VNE Solution for Network Differentiated QoS and Security Requirements: From the Perspective of Deep Reinforcement Learning

by   Chao Wang, et al.

The rapid development and deployment of network services has brought a series of challenges to researchers. On the one hand, the needs of Internet end users/applications reflect the characteristics of travel alienation, and they pursue different perspectives of service quality. On the other hand, with the explosive growth of information in the era of big data, a lot of private information is stored in the network. End users/applications naturally start to pay attention to network security. In order to solve the requirements of differentiated quality of service (QoS) and security, this paper proposes a virtual network embedding (VNE) algorithm based on deep reinforcement learning (DRL), aiming at the CPU, bandwidth, delay and security attributes of substrate network. DRL agent is trained in the network environment constructed by the above attributes. The purpose is to deduce the mapping probability of each substrate node and map the virtual node according to this probability. Finally, the breadth first strategy (BFS) is used to map the virtual links. In the experimental stage, the algorithm based on DRL is compared with other representative algorithms in three aspects: long term average revenue, long term revenue consumption ratio and acceptance rate. The results show that the algorithm proposed in this paper has achieved good experimental results, which proves that the algorithm can be effectively applied to solve the end user/application differentiated QoS and security requirements.


page 1

page 2

page 3

page 4


Security-Aware Virtual Network Embedding Algorithm based on Reinforcement Learning

Virtual network embedding (VNE) algorithm is always the key problem in n...

Network Resource Allocation Strategy Based on Deep Reinforcement Learning

The traditional Internet has encountered a bottleneck in allocating netw...

Space-Air-Ground Integrated Multi-domain Network Resource Orchestration based on Virtual Network Architecture: a DRL Method

Traditional ground wireless communication networks cannot provide high-q...

Isolation Scheme for Virtual Network Embedding Based on Reinforcement Learning for Smart City Vertical Industries

Modern ICT infrastructure is built on virtualization technologies, which...

Smart Scheduling based on Deep Reinforcement Learning for Cellular Networks

To improve the system performance towards the Shannon limit, advanced ra...

Resource Management and Security Scheme of ICPSs and IoT Based on VNE Algorithm

The development of Intelligent Cyber-Physical Systems (ICPSs) in virtual...

Learning Aided Auctioning for Opportunistic Scheduling in a Wireless Optical Network

This paper focusses on Service Level Agreement (SLA) based end-to-end Qu...

Please sign up or login with your details

Forgot password? Click here to reset