Author(s)

Jingwen Wang, Guolong Yu, Xin Cui^*

School of Computer Science and Technology, Shandong University of Technology, Zibo, China.

Traditional traffic management techniques appear to be incompetent in complex data center networks, so proposes a load balancing strategy based on Long Short-Term Memory (LSTM) and quantum annealing by Software Defined Network (SDN) to dynamically predict the traffic and comprehensively consider the current and predicted load of the network in order to select the optimal forwarding path and balance the network load. Experiments have demonstrated that the algorithm achieves significant improvement in both system throughput and average packet loss rate for the purpose of improving network quality of service.

Data Center Network, Software Defined Network, Load Balance, Long Short-Term Memory, Quantum Annealing Algorithms

Wang, J. , Yu, G. and Cui, X. (2024) Multipath Selection Algorithm Based on Dynamic Flow Prediction. Journal of Computer and Communications, 12, 94-104. doi: 10.4236/jcc.2024.127007.