How to Measure the Killer Microsecond

Datacenter-networking research requires tools to both generate traffic and accurately measure latency and throughput. While hardware-based tools have long existed commercially, they are primarily used to validate ASICs and lack flexibility, e.g. to study new protocols. They are also too expensive for academics. The recent development of kernel-bypass networking and advanced NIC features such as hardware timestamping have created new opportunities for accurate latency measurements. This paper compares these two approaches, and in particular whether commodity servers and NICs, when properly configured, can measure the latency distributions as precisely as specialized hardware. Our work shows that well-designed commodity solutions can capture subtle differences in the tail latency of stateless UDP traffic. We use hardware devices as the ground truth, both to measure latency and to forward traffic. We compare the ground truth with observations that combine five latency-measuring clients and five different port forwarding solutions and configurations. State-of-the-art software such as MoonGen that uses NIC hardware timestamping provides sufficient visibility into tail latencies to study the effect of subtle operating system configuration changes. We also observe that the kernel-bypass-based TRex software, that only relies on the CPU to timestamp traffic, can also provide solid results when NIC timestamps are not available for a particular protocol or device

Tuning the aggressive TCP behavior for highly concurrent HTTP connections in intra-datacenter

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.IEEE Modern data centers host diverse hyper text transfer protocol (HTTP)-based services, which employ persistent transmission control protocol (TCP) connections to send HTTP requests and responses. However, the ON/OFF pattern of HTTP traffic disturbs the increase of TCP congestion window, potentially triggering packet loss at the beginning of ON period. Furthermore, the transmission performance becomes worse due to severe congestion in the concurrent transfer of HTTP response. In this paper, we provide the first extensive study to investigate the root cause of performance degradation of highly concurrent HTTP connections in data center network. We further present the design and implementation of TCP-TRIM, which employs probe packets to smooth the aggressive increase of congestion window in persistent TCP connection and leverages congestion detection and control at end-host to limit the growth of switch queue length under highly concurrent TCP connections. The experimental results of at-scale simulations and real implementations demonstrate that TCP-TRIM reduces the completion time of HTTP response by up to 80 & #x0025;, while introducing little deployment overhead only at the end hosts.This work is supported by the National Natural Science Foundation of China (61572530, 61502539, 61402541, 61462007 and 61420106009)