Simulating Network Paths with Recurrent Buffering Units

• URL: http://arxiv.org/abs/2202.13870v1
• Date: Wed, 23 Feb 2022 16:46:31 GMT
• Title: Simulating Network Paths with Recurrent Buffering Units
• Authors: Divyam Anshumaan, Sriram Balasubramanian, Shubham Tiwari, Nagarajan Natarajan, Sundararajan Sellamanickam, Venkata N. Padmanabhan
• Abstract summary: We seek a model that generates end-to-end packet delay values in response to the time-varying load offered by a sender. We propose a novel grey-box approach to network simulation that embeds the semantics of physical network path in a new RNN-style architecture called Recurrent Buffering Unit.
• Score: 4.7590500506853415
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Simulating physical network paths (e.g., Internet) is a cornerstone research problem in the emerging sub-field of AI-for-networking. We seek a model that generates end-to-end packet delay values in response to the time-varying load offered by a sender, which is typically a function of the previously output delays. We formulate an ML problem at the intersection of dynamical systems, sequential decision making, and time-series generative modeling. We propose a novel grey-box approach to network simulation that embeds the semantics of physical network path in a new RNN-style architecture called Recurrent Buffering Unit, providing the interpretability of standard network simulator tools, the power of neural models, the efficiency of SGD-based techniques for learning, and yielding promising results on synthetic and real-world network traces.

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