method, according to another aspect of the invention, a dynamic multipath optimization system based on a cloud network fusion technology is also provided, and the dynamic multipath optimization system based on the cloud network fusion technology is an application of the method in the improvement of computer programs. The dynamic multi-path optimization system based on the cloud network fusion technology is provided with an application guarantee module.
In particular, the application assurance module is configured to perform dynamic multipath optimization. The application guarantee module guides the data packet to the optimal link according to the performance index, the application requirement, the application service priority and the link cost, determines the real-time flow with higher service priority, and then executes the on-demand forward error correction operation to reduce or eliminate packet loss, wherein the application guarantee module is also configured to define the applied service guarantee strategy according to the key application access priority of the user based on the deep packet detection and application layer identification technology.
According to another aspect of the present invention, there is also provided a dynamic multipath optimization device based on a cloud network convergence technology, including: a software application, a memory for storing the software application, and a processor for executing the software application. Each program of the software application program can correspondingly execute the steps in the dynamic multipath optimization method based on the cloud network fusion technology.
It will be appreciated by those skilled in the art that the present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, systems and computer program products according to the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of 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 and/or block diagram block or blocks.
It will be appreciated by persons skilled in the art that the embodiments of the invention described above and shown in the drawings are given by way of example only and are not limiting of the invention. The objects of the invention have been fully and effectively accomplished. The functional and structural principles of the present invention have been shown and described in the examples, and any variations or modifications of the embodiments of the present invention may be made without departing from the principles.
Claims (10)
1. A dynamic multi-path optimization method based on a cloud network fusion technology is characterized by comprising the following steps:
dynamically acquiring performance index information, application requirement information, application service priority information and link cost information in real time;
according to the obtained dynamic information, executing dynamic multipath optimization selection aiming at each data packet, and guiding the data packet to an optimal link corresponding to the data packet;
when dynamic multipath optimization selection is executed, instantly classifying and dynamically distributing flow to a link based on a preset application strategy and a service quality index;
when dynamic multipath optimization selection is executed, broadband link information and leased line information are obtained, and a virtual high-bandwidth pipeline is established;
when dynamic multi-path optimization selection is executed, application and link decoupling are executed based on link group strategy separation and a backup link strategy;
the method comprises the steps of obtaining key application access priority level information of a user, determining real-time flow with higher service priority, and executing priority conversion.
2. The dynamic multipath optimization method based on the cloud network convergence technology as claimed in claim 1, wherein the dynamic multipath optimization method based on the cloud network convergence technology further comprises the following steps:
continuously monitoring paths and links;
automatically detecting the capacity and sensing the transmission state of each data packet; and
when the initial path is failed to be established or exceeds a set threshold value, the real-time flow is automatically switched to a second path;
wherein, the TCP flow is load balanced on at least two links based on each data packet, and link aggregation is executed; where the gateway and terminal reorder the packets where the application flow is aggregated over multiple internet links for higher throughput.
3. The dynamic multipath optimization method based on the cloud network convergence technology as claimed in claim 2, wherein the dynamic multipath optimization method based on the cloud network convergence technology further comprises the following steps: and when the real-time flow with higher service priority is determined, performing on-demand forward error correction operation to reduce or eliminate packet loss.
4. The dynamic multipath optimization method based on the cloud network convergence technology as claimed in claim 3, wherein the dynamic multipath optimization method based on the cloud network convergence technology further comprises the following steps: deep packet inspection and application layer identification is performed.
5. The dynamic multipath optimization method based on the cloud network convergence technology as claimed in claim 1, wherein the dynamic multipath optimization method based on the cloud network convergence technology further comprises the following steps: and executing the setting of the priority of the key business application, wherein the path and the link are continuously monitored, when the key application information of the voice or video conference or the cloud service is monitored, the priority corresponding to the key application information is improved and set, and the path with the lowest packet loss rate is selected, so that the appointed application is ensured to be accessed to the available bandwidth to meet the requirement of the key business.
6. The dynamic multipath optimization method based on the cloud network convergence technology as claimed in any one of claims 1 to 5, wherein the dynamic multipath optimization method based on the cloud network convergence technology further comprises the following steps: and establishing a WOC algorithm model of FillP and a WOC algorithm model of A-FEC, and dynamically optimizing the key service application in multipath.
7. The dynamic multipath optimization method based on the cloud network convergence technology as claimed in claim 1, wherein the dynamic multipath optimization method based on the cloud network convergence technology further comprises the following steps: and creating a PBR policy route, instantly classifying and dynamically allocating traffic to the PBR policy route based on a preset application policy and a service quality index, wherein the service requirement and priority are contained in the policy to define the service level of the application, and for data-sensitive voice and video applications, a path with the lowest packet loss rate is selected.
8. A dynamic multi-path optimization system based on a cloud network fusion technology is characterized in that the dynamic multi-path optimization system based on the cloud network fusion technology is provided with an application guarantee module, and the application guarantee module is configured to execute dynamic multi-path optimization, wherein the application guarantee module guides a data packet to an optimal link according to a performance index, an application requirement, an application service priority and a link cost, determines real-time flow with higher service priority and then executes on-demand forward error correction operation to reduce or eliminate packet loss, and the application guarantee module is further configured to define an applied service guarantee strategy according to a key application access priority level of a user based on a deep packet detection and application layer identification technology; wherein the application assurance module is further configured to: WOC algorithm of FillP and A-FEC is executed, and the dynamic multipath optimization is applied in a key way.
9. The dynamic multipath optimization system based on cloud network convergence technology of claim 8, wherein the application assurance module is further configured to: establishing decoupling between an application and a link; continuously monitoring the paths and the links, automatically detecting the capacity and sensing the transmission state of each data packet, and automatically switching the real-time flow to the second path when the initial path is failed to be established or exceeds a set threshold value; wherein TCP traffic performs link aggregation on a per packet basis with load balancing across at least two links; wherein the gateway and the terminal reorder the data packets; where critical application flows are aggregated over multiple internet links for higher throughput.
10. A dynamic multi-path optimization device based on a cloud network convergence technology is characterized by comprising the following components:
a memory for storing a software application,
a processor for executing the software applications, wherein each program of the software applications correspondingly executes the steps of the dynamic multipath optimization method based on the cloud network convergence technology in claims 1 to 7.
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| CN114465954A (en) * | 2021-12-27 | 2022-05-10 | 天翼云科技有限公司 | Self-adaptive routing method, device and equipment for special cloud line and readable storage medium |
| CN114553781A (en) * | 2021-12-23 | 2022-05-27 | 北京秒如科技有限公司 | Efficient transport layer multi-path convergence method and system |
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| CN115277378B (en) * | 2022-05-19 | 2024-03-19 | 亿点云计算(珠海)有限公司 | Service switching method, device, terminal and storage medium based on stateful service |
Family Cites Families (6)
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| CN1254059C (en) * | 2002-12-10 | 2006-04-26 | 华为技术有限公司 | Method of realizing special multiple-protocol label exchanging virtual network |
| CN101252494B (en) * | 2008-04-09 | 2011-04-13 | 杭州华三通信技术有限公司 | Equipment and method for sharing traffic load |
| CN103618678A (en) * | 2013-11-18 | 2014-03-05 | 北京星网锐捷网络技术有限公司 | Method, device and system for self-adaptation multiple-link aggregation |
| CN110289996A (en) * | 2019-06-14 | 2019-09-27 | 浪潮思科网络科技有限公司 | A kind of business route computing method based on SR |
| CN111740875A (en) * | 2020-05-22 | 2020-10-02 | 浪潮思科网络科技有限公司 | Service data forwarding method, device, equipment and medium |
| CN111953602B (en) * | 2020-07-30 | 2022-07-12 | 新华三技术有限公司 | Routing method and device |
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- 2022-01-10 CN CN202210024007.1A patent/CN114363242A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114070786A (en) * | 2021-11-11 | 2022-02-18 | 北京天融信网络安全技术有限公司 | Dynamic scheduling method and device for policy routing |
| CN114070786B (en) * | 2021-11-11 | 2023-07-11 | 北京天融信网络安全技术有限公司 | Policy routing dynamic scheduling method and device |
| CN114553781A (en) * | 2021-12-23 | 2022-05-27 | 北京秒如科技有限公司 | Efficient transport layer multi-path convergence method and system |
| CN114465954A (en) * | 2021-12-27 | 2022-05-10 | 天翼云科技有限公司 | Self-adaptive routing method, device and equipment for special cloud line and readable storage medium |
| CN114745277A (en) * | 2022-03-30 | 2022-07-12 | 杭州博盾习言科技有限公司 | Elastic expansion method and device for public cloud cross-domain private line, electronic equipment and medium |
| CN114745277B (en) * | 2022-03-30 | 2024-05-28 | 杭州博盾习言科技有限公司 | Elastic expansion method and device for public cloud cross-domain private line, electronic equipment and medium |
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| CN114363242A (en) | 2022-04-15 |
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