Energy-efficient Research Of Service Function Chain Mapping

In recent years,the rapid development and improvement of network technology has led to an increasing demand for network functions.Due to the rapid spread of applications such as online video,network traffic has shown an explosive growth trend.In order to meet people's requirements for network service quality,telecom operators need to constantly perform network updates and capacity expansion.Network Function Virtualization(NFV)is a new concept that decouples some of the specialized equipment hardware and software of telecommunication services and uses software and general equipment to handle business functions.On the basis of satisfying the traditional business requirements,reducing the difficulty of network expansion and improving the utilization of hardware equipment will also be an important research direction of the network in recent years.This thesis focuses on how to achieve energy-saving optimization by adjusting the deployment of service flows in networks using NFV technology.In a network using NFV technology,a series of function point connections is called a service function chain.Under the premise of satisfying the service quality,researching the service deployment plan that can improve the efficiency of network resources utilization has important significance for energy saving optimization.In the third chapter of this thesis,based on the dynamic service flow scenario,an integer linear programming model is established for the deployment of a single SFC,and the corresponding heuristic algorithm is basically designed.Based on the third chapter,with the continuous changes of the network,we can further realize network energy saving by adjusting the positions of certain SFC deployments.In chapter four,the SFC re-deployed integer linear programming model and heuristic algorithm are designed for this problem,and the network's receiving rate and energy consumption are improved.Finally,since the SFC redeployment model in the fourth chapter does not involve cost constraints,the fifth chapter adds the SFC node constraint conditions for redeployment.This chapter modifies the redeployment mathematical model and designs a heuristic algorithm.The algorithm effectively guarantees the service quality on the basis of energy conservation and energy consumption.Through simulation experiments,it can be seen that the SFC mapping algorithm is 4.79 percentage points lower than the theoretical optimal solution.The SFC redeployment algorithm can improve the network reception rate and reduce energy consumption.Considering the redeployment of restricted constraints on nodes,the same network optimization can be achieved.