编配
计算机科学
连锁
背景(考古学)
领域(数学分析)
分布式计算
服务(商务)
网络拓扑
功能(生物学)
网络功能虚拟化
计算机网络
私人信息检索
计算机安全
云计算
操作系统
古生物学
心理学
音乐剧
心理治疗师
经济
视觉艺术
艺术
经济
数学分析
数学
生物
进化生物学
作者
Kalpana D. Joshi,Kotaro Kataoka
标识
DOI:10.1016/j.comnet.2020.107295
摘要
Service Function Chaining (SFC) has become an integral part of every emerging application to satisfy its specific demand. Due to the massive increase in such diverse applications, there is a need for an efficient solution for flexible SFC orchestration. In this context, deploying SFC across domains can be a promising way to provide the required network services through cost-effective resource utilization. However, the operation of Multi-Domain SFC (MD-SFC) mainly has a trade-off between privacy and performance. While sharing the detailed network information, such as topology and resource availability, is important for the efficient MD-SFC orchestration, the network operators are not willing to disclose such private and detailed network information about the domain network. As a result, there is always a higher demand for privacy preservation while employing efficient MD-SFC orchestration. In this paper, we present pSMART, a lightweight, privacy-aware service function chain orchestration in a multi-domain NFV/SDN scenario. The main purpose of pSMART is to utilize less sensitive information, to reduce privacy and security risks, and to employ learning based decision making for efficient MD-SFC mapping. We quantify and analyse the gain of the proposed pSMART approach in terms of privacy-preservation and response time. The simulation results show that the proposed pSMART approach achieves a higher level of privacy and optimizes the response time of MD-SFC orchestration.
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