Abstract
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.
Highlights
Network intelligent control has always been the goal pursued by operators
The software-defined network (SDN) controller obtains the strategy generated by the artificial intelligence (AI) intelligent analysis module and calculates the adjustment object and adjustment strategy of the network optimization according to the intelligent network optimization algorithm
We designed a network control mechanism for network intelligent control and solutions for traffic optimization based on SDN and artificial intelligence
Summary
Network intelligent control has always been the goal pursued by operators. the optimization of the entire network traffic is a difficult problem, and it is an urgent problem to be solved. SDN technology provides new ideas for operators’ network equipment reconfiguration and networking architecture [10,11] (e.g., separation of control and forwarding, virtualization, capability opening, dynamic reconfiguration, centralized management and control), which solve the problem of poor network reliability, low and unbalanced resource utilization rate, high operation and maintenance costs and other issues [12,13,14]. Network intelligent control and traffic optimization can be realized based on SDN and AI, and paths of different priority service traffic can be scheduled real-timely; in this way, it is possible to avoid local congestion and improve network quality and network utilization of the entire network. If the traffic does not have detour conditions, it is necessary to limit the low-priority service traffic at the ingress to reduce the congested link bandwidth and always guarantee the service level agreement (SLA) quality of 5G high-priority services [24]
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