Network Intelligent Control and Traffic Optimization Based on SDN and Artificial Intelligence

被引:16
|
作者
Guo, Aipeng [1 ,2 ]
Yuan, Chunhui [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing 100087, Peoples R China
[2] China United Network Telecommun Corp, Beijing 100048, Peoples R China
关键词
artificial intelligence (AI); big data; network intelligent control; software-defined network (SDN); traffic optimization; SWARM;
D O I
10.3390/electronics10060700
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1 / 20
页数:18
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