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The amount of stored data in enterprise Data Centers quadruples every
18 months. This trend presents a serious challenge for backup
management and sets new requirements for performance efficiency of
traditional backup and archival tools. In this work, we discuss
potential performance shortcomings of the existing backup
solutions. During a backup session a predefined set of objects (client
filesystems) should be backed up. Traditionally, no information on
the expected duration and throughput requirements of different backup
jobs is provided. This may lead to an inefficient job schedule and the
increased backup session time.
We analyze historic data on backup
processing from eight backup servers in HP Labs, and introduce two
additional metrics associated with each backup job, called job
duration and job throughput. Our goal is to use this additional
information for automated design of a backup schedule that minimizes
the overall completion time for a given set of backup jobs. This
problem can be formulated as a resource constrained scheduling problem
which is known to be NP-complete. Instead, we propose an efficient
heuristics for building an optimized job schedule, called FlexLBF.
The new job schedule provides a significant reduction in the backup
time (up to 50%) and reduced resource usage (up to 2-3
times). Moreover, we design a simulation-based tool that aims to
automate parameter tuning for avoiding manual configuration by system
administrators while helping them to achieve nearly optimal
performance.
Related Papers and Reports
- L. Cherkasova, R. Lau, H. Burose, S. V. Kalambur, B. Kappler, K. Veeranan: Run-time Performance Optimization and Job Management in a Data Protection Solution. Will appear in Proc. of the 11th IFIP/IEEE Symposium on Integrated Management
(IM'2011), Dublin, Ireland, May 23-27, 2011.
- L. Cherkasova, A. Zhang, X. Li: DP+IP = Design of
Efficient Backup Scheduling. Proc. of the 6th
International Conference on Network and Service Management (CNSM'2010), Niagara Falls, Canada, October 25-29, 2010.
- L. Cherkasova, R. Lau, H. Burose, B. Kappler:
Enhancing and Optimizing a Data Protection Solution.
Proc. of the 17th IEEE/ACM International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems
(MASCOTS'2009), London, UK, September 21-23, 2009. Nominee for Best Paper Award.
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