Title: Deconstructing the Tail at Scale Effect Across Network Protocols,
Abstract: Network latencies have become increasingly important for the performance of
web servers and cloud computing platforms. Identifying network-related tail
latencies and reasoning about their potential causes is especially important to
gauge application run-time in online data-intensive applications, where the
99th percentile latency of individual operations can significantly affect the
the overall latency of requests.
This paper deconstructs the "tail at scale" effect across TCP-IP, UDP-IP, and
RDMA network protocols. Prior scholarly works have analyzed tail latencies
caused by extrinsic network parameters like network congestion and flow
fairness. Contrary to existing literature, we identify surprising rare tails in
TCP-IP round-trip measurements that are as enormous as 110x higher than the
median latency. Our experimental design eliminates network congestion as a
tail-inducing factor. Moreover, we observe similar extreme tails in UDP-IP
packet exchanges, ruling out additional TCP-IP protocol operations as the root
cause of tail latency. However, we are unable to reproduce similar tail
latencies in RDMA packet exchanges, which leads us to conclude that the TCP/UDP
protocol stack within the operating system kernel is likely the primary source
of extreme latency tails.