Traffic sampling has become an indispensable tool in network management. While there exists a plethora of sampling systems, they generally assume flow rates are stable and predictable over a sampling period. Consequently, when deployed in networks with dynamic flow rates, some flows may be missed or under-sampled, while others are over-sampled. This paper presents the design and evaluation of dSamp, a network-wide sampling system capable of handling dynamic flow rates in Software-Defined Networks (SDNs). The key idea in dSamp is to consider flow rate fluctuations when deciding on which network switches and at what rate to sample each flow. To this end, we develop a general model for sampling allocation with dynamic flow rates, and then design an efficient approximate integer linear program called APX that can be used to compute sampling allocations even in large-scale networks. To show the efficacy of dSamp for network monitoring, we have implemented APX and several existing solutions in ns-3 and conducted extensive experiments using model-driven as well as trace-driven simulations. Our results indicate that, by considering dynamic flow rates, APX outperforms the existing solutions by up to 10% in sampling more flows at a given sampling rate.

翻译：流量采样已成为网络管理中不可或缺的工具。尽管存在大量采样系统，但它们通常假设流率在采样周期内保持稳定且可预测。因此，当部署在具有动态流率的网络中时，某些流可能被遗漏或采样不足，而其他流则被过度采样。本文介绍了dSamp的设计与评估，这是一种能够处理软件定义网络（SDNs）中动态流率的全网范围采样系统。dSamp的核心思想是在决定由哪些网络交换机、以何种速率对每个流进行采样时，考虑流率的波动。为此，我们建立了一个针对动态流率的采样分配通用模型，并设计了一种名为APX的高效近似整数线性规划方法，该方法即使在大规模网络中也能用于计算采样分配。为了展示dSamp在网络监控中的有效性，我们在ns-3中实现了APX及多种现有解决方案，并利用模型驱动和轨迹驱动的仿真进行了大量实验。结果表明，通过考虑动态流率，APX在给定采样率下能够多采样高达10%的流，性能优于现有解决方案。