# VNF Placement Optimization at the Edge and Cloud +
## 6 Results and Discussions
### A Hybrid Simulation Approach  
Above, we evaluated the performance of the proposed VNF-PEC algorithms using a java-based simulator. A simulation-based evaluation introduces many benefits, especially in terms of cost and time execution of the experiments. However, using a purely simulated environment to evaluate the performance of such a complex system, where different and heterogeneous hardware and software components are merged together towards providing a flexible and efficient end-to-end networking solution from the things to the Cloud, can lead to a discrepancy in the results extracted under an emulation approach (e.g., using IoT, Edge, and Cloud testbeds). Even though this deviation in the results between a simulation-based and an emulation-based approach can be significant, in the particular work, we tried to create a realistic experimentation environment using real data from industrial use-cases and literature reviews to reduce the gap between these two testing methodologies. Furthermore, bearing in mind that we have to deal with mission critical IoT applications in which the delay is of utmost importance in the overall evaluation, we introduced a complete and thorough delay model to simulate the latency performance of our approaches. On the other hand, aiming to conduct real experiments for large-scale IoT, MEC, and Cloud research concepts comes with a high setup and implementation cost. For example, in order to reproduce our experimentation set-up, we would need hundreds of IoT devices, dozens of servers, dozens of different software packages and licenses, and an extremely high amount of time for configuring our hardware and software components, making a purely emulation approach impossible. Thus, inspired by the hybrid simulation approach proposed in [58], we design and propose a hybrid simulation alternative that can combine emulation and simulation together towards providing a more realistic evaluation. Figure 15 illustrates the design of a hybrid simulation/emulation approach for the VNF-PEC implementation. In the particular framework, the first step is to emulate our IoT platform. For this step, we envision the utilization of an IoT testbed, where we can deploy our IoT applications and gather statistics regarding their traffic characteristics. The data statistics will be stored as traffic profiles that we will load to our traffic generator, which will be used to emulate the IoT traffic. However, since we are assuming a dynamic traffic model, we will simulate the random inter-arrival and lifetime distribution of the IoT devices, which will constitute the input of our CVI-SIM simulator. The CVI-SIM will then accordingly update the traffic profile of the traffic generator (e.g., by adjusting the number of flows corresponding to the number of IoT devices associated with the IoT applications). Figure 14: Average CPU variance of activated servers. The infrastructure topology including the networking aspects of representing the Edge and Cloud will be simulated as typical network graphs, upon which the VNF placement will be performed. From this placement, we will extract offline statistics of the VNF-PEC evaluation like the total deployment cost, number of leased resources and routing decisions. In other words, the CVI-SIM will act as a controller with a complete knowledge of the underlying infrastructure and the status of the available resources. However, in this case, the intercommunication of the VNFs will be emulated by using two small-scale data centers to emulate the delay behavior of the placement solution. Specifically, as shown in Figure 15, we assume that we have an SC of five VNFs that is allocated in two servers at the Edge and another one at the Cloud. At the edge, two VNFs of the SC are allocated on the same server, while the third one at a different server. Finally, the rest two VNFs are allocated on a Cloud server.