DEPO

Aisha Syed, Bilal Anwer, V. Gopalakrishnan, Jacobus Van Der Merwe
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引用次数: 6

摘要

网络功能虚拟化(NFV)和软件定义网络(SDN)的出现使得网络被实现为软件定义基础设施(sdi)。sdi提供的动态性和灵活性为确保政策变化不会导致意想不到的后果带来了新的挑战。这些问题的范围从基本网络不变量的破坏到网络性能的降低。我们提出了D框架,它支持自动发现和量化新的编排和服务级别SDI策略的潜在影响。我们的方法在沙箱SDI中结合了知识建模、数据分析、机器学习和仿真技术。我们通过在带有4G LTE/EPC宽带服务的SDI测试平台上对其进行评估来演示我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DEPO
The emergence of network functions virtualization (NFV) and software defined networking (SDN) has resulted in networks being realized as software defined infrastructures (SDIs). The dynamicity and flexibility o ered by SDIs introduces new challenges in ensuring that policy changes do not result in unintended consequences. These can range from the breakdown of basic network invariants to degradation of network performance. We present the D framework that enables automated discovery and quantification of the potential impact of new orchestration and service level SDI policies. Our approach uses a combination of knowledge modeling, data analysis, machine learning, and emulation techniques in a sandbox SDI. We demonstrate our approach by evaluating it over a testbed SDI with a 4G LTE/EPC broadband service.
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