fact that we model the behavior of YouTube and Netflix using FFserver, of World of Warcraft through Minecraft, or of Google Maps using OpenStreetMap. On the one hand, this might sound a bit bold. On the other hand, it is true that the problems faced by different applications of the same type – and the solutions thereto – tend to overlap. This explains, as an example, the existence of gaming [*engines*]{} such as Unity or Microsoft XNA, providing the developers of a heterogeneous set of games with homogeneous solutions to a small set of common problems.

In summary, our analysis provides valuable guidelines highlighting the existence of a mismatch between the quantity of traffic and the corresponding CPU load, as well as its magnitude. Additionally, the methodology we employ is general, and works unmodified in cases where additional traffic types and/or applications are taken into account, or if larger-scale experiments can be performed.

[**Dataset available.**]{} The results of our experiments are available for download from [@html].

MEC design {#sec:design}
==========

We now show how the enhanced dataset we created can be used to devise a MEC design strategy. Our input data are represented by:

-   a set of base stations;

