# Fog vs. Cloud Computing: Should I Stay or Should I Go? +
## 5 Conclusions
Another interesting path is to not only consider the costs from the point of view of the device, but also to calculate the costs looking at the whole system in order to analyze the impact of employing fog computing in the applications that we are studying. Furthermore, we propose to implement a system that uses our model to choose between processing values in the fog or the cloud, and execute it on constrained devices. [PERSON] and [PERSON] conceived of and designed the models and experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] contributed materials/analysis tools; [PERSON] and [PERSON] wrote the article. The authors would like to thank CAPES (PROCAD 2966/2014), CNPq (140653/2017-1 and 313012/2017-2), and FAPESP (2013/08293-7) for their financial support. The authors would like to thank the Multidisciplinary High Performance Computing Lab for its infrastructure and contributions. The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results. \begin{table}
\begin{tabular}{l l l c c c c c c c c c c} \hline \hline
**Benchmark** & **Dataset** & \(\mathbf{t}\) (ms) & \(p\) (\%) & \(\mathbf{v}\) & \(\mathbf{n}\) & \(\mathbf{f}\) (Est.) & \(\mathbf{f}\) (Real) & **Slope (Est.)** & **Slope (Real)** & **Slope Error (\%)** \\ \hline \multirow{6}{*}{MinMax \([-15,15]\)} & HRelHumidity & 0.673551 & 0.001408 & 355 & 355 & 1.0000 & 1.0000 & \(-0.5201\) & \(-0.5201\) & \(-0.0000\) \\  & HVisibility & 0.614381 & 0.001284 & 389 & 0 & 0.0000 & 0.0000 & \(-1.1882\) & \(-1.1882\) & \(-0.0000\) \\  & HWBTempC & 0.629857 & 0.001317 & 379 & 210 & 0.5541 & 0.2784 & \(-0.7058\) & \(-0.8762\) & \(-19.4563\) \\  & HVindspeed & 0.619163 & 0.001294 & 386 & 7 & 0.0181 & 0.1393 & \(-1.1543\) & \(-1.0127\) & \(+13.9844\) \\  & Synthetic & 0.653126 & 0.001328 & 376 & 206 & 0.5429 & 0.5536 & \(-0.7053\) & \(-0.7024\) & \(+0.4010\) \\ \hline \multirow{6}{*}{MinMax \([-5,5]\)} & HRelHumidity & 0.673655 & 0.001408 & 355 & 355 & 1.0000 & 1.0000 & \(-0.5201\) & \(-0.5201\) & \(-0.0000\) \\  & HVisibility & 0.660127 & 0.001380 & 362 & 302 & 0.8343 & 0.8336 & \(-0.5752\) & \(-0.5754\) & \(-0.0392\) \\  & HVBtempC & 0.646680 & 0.001352 & 369 & 190 & 0.0000 & 0.6911 & \(-0.5303\) & \(-0.6341\) & \(-16.3797\) \\  & HVindspeed & 0.665631 & 0.001371 & 364 & 275 & 0.755 & 0.8013 & \(-0.6045\) & \(-0.5883\) & \(+2.7673\) \\  & Synthetic & 0.643882 & 0.001346 & 371 & 308 & 0.8030 & 0.8299 & \(-0.5840\) & \(-0.5841\) & \(-0.0189\) \\ \hline \multirow{6}{*}{Outlier 16} & HRelHumidity & 0.715757 & 0.001496 & 334 & 10 & 0.0299 & 0.0236 & \(-0.9897\) & \(-0.9959\) & \(-0.6239\) \\  & HVisibility & 0.66737 & 0.010395 & 385 & 43 & 0.1201 & 0.0911 & \(-0.9668\) & \(-0.9947\) & \(-2.8069\) \\  & HVBtempC & 0.723876 & 0.001513 & 330 & 5 & 0.0152 & 0.0222 & \(-0.9933\) & \(-0.9863\) & \(+0.7048\) \\  & HVindspeed & 0.719371 & 0.001504 & 302 & 10 & 0.0301 & 0.0267 & \(-0.9847\) & \(-0.9880\) & \(-0.3395\) \\  & Synthetic & 0.741199 & 0.001549 & 322 & 1 & 0.0031 & 0.0076 & \(-0.9819\) & \(-0.9775\) & \(+0.4442\) \\ \hline \multirow{6}{*}{Outlier 256} & HRelHumidity & 2.5970709 & 0.005415 & 92 & 0 & 0.0000 & 0.0051 & \(-0.2818\) & \(-0.2814\) & \(+0.1445\) \\  & HVisibility & 1.2791901 & 0.003614 & 138 & 0 & 0.3986 & 0.1112 & \(-0.3614\) & \(-0.4033\) & \(-0.3846\) \\ \cline{1-1}  & HVBtempC & 2.561749 & 0.005355 & 93 & 0 & 0.0000 & 0.0124 & \(-0.2850\) & \(-0.2840\) & \(+0.3539\) \\ \cline{1-1}  & HVindspeed & 2.454752 & 0.005131 & 97 & 0 & 0.0000 & 0.0160 & \(-0.2974\) & \(-0.2960\) & \(+0.4765\) \\ \cline{1-1}  & Synthetic & 2.633129 & 0.005504 & 90 & 1 & 0.0111 & 0.0012 & \(-0.2764\) & \(-0.2771\) & \(-0.2729\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Execution time results in cloud-prone cases.