DEPO

Abstract

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.