Data Center's Performance Measurements and its Optimization Using Automated Workload Reports (AWRs) Under Cloud Environment

A. Poobalan, Dr.N. Uma Maheswari and K. Khaja Mohideen


Data centre is a term that decides the overall data needs of company and its environment. The Cloud Computing is the major support provider for data centre in modern multi-tenant requirements. The development in the data management forces us to support the data centers for efficient and effective handling of data under modern connectivity infrastructure environment. The developments in cloud computing paradigm confirm the need of faster and efficient performance evaluation facilities for Data centers and its management. The data centre should need enough resources such as storage capacity, managing software(s), additional capabilities such as optimization of storage, user requests. In a multi-tenant platform it demands rules and facilities on how we manage our data centre with operational management tasks. The advanced modeling of data does not feasible due to nature of data centre components such as different types of cloud servers, diversity of user requests, feasible storage capabilities in a multi-tenant province. We proposed a new mechanism to overcome these performance problems and to aim for optimize their performance; we can achieve this goal with help of queuing theory which directly deals the performance and its issues and gives solutions. In this paper, we proposed model called Multi-tenant Queue model focusing on the major performance metrics such as Transaction workload, internal response time, and effective utilization of resources. Calculation of Workload trace, on demand resource serving with no waiting time, a priori reserve of the resources in advance, no. of users as metrics considered for data performance under data centre. The performance measurements are facilitated with Automated Workload Reports (AWRs) with flow graphs under Oracle Performance and tuning makes use ADDT for optimization data storage and retrievals for data centers to provide a breed of computers (micro data centre) powered by a smart cloud intelligent systems.

Keywords: Data Centers, Cloud Computing, Multi-tenant, AWR, ADDT and Virtual Machine.

Volume: 5 | Issue: 1

Pages: 01-13

Paper ID : IJPPAS104900

Issue Date: February , 2017

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