author	 = {Julian Kunkel and Eugen Betke},
	title	 = {{Tracking User-Perceived I/O Slowdown via Probing}},
	year	 = {2019},
	month	 = {12},
	booktitle	 = {{High Performance Computing: ISC High Performance 2019 International Workshops, Frankfurt/Main, Germany, June 16-20, 2019, Revised Selected Papers}},
	editor	 = {Michèle Weiland and Guido Juckeland and Sadaf Alam and Heike Jagode},
	publisher	 = {Springer},
	series	 = {Lecture Notes in Computer Science},
	number	 = {11887},
	pages	 = {169--182},
	conference	 = {HPC-IODC workshop, ISC HPC},
	location	 = {Frankfurt, Germany},
	isbn	 = {978-3-030-34356-9},
	issn	 = {1611-3349},
	doi	 = {},
	abstract	 = {The perceived I/O performance of a shared file system heavily depends on the usage pattern expressed by all concurrent jobs. From the perspective of a single user or job, the achieved I/O throughput can vary significantly due to activities conducted by other users or system services like RAID rebuilds. As these activities are hidden, users wonder about the cause of observed slowdown and may contact the service desk to report an unusual slow system. In this paper, we present a methodology to investigate and quantify the user-perceived slowdown which sheds light on the perceivable file system performance. This is achieved by deploying a monitoring system on a client node that constantly probes the performance of various data and metadata operations and then compute a slowdown factor. This information could be acquired and visualized in a timely fashion, informing the users about the expected slowdown. To evaluate the method, we deploy the monitoring on three data centers and explore the gathered data for up to a period of 60 days. A verification of the method is conducted by investigating the metrics while running the IO-500 benchmark. We conclude that this approach is able to reveal short-term and long-term interference.},
	url	 = {},