Emergent Mind

Performance Evaluation of the NDN Data Plane Using Statistical Model Checking

(1905.01607)
Published May 5, 2019 in cs.NI and cs.FL

Abstract

Named Data Networking (NDN) is an emerging technology for a future internet architecture that addresses weaknesses of the Internet Protocol (IP). Since Internet users and applications have demonstrated an ever-increasing need for high speed packet forwarding, research groups have investigated different designs and implementation for fast NDN data plane forwarders and claimed they were capable of achieving high throughput rates. However, the correctness of these statements is not supported by any verification technique or formal proof. In this paper, we propose using a formal model-based approach to overcome this issue. We consider the NDN-DPDK prototype implementation of a forwarder realized at NIST, which leverages concurrency to enhance overall quality of service. We use our approach to improve its design and to formally show that it can achieve high throughput rates.

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