The main obstacle in mass adoption of cloud computing for database operations is the data security issue. In this paper, it is shown that IT services particularly in hardware performance evaluation invirtual machinecan be accomplished effectively without IT personnel gaining access to real data for diagnostic and remediation purposes. The proposed mechanisms utilizedTPC-Hbenchmark to achieve 2 objectives. First, the underlying hardware performance and consistency is supervised via a control system, which is constructed using a combination ofTPC-Hqueries,linear regression, andmachine learningtechniques. Second,linear programmingtechniques are employed to provide input to the algorithms that construct stress-testing scenarios in thevirtual machine, using the combination ofTPC-Hqueries. These stress-testing scenarios serve 2 purposes. They provide the boundary resource threshold verification to the first control system, so that periodic training of the synthetic data sets for performance evaluation is not constrained by hardware inadequacy, particularly when the resources in thevirtual machineare scaled up or down which results in the change of the utilization threshold. Secondly, they provide a platform for response time verification on critical transactions, so that the expected Quality of Service (QoS) from these transactions is assured.
Secure Hardware Performance Analysis in Virtualized Cloud Environment
