Research On Deployment And Scheduling Of Service Function Components Based On Security Cloud

With the accelerated pace of enterprise digital transformation,traditional security measures are no longer enough to meet the needs of security protection in the complex and changeable network environment.How to provide tenants with efficient,stable and reliable security protection services to meet the needs of security protection has beco me the research focus of the current security industry.Security service chain(SSC)combines various types of security service function components(VSF)in the security resource pool by using programmable technologies such as NFV technology,SDN technology and automated traffic traction technology[1]to form an orderly security service chain to meet security requests,providing an effective breakthrough for solving the above problems.The core of using SSC to provide security services lies in SSC orchestration,service component deployment and service component scheduling.In a secure cloud environment,the reliability of virtual service functional components is relatively low,while the security services have high requirements on delay and reliability.This paper proposes a low-delay and reliability guaranteed service functional component deployment algorithm based on Q-Learning.The algorithm can be divided into two phases:VSF mapping and VSF backup.Firstly,based on Q-Learning algorithm of reinforcement Learning,appropriate VSF placement nodes are calculated and selected by Q matrix to realize efficient VSF deployment,reduce end-to-end delay of service and ensure service quality.Then,by quantifying the importance of VSFS deployed nodes,the VSFS with high importance are backed up to improve the cost effectiveness of backup resources.Aiming at the problem of how to dynamically schedule the security service chain to ensure the continuous and reliable supply of security services when security requirements change or service nodes are abnormal,this paper proposes a service function component scheduling method based on immune genetic algorithm.Firstly,a service component scheduling model based on immune genetic algorithm was established,and the main optimization objectives of service function component scheduling were defined,including service time,service function component consumption and service feedback.Then,based on this model,a mathematical model of service functional component scheduling task is established,and a hybrid algorithm model based on genetic algorithm and immune algorithm is proposed to solve the problem of service functional component scheduling.In this paper,the rationality of the above algorithm scheme is verified by reasonable simulation experiments,and the effectiveness and innovation of the algorithm proposed in this paper is further proved by comparing with a variety of algorithms,which improves the security service quality of the security service chain and the reliability of the security service supply,and then provides an effective scheme to solve the new security protection needs generated in the process of enterprise digital transformation.