论文标题
品脱：概率内带网络遥测
PINT: Probabilistic In-band Network Telemetry
论文作者
论文摘要
商品网络设备支持将带内遥测测量值添加到数据包中，从而实现了广泛的应用程序，包括网络故障排除，拥塞控制和路径跟踪。但是，包含有关数据包的信息会增加大量的开销，从而影响流程完成时间和应用程序级别的性能。 我们介绍了Pint，这是一个频段遥测框架，该框架将添加到每个数据包的信息量范围。 Pint在多个数据包上编码请求的数据，从而允许每包高达一位的限制。我们分析品脱和证明性能界限，包括同时多次查询的情况。 Pint在P4中实现，可以在网络设备上部署。使用真实的拓扑和流量特征，我们表明品脱同时启用了诸如拥塞控制，路径跟踪和计算尾部潜伏期之类的应用程序，每包仅使用16位，并且性能与最新的状态相当。
Commodity network devices support adding in-band telemetry measurements into data packets, enabling a wide range of applications, including network troubleshooting, congestion control, and path tracing. However, including such information on packets adds significant overhead that impacts both flow completion times and application-level performance. We introduce PINT, an in-band telemetry framework that bounds the amount of information added to each packet. PINT encodes the requested data on multiple packets, allowing per-packet overhead limits that can be as low as one bit. We analyze PINT and prove performance bounds, including cases when multiple queries are running simultaneously. PINT is implemented in P4 and can be deployed on network devices. Using real topologies and traffic characteristics, we show that PINT concurrently enables applications such as congestion control, path tracing, and computing tail latencies, using only sixteen bits per packet, with performance comparable to the state of the art.
