As most computer systems are expected to remain operational 24 hours a day, 7 days a week, they must complete maintenance work while in operation. This work is in addition to the regular tasks of the system and its purpose is to improve system reliability and availability. Nonetheless, additional work in the system, although labeled as best effort or low priority, still affects the performance of foreground tasks, especially if background/foreground work is non-preemptive. In this paper, we propose an analytic model to evaluate the performance trade-offs of the amount of background work that a storage system can sustain. The proposed model results in a quasi-birth-death (QBD) process that is analytically tractable. Detailed experimentation using a variety of workloads shows that under dependent arrivals both foreground and background performance strongly depends on system load. In contrast, if arrivals of foreground jobs are independent, performance sensitivity to load is reduced. The model identifies dependence in the arrivals of foreground jobs as an important characteristic that controls the decision of how much background load the system can accept to maintain high availability and performance gains
Description
IEEE Xplore Abstract - Evaluating the Performability of Systems with Background Jobs
%0 Conference Paper
%1 zhang2006evaluating
%A Zhang, Qi
%A Mi, Ningfang
%A Smirni, E.
%A Riska, A
%A Riedel, E.
%B Dependable Systems and Networks, 2006. DSN 2006. International Conference on
%D 2006
%K availability dependability
%P 495-504
%R 10.1109/DSN.2006.33
%T Evaluating the Performability of Systems with Background Jobs
%U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1633538
%X As most computer systems are expected to remain operational 24 hours a day, 7 days a week, they must complete maintenance work while in operation. This work is in addition to the regular tasks of the system and its purpose is to improve system reliability and availability. Nonetheless, additional work in the system, although labeled as best effort or low priority, still affects the performance of foreground tasks, especially if background/foreground work is non-preemptive. In this paper, we propose an analytic model to evaluate the performance trade-offs of the amount of background work that a storage system can sustain. The proposed model results in a quasi-birth-death (QBD) process that is analytically tractable. Detailed experimentation using a variety of workloads shows that under dependent arrivals both foreground and background performance strongly depends on system load. In contrast, if arrivals of foreground jobs are independent, performance sensitivity to load is reduced. The model identifies dependence in the arrivals of foreground jobs as an important characteristic that controls the decision of how much background load the system can accept to maintain high availability and performance gains
@inproceedings{zhang2006evaluating,
abstract = {As most computer systems are expected to remain operational 24 hours a day, 7 days a week, they must complete maintenance work while in operation. This work is in addition to the regular tasks of the system and its purpose is to improve system reliability and availability. Nonetheless, additional work in the system, although labeled as best effort or low priority, still affects the performance of foreground tasks, especially if background/foreground work is non-preemptive. In this paper, we propose an analytic model to evaluate the performance trade-offs of the amount of background work that a storage system can sustain. The proposed model results in a quasi-birth-death (QBD) process that is analytically tractable. Detailed experimentation using a variety of workloads shows that under dependent arrivals both foreground and background performance strongly depends on system load. In contrast, if arrivals of foreground jobs are independent, performance sensitivity to load is reduced. The model identifies dependence in the arrivals of foreground jobs as an important characteristic that controls the decision of how much background load the system can accept to maintain high availability and performance gains},
added-at = {2014-08-28T15:29:35.000+0200},
author = {Zhang, Qi and Mi, Ningfang and Smirni, E. and Riska, A and Riedel, E.},
biburl = {https://www.bibsonomy.org/bibtex/29f832404d6e7a3b4be8119f47a3d87a2/avail_map_stud},
booktitle = {Dependable Systems and Networks, 2006. DSN 2006. International Conference on},
description = {IEEE Xplore Abstract - Evaluating the Performability of Systems with Background Jobs},
doi = {10.1109/DSN.2006.33},
interhash = {6ebab6236c55e2afb732818d10d3c2fa},
intrahash = {9f832404d6e7a3b4be8119f47a3d87a2},
keywords = {availability dependability},
month = {June},
pages = {495-504},
timestamp = {2014-08-28T15:57:46.000+0200},
title = {Evaluating the Performability of Systems with Background Jobs},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1633538},
year = 2006
}