USENIX 2004 Annual Technical Conference, General Track Abstract
Pp. 8798 of the Proceedings
Monkey See, Monkey Do: A Tool for TCP Tracing and Replaying
Yu-Chung Cheng, University of California, San Diego; Urs Hölzle and Neal Cardwell, Google; Stefan
Savage and Geoffrey M. Voelker, University of California, San Diego
The performance of popular Internet Web services is governed by a
complex combination of server behavior, network characteristics and client
workload - all interacting through the actions of
the underlying transport control protocol (TCP). Consequently, even
small changes to TCP or to the network infrastructure can have
significant impact on end-to-end performance, yet at the same time it
is challenging for service administrators to predict what that impact
will be. In this paper we describe the implementation of a tool
called Monkey that is designed to help address such questions.
Monkey collects live TCP trace data near a server, distills key
aspects of each connection (e.g., network delay, bottleneck bandwidth,
server delays, etc) and then is able to faithfully replay the client
workload in a new setting. Using Monkey, one can easily evaluate the
effects of different network implementations or protocol optimizations
in a controlled fashion, without the limitations of synthetic
workloads or the lack of reproducibility of live user traffic. Using
realistic network traces from the Google search site, we show
that Monkey is able to replay traces with a high degree of accuracy
and can be used to predict the impact of changes to the TCP stack.
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