Network transmission capacity is an important guarantee for the normal operation of the network. The effective routing strategy avoids the use of nodes with large degree value, which leads to low utilization of nodes and failure to consider the priorities of different packets. On this basis, a routing algorithm based on packet source node classification is proposed. This strategy introduces an adjustable parameter. By adjusting this parameter, the data packets generated at the important nodes are transferred to the nodes with higher degree, which is to say they can reach the destination faster. The data packets generated at the sub-important nodes are transmitted by nodes with smaller degrees, thus reaching the destination relatively slowly. The routing strategy is evaluated in terms of order parameters, average routing time and node utilization. Compared with nonclassified routing and randomly classified routing strategy, the network transmission capacity was increased by 19% and 38%, respectively. Each node in the network was used more evenly. At the same time, the network transmission capacity under different parameters is analyzed theoretically through a series of derivations. In order to explore the performance of routing strategy in actual networks, this paper selects the actual network of web-EPA for simulation. The experimental results show that the proposed routing strategy is 7% and 17% higher than the nonclassified routing and random classified routing, respectively.
UFIR Filtering Under Uncertain One-Step Delayed and Missing Data