Abstract-With Network Function Virtualization (NFV), network functions are deployed as modular software components on the commodity hardware, and can be further chained to provide services, offering much greater flexibility and lower cost of the service deployment for the network operators. At the same time, replacing the network functions implemented in purpose built hardware with software modules poses a great challenge for the operator to maintain the same level of performance. The grade of service promised to the end users is formalized in the Service Level Agreement (SLA) that typically contains the QoS parameters, such as minimum guaranteed data rate, maximum end to end latency, port availability and packet loss. State of the art solutions can guarantee only data rate and latency requirements, while service availability, which is an important service differentiator is mostly neglected. This paper focuses on the placement of virtualized network functions, aiming to support service differentiation between the users, while minimizing the associated service deployment cost for the operator. Two QoS-aware placement strategies are presented, an optimal solution based on the Integer Linear Programming (ILP) problem formulation and an efficient heuristic to obtain near optimal solution. Considering a national core network case study, we show the cost overhead of availability-awareness, as well as the risk of SLA violation when availability constraint is neglected. We also compare the proposed function placement heuristic to the optimal solution in terms of cost efficiency and execution time, and demonstrate that it can provide a good estimation of the deployment cost in much shorter time.
Taking QoE requirement into account, authors in REF focus on VNF placement to support service differentiation among users, then present an Integer Linear Programming model (ILP) and a heuristic algorithm to minimize the associated SC deployment cost.
QoS-driven function placement reducing expenditures in NFV deployments
2017 IEEE International Conference on Communications (ICC)
2017 IEEE International Conference on Communications (ICC)
Computer Science