论文标题

SFCAA:服务功能链作为NFV环境中的服务

SFCaaS: Service Function Chains as a Service in NFV Environments

论文作者

Moufakir, Tarik, Zhani, Mohamed Faten, Gherbi, Abdelouahed, Aloqaily, Moayad, Ghrada, Nadir

论文摘要

随着网络软件趋势的出现,预计互联网提供商提供的传统网络服务将通过充分利用新的新技术(例如网络功能虚拟化和软件定义的网络)来发展。 In this paper, we investigate offering Service Function Chains as a Service (SFCaaS) in NFV Environments. We first describe the potential business model to offer such a service.然后,我们对亚马逊EC2在位置,实例大小和性能方面提供的虚拟机实例的成本进行了详细研究,以指导服务链条提供和资源分配。之后,我们从SFC提供商的角度解决了服务链功能的资源分配问题,同时利用执行的成本研究。 We hence formulate the problem as an Integer Linear Program (ILP) aiming at reducing the SFC provider's operational costs of virtual machine instances and links as well as the synchronization costs among the instances.我们还提出了一种新的启发式算法,以考虑到对亚马逊EC2实例的成本进行的研究,以同样的目标进行了相同的目标解决映射问题。我们通过广泛的模拟表明,与受现有文献启发的基线算法相比,拟议的启发式方法可显着降低运营成本。

With the emergence of network softwarization trend, traditional networking services offered by Internet providers are expected to evolve by fully leveraging new recent technologies like network function virtualization and software defined networking. In this paper, we investigate offering Service Function Chains as a Service (SFCaaS) in NFV Environments. We first describe the potential business model to offer such a service. We then conduct a detailed study of the costs of virtual machine instances offered by Amazon EC2 with respect to the location, instance size, and performance in order to guide service chain provisioning and resource allocation. Afterwards, we address the resource allocation problem for service chain functions from the SFC provider's perspective while leveraging the performed cost study. We hence formulate the problem as an Integer Linear Program (ILP) aiming at reducing the SFC provider's operational costs of virtual machine instances and links as well as the synchronization costs among the instances. We also propose a new heuristic algorithm to solve the mapping problem with the same aforementioned goals taking into account the conducted study of the costs of Amazon EC2 instances. We show through extensive simulations that the proposed heuristic significantly reduce operational costs compared to a Baseline algorithm inspired by the existing literature.

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