Network monitoring is essential to tasks ranging from planning to troubleshooting. Unfortunately, comprehensive real-time monitoring of complex networks with large traffic volume is challenging. In particular, tracking of time-dependent metrics, such as round-trip latency or transmission rate requires maintaining state and this is hard to scale. We propose BloomTime: a network monitoring primitive in hardware that employs standard bloom filters to approximately track the times between packets. We have prototyped BloomTime on the NetFPGA platform. As a use case, we use BloomTime to monitor the mean and variance of packet inter-arrival times. We have compared BloomTime against end-host measurements and a centralized solution using classic stateful monitoring. We show that BloomTime can monitor 70 times more flows than the traditional stateful approach with approximation errors below 20%. BloomTime was validated in a realistic test environment using real traces. We show that BloomTime can monitor simultaneously 2000 flows on the NetFPGA 1G board (first generation) with 4 MB of SRAM.

网络监控对于从计划到故障排除的任务至关重要。不幸的是，对具有大流量的复杂网络进行全面的实时监视具有挑战性。特别是，跟踪与时间相关的度量（例如往返延迟或传输速率）需要维持状态，并且这很难扩展。我们提出BloomTime：硬件中的网络监视原语，它使用标准的Bloom过滤器来近似跟踪数据包之间的时间。我们已经在NetFPGA平台上建立了BloomTime的原型。作为一个用例，我们使用BloomTime监视数据包到达时间的均值和方差。我们已经比较了BloomTime针对终端主机的测量和使用经典状态监控的集中式解决方案。我们证明，BloomTime可以监视的流量比传统的有状态方法多70倍，且近似误差低于20％。BloomTime在真实的测试环境中使用真实的轨迹进行了验证。我们展示了BloomTime可以同时监视具有4 MB SRAM的NetFPGA 1G板（第一代）上的2000条流。