Trace-driven replayers provide a flexible and convenient way to evaluate or debug target systems. Previous researchers focused on the individual impact of either the network or the storage system on overall system performance by using trace-driven replayers. However, as big data and cloud servers become prevalent and the performance gap between storage and networks decreases substantially, it becomes important to consider both impacts of storage and network on target systems. In this paper, we build a replayer called NetStorage to replay the captured traces of both network and storage to evaluate the performance of combined network-storage systems. When involving multiple replayers, the synchronization between these replayers becomes crucial. We introduce a manager component to control the synchronization between replayers. By doing that, the NetStorage is capable of efficiently replaying multiple traces synchronously in order to mimic the real application behavior in network and storage environments for different scenarios. Finally, a case study is provided to compare performance of two systems by using the NetStorage.
Bibliographical noteFunding Information:
This work was supported in part by the Center for Research in Intelligent Storage (CRIS), United States , which is supported by National Science Foundation, United States Grant No. IIP-1439622 and member companies. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.
© 2018 Elsevier B.V.
Copyright 2019 Elsevier B.V., All rights reserved.
- Network-storage system
- Performance evaluation
- Trace-driven replayer