Intelligent Network Control

Author(s):  
Haipeng Yao ◽  
Chunxiao Jiang ◽  
Yi Qian



2005 ◽  
Vol 43 (5) ◽  
pp. S11-S18 ◽  
Author(s):  
K.H. Liu


2015 ◽  
Vol 734 ◽  
pp. 207-210
Author(s):  
Qing Quan Cui ◽  
Jing Ning

Automatic equipments workshop in the production process, the statistics and reports for various data is the condition that the statistics after the production. From the system perspective, this is an off-line control system, and the time difference will increase the failure rate and reduce the efficiency of the equipment manufacturing products. According to this problem, the intelligent network management scheme for the production equipment is designed in the paper, as aluminum electrolytic capacitor production equipment an example, the network control system (NCS) is introduced into the equipment management of production of aluminum electrolytic capacitors, and the design idea and structure are given. Through the design, the intelligent management of aluminum electrolytic capacitor production equipment is realized, which can ensure the efficient, real-time and accuracy of each production link in capacitor.



2014 ◽  
Vol 716-717 ◽  
pp. 1599-1603
Author(s):  
Zhi Xin Hu ◽  
Jiu Nan Xu ◽  
Ling Xiao Weng

This paper designs a new mechatronic modeling and simulation platform, which uses Solidworks to establish the mechanical model, and uses LabVIEW intelligent network library function to realize mechatronic control. Combining with VC software it realizes the simulation results visualized output, which realizes the co-simulation design of SolidWorks, LabVIEW and VC software. With the help of this system, engineers can establish mechanical model by computer software, and use interdisciplinary field theory to analyze the product key performance indicators in the virtual operating environment, further visual processing, and according to the simulation data to improve and optimize the system. It provides a new method for computer research and development of mechatronic products.



Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 700
Author(s):  
Aipeng Guo ◽  
Chunhui Yuan

For telecom operators, it is of great significance to employ artificial intelligence (AI) and big data technology in a software-defined network (SDN) in order to achieve intelligent network control, traffic management and optimization. This paper proposes a solution for intelligent work control and traffic optimization. This paper is mainly focused on SDN-based network traffic algorithm optimization and experimental verification. In this paper, we design a network control mechanism for network intelligent control as well as solutions for traffic optimization based on SDN and artificial intelligence. We analyze operators’ network requirements (e.g., the carrying of the 5th generation mobile network (5G) service, multi-protocol label switching virtual private networks optimization, cloudification of services and the IP backbone network). Then, we propose an intelligent network control architecture based on SDN and artificial intelligence. The proposed architecture consists of three modules, including a network status collection/perception module, an AI intelligent analysis module and an SDN controller module. Moreover, this paper also analyzes the objects of traffic optimization as well as routing calculation algorithms (e.g., the greedy algorithm, the top-k-shortest paths (KSP) algorithm) and routing optimization algorithms (e.g., particle swarm optimization, simulated annealing and genetic algorithms). In addition, we also put forward three optimization algorithms for the operator’s network, namely, network congestion control and prevention algorithms, resource preemption algorithms and balance of the entire network traffic algorithms. Then, we propose optimization algorithms for the above three objectives of operator network optimization, respectively. Finally, we conduct large-scale experiments to verify the effectiveness of the control mechanism and algorithms. The experimental results demonstrate that the use of SDN and artificial intelligence in operator networks can realize network intelligent control and traffic optimization more intelligently.



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