Congestion control issues have received consistent attention from several telecommunication researchers and practitioners for many years because network congestion often causes significant packet loss and delay problems. Although many suggested methods for these issues and problems can be available in telecommunication literature, there is room for improvement. This paper's primary objective is to propose a dynamic weighting method in routing to reduce congestion during peak hours by predicting incoming traffics and optimizing weights in the adjacency matrix of the routing table online. While changing weight values in the routing table, this method implicitly changes the routing path of many nodes through the congested node. As a result, the packet losses and delays can be decreased in used nodes. The main steps of this proposed framework are fourfold. First, the candidate weighing list is calculated based on the routing table of the congested node. Second, a proposed auto-adaptive framework (AAF) is used to predict congestion levels and apply the weighing list in the network node. Third, the evaluation of network congestion is then performed by the probability of packet losses due to overflowing buffers. Finally, the case study results demonstrate that the proposed AAF framework can significantly reduce network congestion.

多年来，拥塞控制问题一直受到几位电信研究人员和从业者的关注，因为网络拥塞通常会导致严重的数据包丢失和延迟问题。尽管在电信文献中可以找到许多针对这些问题的建议方法，但仍有改进的空间。本文的主要目的是提出一种动态加权路由方法，以通过预测传入流量并优化在线路由表邻接矩阵中的权重来减少高峰时段的拥塞。在更改路由表中的权重值时，此方法隐式更改许多节点通过拥塞节点的路由路径。结果，可以减少使用节点中的分组丢失和延迟。该提议框架的主要步骤有四个方面。首先，基于拥塞节点的路由表计算候选加权列表。其次，提出的自适应框架（AAF）用于预测拥塞级别并在网络节点中应用权重列表。第三，然后通过由于缓冲区溢出导致的数据包丢失的概率来执行网络拥塞评估。最后，案例研究结果表明，提出的AAF框架可以大大减少网络拥塞。然后，通过由于缓冲区溢出导致的数据包丢失的可能性来执行网络拥塞的评估。最后，案例研究结果表明，提出的AAF框架可以大大减少网络拥塞。然后，通过由于缓冲区溢出导致的数据包丢失的可能性来执行网络拥塞的评估。最后，案例研究结果表明，提出的AAF框架可以大大减少网络拥塞。