HEURISTIC BASED ALGORITHM FOR SFC ALLOCATION IN 5G EXPERIENCE APPLICATIONS

In this paper, a cost-effective model for service function chain (SFC) placement used in analyzed based applications has been proposed. In the allocation of computation resources, history of executed and recently released SFs has been considered. In this regards, SFs are optimally executed in a virtualized network on the computing nodes with available resources. The placement issue has been propounded as a constrained optimization problem. To solve this problem a heuristic solution based on genetic algorithm is used. To evaluate and compare the performance of the proposed model, an evaluation scenario for video surveillance use case has been followed and compared by other algorithms. Numerical results shows that the proposed model can remarkably decrease the costs in terms of energy and resources by considering history of computation resources used in a cloud environment.