DiffPerf: 向SDN实现中性能差异化与优化迈进
DiffPerf: Towards Performance Differentiation and Optimization with SDN Implementation
AI总结：
DiffPerf通过SDN实现网络性能差异化与优化，动态分配带宽并隔离用户流以提升视频流媒体质量。
摘要：
继续当前趋势，互联网流量预计在未来几年内将显著增长，视频流量将占据最大份额。一方面，这种增长对接入提供商（APs）提出了挑战，他们必须升级基础设施以满足增长的流量需求，并找到新的方法来 monetize 网络资源。另一方面，尽管有众多底层传输协议的优化，用户的网络带宽利用情况以及因此用户的感知质量仍然主要受网络延迟和缓冲区大小的影响。为了解决这两个问题，我们提出了DiffPerf，一个基于类别的差异化框架，从宏观层面动态分配带宽给由APs预定义的服务类别，从微观层面统计上区分和隔离用户流以帮助它们实现更好的性能。我们将在OpenDaylight SDN控制器和可编程Barefoot Tofino交换机上实现DiffPerf，并从应用程序角度评估其在MPEG-DASH视频流媒体中的表现。我们的评估展示了DiffPerf为APs提供的实用性和灵活性，通过多种质量在多个类别中提供服务。同时，它有助于实现更好的公平性和提高同一类别内用户感知质量。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
