Human activities are highly predictable, so are the network traffic. It appears in a tidal phenomenon in traffic. Current resource allocation methods cannot adapt to tidal traffic, resulting in low resource utilization. To predicted tidal traffic, we have established a neural network model optimized by adaptive artificial fish swarm algorithm. Then we propose a novel multi-path pre-reserved resource allocation strategy to increase resource utilization. The results confirm the effectiveness of our method.
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