## 5 Results
### Simulation Setup
In this paper, to make a more thorough investigation, we analyzed five traffic profiles (TPs) different in terms of the source-destination (s-d) nodes' distribution. The general idea of the traffic generation is based on the multivariable gravity model [31]. In more detail, the traffic generation is based on several components  
Figure 5: Tested network topologies: US26 (**a**), Euro28 (**b**). which can be tuned according to considered scenarios. The source node selection probability is based on metrics describing the nodes (cities), such as population of the country/city and GDP of the country/city, based on data available in Wikipedia. In turn, the destination node selection probability is based on various functions of the distance between each nodes pair (e.g., square root). In consequence, the created traffic reflects the multivariable gravity model with different parameters to account for the fact that the traffic in contemporary networks is highly dependent on services such as cloud computing and edge computing. The analyzed traffic profiles are as follows:  
* TP A. The distribution of requests between s-d nodes is uniform, i.e., the source node selection probability is the same for all nodes and the same applies for every node to be chosen as the destination node. * TP B. The distribution of requests between s-d nodes is inversely proportional to the square root of the distance between node pairs, i.e., the source node selection probability is uniform, but the probability of choosing the destination node is inversely proportional to the square root of the distance between selected source node and each of the remaining nodes. * TP C. The distribution of requests between s-d nodes is inversely proportional to the distance between node pairs, i.e., the source node selection probability is uniform, but the probability of choosing the destination node is inversely proportional to the distance between selected source node and each of the remaining nodes. * TP D. The distribution of requests between s-d nodes depends on the square root of two elements: distance between nodes (inversely) and product of population and GDP for given node, i.e., the source node selection probability is proportional to the square root of the product of population and GDP for given node. In turn, the probability of destination node selection is inversely proportional to the square root of the distance between chosen source node and each of the remaining nodes. * TP E. The distribution of requests between s-d nodes depends on two elements: distance between nodes (inversely) and product of population and GDP for given node, i.e., the source node selection probability is proportional to the product of population and GDP for a given node. In turn, the probability of destination node selection is inversely proportional to the distance between chosen source node and each of the remaining nodes. The basic performance metric used in the simulations is _bandwidth blocking probability_ (BBP) defined as the volume of rejected traffic divided by the volume of whole traffic offered to the network. Moreover, we use a metric called _accepted traffic_ which denotes the maximum traffic that can be provisioned in the network with BBP not greater than 1% which is a commonly acceptable threshold for BBP.