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Authors
Affiliations
1 Department of Electrical Engineering and Computer Science, Vanderbilt University, IN
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 6, No 2 (2014), Pagination: 1-19
Abstract
Reliability of a performance model is quintessential to the robust resource management of applications on the cloud platform. Existing studies show that the contention for shared I/O induces temporal performance variations in a guest VM and heterogeneity in the underlying hardware leads to relative performance difference between guest VMs of the same abstract type. In this work, we demonstrate that a guest VM exhibits significant performance variations across repeated runs in spite of contention free hosting of a single guest VM on a physical machine. Also, notable performance difference between guest VMs created equal on physical machines of a homogeneous cluster is noticed. Systematic examination of the components involved in the request processing identifies disk I/O as the source of variations. Further investigation establishes that the ischolar_main cause of the variations is linked with how MySQL manages the storage of tables and indexes on the guest VM's disk file system. The observed variations in performance raise the challenge of creating a consistent and repeatable profile. To this end, we present and evaluate a black box approach based on database population from a snapshot to reduce the perceived performance variations. The experimental results show that the profile created for a database populated using a snapshot can be used for performance modeling up to 80% CPU utilization. We validate our findings on the Amazon EC2 cloud platform.
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