Research On Service Function Chain Deployment Under Wireless Network

Nowadays,unmanned platforms have been widely used in many fields,such as civil,military,industrial and so on.Especially in the military field,they have great application value.They can be used to perform tasks in dangerous environments.However,there are also some technical challenges.Firstly,unmanned platforms are required to load different functions quickly because of their changeable tasks.Secondly,unmanned platforms have high requirements for communication,and there are hidden dangers of information security.Thirdly,the limited carrying resources of platforms lead to a small number of tasks that can be performed.For the above three problems,there is no better solution to solve the above problems at the same time.In this thesis,container technology is used to deploy Docker with the advantages of fast deployment and low resource overhead.Combining with container deployment,this thesis designs related resource allocation/scheduling algorithm for different networking scenarios of unmanned platforms to minimize platform resource overhead.The main research contents are as follows:(1)For the dense MESH wireless network architecture,two nodes can be reached by one hop through the central node.However,the channel resources in the wireless network are limited,and the central node can not connect to all nodes at the same time.In order to ensure the normal operation of the service,real-time channel switching is needed.In this thesis,a wireless channel switching algorithm WCSA(Wireless Channel Switch A)is proposed to minimize the cost.Lgorithm,which realizes flexible switching between channels at minimum cost,ensures the smooth deployment of SFC(Service Function Chain).Secondly,aiming at the single base station MESH network architecture,this thesis proposes a single base station minimum cost SBGLC(Single Base Greedy Least Cost)deployment algorithm based on greedy idea.This algorithm combines WCSA to get the minimum cost deployment scheme on the premise of flexible deployment.Aiming at the multi-base station MESH network architecture,this thesis proposes a multi-base station genetic algorithm(Multiple Base Genetic Algorithms),which also realizes the flexible deployment of SFC by combining WCSA and uses genetic algorithm to optimize the deployment of SFC with the goal of minimizing the mapping cost.In addition,considering the scenario of actual traffic changes of unmanned platforms,this thesis discusses the bandwidth changes of virtual links,simulates the bandwidth changes of different trends and analyses the results.(2)For sparse wireless network architecture,in order to save platform overhead,this thesis proposes a clustering algorithm MMVAA(Max Min VNF Aggregation algorithm)based on minimizing the number of VNFs,which combines the SFC of the same source and destination nodes with the goal of minimizing the number of VNFs.Then,this thesis designs and implements a two-stage SFC deployment algorithm based on the idea of segmentation.In the first stage,we design an improved K-short-circuit algorithm based on genetic algorithm to get the set of alternative SFC mapping paths.This algorithm can get K alternative paths between the same source and destination nodes in a relatively short time.In the second stage,a greedy heuristic algorithm is designed to achieve the deployment of network functions with the goal of minimizing deployment costs.The simulation results show that the proposed algorithm performs better than the comparative algorithm in reducing the cost of deploying SFC,and the mapping success rate can also be guaranteed by adjusting K short circuit.