DiffPerf: Towards Performance Differentiation and Optimization with SDN Implementation

Walid Aljoby, Xin Wang, Dinil Mon Divakaran, Tom Z. J. Fu, Richard T. B. Ma

Continuing the current trend, Internet traffic is expected to grow significantly over the coming years, with video traffic consuming the biggest share. On the one hand, this growth poses challenges to access providers (APs), who have to upgrade their infrastructure to meet the growing traffic demands as well as find new ways to monetize their network resources. On the other hand, despite numerous optimizations of the underlying transport protocol, a user's utilization of network bandwidth and is thus the user's perceived quality still being largely affected by network latency and buffer size. To address both concerns, we propose DiffPerf, a class-based differentiation framework, that, at a macroscopic level dynamically allocates bandwidth to service classes pre-defined by the APs, and at a microscopic level statistically differentiates and isolates user flows to help them achieve better performance. We implement DiffPerf on OpenDaylight SDN controller and programmable Barefoot Tofino switch and evaluate it from an application perspective for MPEG-DASH video streaming. Our evaluations demonstrate the practicality and flexibility that DiffPerf provides APs with capabilities through which a spectrum of qualities are provisioned at multiple classes. Meanwhile, it assists in achieving better fairness and improving overall user's perceived quality within the same class.

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