基于通用多协议标签交换的云计算虚拟化

Rajat Saxena, Ajay Patel
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引用次数: 0

摘要

广义多协议标签交换(GMPLS)或多协议Lambda交换是在MPLS (Multi-Protocol Label Switching)中产生放大以支持网络交换、空间交换和分组交换的一种新技术。因此,我们可以说GMPLS是MPLS的扩展,它通过自动交换提供弹性和恢复。在本文中,我们提供了一个基于Docker的仿真环境,该环境模拟了一个复杂的网络,并创建了GMPLS的洞察力功能。基于Docker的模拟环境是轻量级和可扩展的。它以最小的规格模拟大型复杂网络。我们已经测试了这个基于Docker的GMPLS模拟测试平台,它依赖于扩展的网络资源。与其他虚拟化方法相比,我们的方法显示出了巨大的改进。在本文中,我们基于UML、Virtual Box和Docker进行了比较研究,发现与UML和Virtual Box相比,Docker消耗的资源非常少。在1 TB硬盘空间和16 GB RAM的系统中,我们可以使用Virtual Box设计和研究30-40个节点的拓扑结构,使用UML设计和研究10-15个节点的拓扑结构。然而,使用Docker可以设计和测试包含300个节点的拓扑。因此,可伸缩性受到系统规范的限制。
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Generalized Multi-protocol Label Switching based Virtualization for Cloud Computing
Generalized Multi Protocol Label Switching (GMPLS) or Multi-Protocol Lambda Switching is a new technology which produce amplification in Multi Protocol Label Switching (MPLS) to provide support network switching, space switching, and packet switching for time and wavelength. Thus, we can say that GMPLS is extension of MPLS which provides resilience and restoration by automatic switching. In this paper, we provide a Docker based simu-1ation environment which emulates a complex network and create insight functioning of GMPLS. The Docker based simulation environment is light-weight and scalable. It emulates large and complex network with minimal specifications. We have tested this Docker based GMPLS simulation testbed that depends on scaled network resources. Our method has shown tremendous improvement over the other virtualization methods. In this paper, we do a comparative study based on UML, Virtual Box, and Docker and found that Docker consumes very less resources when compared to UML and Virtual Box. In a system with 1 TB Hard disk space and 16 GB RAM, we can design and study a topology with 30–40 nodes using Virtual Box and a topology with 10–15 nodes using UML. Whereas, with Docker a topology with 300-nodes can be designed and tested. Thus scalability is limited by system specifications.
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