## 6 Discussion  
The following recommendations regarding applying the proposed load balancing models inside the network and at its edge can be offered based on the research results. The general recommendations include considering various traffic parameters when limiting it systematically, including the IP priorities of packet flows and their intensities. This is important from the point of view of ensuring DiffServ QoS and combating network overload. Thus, when using the technology of absolute priorities, when it is necessary to guarantee the service of high-priority traffic, it is appropriate to use the TER-LLM solution with weighting coefficients (9) in optimality criterion (6). During the implementation of this solution, as the research results showed (Figure 7), that packet flows with the highest IP priority are limited by their rate at the network edge last. Figure 10: The procedure for limiting different packet flow types when using the OSPF-TS model, when \(\alpha_{TH}=0.7\), \(PR^{1}=5\), and \(PR^{2}=2\): (**a**) the proportion of the first flow intensity that receives a denial of service; (**b**) the proportion of the second flow intensity that receives a denial of service; (**c**) the limitation intensity of the first flow at the border router; (**d**) the limitation intensity of the second flow at the border router. A more adaptive solution to limit the load at the network edge is the TER-LLM model with weighting coefficients (8) in optimality criterion (6). This solution generally supports the previous version's functionality, but also considers the packet flow rate arriving on the network. As the research results showed (Figures 3-5), when the upper bound of the network link utilization reaches the threshold value \(\alpha=\alpha_{TH}\), this solution implements sequential load balancing in the event of overloading. The packet flow that caused the overload was primarily limited in two prominent cases: first, in the load areas where the packet flow rates differed quite a lot (Figure 3); and second, in the case where the IP priorities of the flows were almost the same (Figure 5). When the flow rates were equalized, the restriction was implemented based on analyzing their IP priorities (Figure 3). On the other hand, the influence of flow rates on the limitation process was almost not felt at the maximum difference in the values of their IP priorities (Figure 4), which reflected the principle of the TER-LLM model with weighting coefficients (9). As the research results showed, the TER-TEL model was confirmed to have the highest level of adaptability when balancing the load in limiting it at the network edge. A common feature of these solutions is that IP priorities and packet flow rates are comprehensively considered when limiting the load. However, relative priorities are implemented when the network is overloaded, and all flows are limited; however, those with a higher IP priority are limited less intensively than lower-priority flows. Using weighting coefficients (8) in optimality criterion (11) allows, in addition to IP priorities, to consider flow rates in order to more intensively limit precisely those flows that cause overload. Then, Tables 3 and 4 demonstrate the results of traffic limitation for four characteristic points for comparison concerning the intensities of two flows under \(\alpha_{TH}=0.7\), \(PR^{1}=5\), and \(PR^{2}=2\) for the first stage of research when the two proposed optimality criteria (6) and (11) were used with weighting coefficients (8) in the corresponding objective function. Using the TER-TEL model and weighting coefficients (8  
their intensities; this was the study's primary purpose. With an increase in the available network resources (structural and link), the level of utilization of communication links will naturally decrease, and load limitation at the network edge will begin at higher packet flow rates.