Abstract

Defending all single connection failures for a particular system, segment routing issue, the switch will focus on the problems of selecting a small subset of trust-aware routing to improve the deep learning (DL). In the end, even if there were multiple path failures, these paths may introduce long-term, unnecessary overload in the proposed long short-term memory networks-based queuing routing segmentation (LSTM-QRS) experience of reducing traffic delays and adjusting traffic length by reducing network bandwidth. The critical factor is a novel traffic repair technique used to create a traffic repair path that switches to software-defined network (SDN) using multiple routing and providing additional flexibility in re-routing using long short-term memory networks (LSTM)-based queuing routing segment (LSTM-QRS) algorithms. It reduces the repair path length and recommends replacing the target-based traffic with the connection-based traffic fault detection router to avoid targeted traffic network congestion.

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