Dynamic partitioning of the cache hierarchy in shared data centres

Soundararajan, Gokul, Chen, Jin, Sharaf, Mohamed A. and Amza, Cristiana (2008). Dynamic partitioning of the cache hierarchy in shared data centres. In: Peter Buneman, Beng Chin Ooi, Kenneth Ross and Gerald Weber, Proceedings of the VLDB Endowment. 34th International Conference on Very Large Databases, Auckland, New Zealand, (635-646). 23-28 August 2008.

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Author Soundararajan, Gokul
Chen, Jin
Sharaf, Mohamed A.
Amza, Cristiana
Title of paper Dynamic partitioning of the cache hierarchy in shared data centres
Conference name 34th International Conference on Very Large Databases
Conference location Auckland, New Zealand
Conference dates 23-28 August 2008
Proceedings title Proceedings of the VLDB Endowment   Check publisher's open access policy
Journal name Proceedings of the VLDB Endowment   Check publisher's open access policy
Place of Publication New York, United States
Publisher ACM Digital Library
Publication Year 2008
Sub-type Fully published paper
Open Access Status
ISSN 2150-8097
Editor Peter Buneman
Beng Chin Ooi
Kenneth Ross
Gerald Weber
Volume 1
Issue 1
Start page 635
End page 646
Total pages 12
Language eng
Abstract/Summary Due to the imperative need to reduce the management costs of large data centers, operators multiplex several concurrent database applications on a server farm connected to shared network attached storage. Determining and enforcing per- application resource quotas in the resulting cache hierarchy, on the fly, poses a complex resource allocation problem spanning the database server and the storage server tiers. This problem is further complicated by the need to provide strict Quality of Service (QoS) guarantees to hosted applications. In this paper, we design and implement a novel coordinated partitioning technique of the database buer pool and storage cache between applications for any given cache replacement policy and per-application access pattern. We use statistical regression to dynamically determine the mapping between cache quota settings and the resulting per application QoS. A resource controller embedded within the database engine actuates the partitioning of the two-level cache, converging towards the conguration with maximum application utility, expressed as the service provider revenue in that conguration, based on a set of latency sample points. Our experimental evaluation, using the MySQL database engine, a server farm with consolidated storage, and two e-commerce benchmarks, shows the eectiveness of our technique in enforcing application QoS, as well as maximizing the revenue of the service provider in shared server farms.
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

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Created: Sun, 23 Oct 2011, 03:27:19 EST by Dr Mohamed Sharaf on behalf of School of Information Technol and Elec Engineering