No abstract

Network slicing is a vital component of the 5G system to support diverse network scenarios, creating virtual networks (slices) by mapping virtual network requests to real networks. The mapping is an arduous computing process, mathematically studied and known as the Virtual Network Embedding (VNE) problem, and its complexity is NP-Hard. The mapping process is oriented to respect the QoS demands from the virtual network requests and the available resources in the physical-substrate infrastructure. Meta-heuristic approaches are a suitable way to solve the VNE problems because of their capacity to escape from the local optimum and adapt the solution search to complex networks; these abilities are essential in 5G networks scenarios. This article presents a systematic review of meta-heuristics organized by application, development and problem-solving approaches to VNE. It also provides the standard parameters to model the infrastructure and virtual network requests to simulate network slicing as a service. Finally, our work proposes some future research based on the discovered gaps.

The 5G mobile network is based on a virtualized infrastructure and offers a virtual network (VN) creation service considering many new scenarios arising from the 5G vision. The diversity of scenarios and the instantiation of VN on-demand induce pressure on the virtual network embedding (VNE). VNE is the mapping of virtual nodes and links to real nodes and links obeying the QoS parameters present in the VN request and available resources. Since this is an optimization and NP-Hard problem, multiple efforts have been made to create VNE algorithms. Considering such efforts, this work presents: (i) a fitness function regarding multiobjective optimization; and (ii) a Parallel Differential Evolution (PDE) approach to face the VNE. We designed the PDE due to the lack of viable parallel solutions in the 5G scenario. We compared our approaches with different versions of Greedy, Stress, and Genetic Algorithms, totaling ten approaches. The results demonstrate that DE and its parallel version obtained a higher number of mapped requisitions. Also, the parallel performance decreases the execution time in certain conditions; in a favorable scenario, the parallel version obtains up 21.04% of runtime reduction.

Network slicing is a key component of the envisioned 5G network. Slices are virtual networks purpose-built for tenants using a shared infrastructure. The slicing process is mathematically known as a virtual network embedding problem (VNE). Despite the plethora of VNE strategies in the literature, they do not take into account the fact that massive data transmission can be carried in a certain period. Embedding a large number of virtual networks to a real physical network over time is an NP-Hard problem, and it becomes more complex because of new considerations such as periodicity, amount of data and duration. Thus, we propose the NS4MIoT, a solution to allocate slices resources for each tenant, allowing it to be aware of each transmission's periodicity, amount of data, and duration. NS4MIoT is an approach to increase the quantity of requisition mapped in an envisioned 5G network for IoT massive communication. To validate our solution, we incorporate it into two different embedding algorithms. Furthermore, we compare the same algorithms with and without the NS4MIoT approach, and the outcomes demonstrate an improvement in the mapping rate in all cases when it is incorporated.