Intelligent network control system and method

A technology of intelligent network and control system, which is applied in the direction of transmission system, digital transmission system, data exchange network, etc. It can solve problems affecting network performance, high CPU load, multiple IP addresses, etc., to meet network requirements and reduce hardware equipment requirements , Improve the effect of network performance

Active Publication Date: 2021-01-15
NANJING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

When low-level devices carry high-load traffic or tasks, they often cause problems such as packet loss, packet extension, and high CPU load, thereby affecting network performance.
[0005] 3) The functions of traditional network equipment are defined by the manufacturer, and administrators can only configure and apply them according to the existing functions
But it also has many disadvantages: a) In order to make this DNS server interact with other DNS servers in time, ensure that DNS data is updated in time, and that addresses can be randomly assigned, generally the DNS refresh time must be set to a small value, but too small will It will cause a large increase in DNS traffic and cause additional network problems; b) Once a server fails, even if the DNS settings are modified in time, it still needs to wait for enough time (refresh time) to take effect. During this period, the faulty server is saved The client computer at the address will not be able to access the server normally; c) DNS load balancing uses a simple round-robin load algorithm, which cannot distinguish between servers, cannot reflect the current operating status of the server, and cannot allocate more to servers with better performance Requests, even the situation that customer requests are concentrated on a certain server; d) Each server must be assigned an IP address on the Internet, which will inevitably take up too many IP addresses
[0011] The use of switching load (fourth layer load balancing) and seventh layer load balancing is limited by the protocols it supports (generally only HTTP), which limits its wide application, and checking HTTP headers will take up a lot of system resources. It will inevitably affect the performance of the system. In the case of a large number of connection requests, the load balancing device itself will easily become the bottleneck of the overall performance of the network.

Method used

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  • Intelligent network control system and method
  • Intelligent network control system and method

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Experimental program
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Embodiment

[0064] The preliminary design process of this system is as follows: figure 1 As shown, the specific design process is as follows:

[0065] The first step is to use a KSP optimization algorithm HRAF (Heuristic and Recursive Algorithm by using on-the-Fly search) that mixes multiple search techniques to perform a pathfinding heuristic algorithm to initially select K optimal paths for the business.

[0066] The second step is to carry out binning, build a node pair model, use Euclidean distance as the similarity measurement method to cluster network traffic services, use descending best fit algorithm for binning, and collect training data and add labels, training contains multi-hidden The deep learning network model of the layered machine learning architecture, through large-scale data training, obtains a large amount of more representative feature information, builds a path database, realizes dynamic routing decisions, and plans the optimal path

[0067] The third step is to use...

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Abstract

The invention discloses an intelligent network control system and method. The system includes a path-finding module, a packing module, a constraint metric learning module, a network monitoring and evaluation module and a congestion control module. The path-finding module utilizes KSP optimization algorithms of various search technologies. Find feasible paths for business traffic; the packing module combines heuristic algorithms with a supervised deep learning network to plan the optimal path; the constraint metric learning module restricts some network resources, and the network monitoring and evaluation module is used for the system network. A detection is performed, a database is established, and the network is monitored and fed back in real time; the congestion control module is triggered by the network monitoring and evaluation module, so as to take some measures to solve the network congestion. Through the interaction of several modules, forwarding paths are selected according to the current real-time network conditions, and dynamic multi-path load balancing is realized, thereby reducing hardware device requirements, improving network performance, and meeting user network requirements.

Description

technical field [0001] The invention relates to intelligent network control technology, in particular to an intelligent network control system and method. Background technique [0002] For a long time, the working method of the traditional network is that the network devices independently learn the entire network topology through different protocols, make decisions and forward data according to different interaction mechanisms, and when the devices perceive changes in the nodes in the network, they will Each will re-establish the neighbor relationship, learn the global topology, and calculate the routing path. The decentralized decision-making method of traditional network equipment has been used to this day. However, as the network scale becomes larger and larger, some limitations of the traditional network architecture itself are gradually exposed. The following problems are difficult to fundamentally solve: [0003] 1) With the gradual increase in the scale of the data c...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/723H04L12/803H04L12/851H04L45/50
CPCH04L45/50H04L47/125H04L47/24
Inventor 王永利赵宁刘晨阳曹娜冯霞袁欢欢范嘉捷王振鹏秦昊周子韬明晶晶刘聪
Owner NANJING UNIV OF SCI & TECH
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