  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.
