Reliability Assurance Dynamic SSC Placement Using Reinforcement Learning

Autor: Wei Li, Yuan Jiang, Xiaoliang Zhang, Fangfang Dang, Feng Gao, Haomin Wang, Qi Fan
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Information, Vol 13, Iss 2, p 53 (2022)
Druh dokumentu: article
ISSN: 2078-2489
DOI: 10.3390/info13020053
Popis: Software-defined networking (SDN) and network function virtualization (NFV) make a network programmable, resulting in a more flexible and agile network. An important and promising application for these two technologies is network security, where they can dynamically chain virtual security functions (VSFs), such as firewalls, intrusion detection systems, and intrusion prevention systems, and thus inspect, monitor, or filter traffic flows in cloud data center networks. In view of the strict delay constraints of security services and the high failure probability of VSFs, we propose the use of a security service chain (SSC) orchestration algorithm that is latency aware with reliability assurance (LARA). This algorithm includes an SSC orchestration module and VSF backup module. We first use a reinforcement learning (RL) based Q-learning algorithm to achieve efficient SSC orchestration and try to reduce the end-to-end delay of services. Then, we measure the importance of the physical nodes carrying the VSF instance and backup VSF according to the node importance of VSF. Extensive simulation results indicate that the LARA algorithm is more effective in reducing delay and ensuring reliability compared with other algorithms.
Databáze: Directory of Open Access Journals
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