Costefficient virtual network function chaining over NFVbased telecommunications networks Network Function Visualization (NFV) enables the softwarization of network functions on standardized commodity hardware, which is promising to help the network carriers to achieve a lower investment cost, a shorter time to deployment, as well as a more flexible and dynamic way of network configuration and management. One of the key challenges is how to efficiently place and chain the softwarebased virtual network functions in the physical substrate to provision the requested network service while minimizing the physical network cost. In this paper, we mathematically formulate the virtual network function chaining problem using Integer Linear Programming (ILP), in order to facilitate an optimal solution. In addition, we propose a set of heuristic algorithms to efficiently solve this problem. The proposed Close To Destination (CTD) algorithm can achieve a nearoptimal physical network cost that is close to the optimal result obtained from the ILP solution, but with a very low computational complexity. Comprehensive simulations are conducted to evaluate the proposed approaches, and the results demonstrate the effectiveness of the proposed CTD algorithm.

Resource Optimization and TrafficAware VNF Placement in NFVEnabled Networks Although network function virtualization (NFV) is a promising approach for providing elastic network functions, it faces several challenges. A critical but difficult issue for the service and network providers is deciding where to instantiate a list of virtual network functions (VNFs), namely VNF placement problem. In this paper, we investigate the VNF placement, for the purpose of resource and network traffic consumption minimization. Moreover, we consider the arrival rates of usersu0027 requests for different types of service function chains (SFCs). This allows the placement scheme to adapt to usersu0027 timevarying requests and improve the network resource utilization. Then we formulate the VNF placement problem as a jointly constrained optimization problem. Afterwards, we propose an approach called joint optimization resource and traffic consumption (JORTC) with enhanced biogeographybased (EBBO) optimization algorithm to resolve the VNF placement problem. Finally, the evaluation results show the effectiveness of JORTC approach and performance advancement over the benchmarks.