# VNF Placement Optimization at the Edge and Cloud +
## 2 Related Work
In addition, the manipulated traffic can be bursty and can dynamically change during different time periods [38]. Hence, an appropriate load balancing scheme can easily facilitate any bursts and spikes of the incoming traffic. There are multiple benefits of this approach that include the avoidance of Service Level Agreement (SLA) violations and the need to utilize additional resources from the Cloud that have to cross a possible expensive transport network. In case that there are both Cloud and MEC resources available, an additional objective can be how to optimally offload and redirect traffic between the two layers [42]. This is particularly important for applications that generate a huge amount of data and an optimal decision needs to be made on where these data should be processed. Of course, the MEC layer may not have the necessary infrastructure to provide networking services for these huge amounts of traffic. Hence, a first decision can be performed in the MEC to determine in real time which traffic should be forwarded to the Cloud to apply the necessary VNFs [43]. The decision of which VNFs should be deployedto the Cloud is very important, since a continuous data transmission to the Cloud can cause cost, privacy, and data storage overheads [44]. Another important action comes when performing traffic offloading and load balancing at the same time. In this case, a vertical approach can be considered by appropriately offloading the wireless traffic to a set of cloudlets residing at the edge of the network [45]. To optimize traffic offloading, real-time VNF placement solutions should be devised. This way, traffic can be redirected on the fly according to the computational and communication requirements of the aggregated traffic stream. The objective function should reflect the dynamic nature of the streams and perform the VNF allocation wisely to efficiently offload the traffic to the Cloud respecting any location and latency requirements imposed by the IoT application. The above objectives entail different requirements and component goals that are usually conflicting, making the VNF-PEC a very challenging problem. For example, aiming to minimize deployment cost can lead to a consolidation of multiple VNFs on the same server. This can have an immense impact on the processing delay, which is roughly proportional to resource utilization. Similarly, the minimization of deployment cost can affect the load balancing objective by inefficiently utilizing the available resources. Another conflict can be generated when the traffic is offloaded to the Cloud. Either a cost and delay increase will be noticed, since the traffic now has to cross the expensive transport network adding a delay overhead to the overall communication. Load balancing and delay is another pair of conflicting objectives. Load balancing can dictate the VNF placement solution to utilize less loaded resources to equalize the average resource utilization. However, this can lead to placing parts of the same SCs in physical hosts that are very distant, increasing the overall propagation delay. These conflicts arise from the different requirements of the involved actors of this communication model. The infrastructure providers (either MEC or Cloud) want to efficiently utilize their resources by performing load balancing and VNF consolidation. Network service providers aim for a minimization of the total cost of providing their networking solutions to the end users, while the end users require a high QoS by experiencing low delays. Hence, in contrast with the research endeavours existing above, which consider only a subset of the total set of factors that can influence VNF-PEC performance, in this work, we target finding an optimal trade-off by jointly optimizing the total set of requirements and objectives. Furthermore, we consider SCs with different topological characteristics and traffic manipulation (e.g., compressed/decompressed traffic) that can influence the overall solution.