Abstract
This paper proposes a framework named Dynamic Access and Integration Services (DAIS) framework. The framework provides on-demand and large scale integrated data access in cloud computing environment. The sole motivation of this research paper is to enhance the performance of Cloud-Oriented Storage (COS) systems. DAIS framework consists of two basic modules namely (1) Adjacency COS Overlay Topology (ACOT) and (2) Cloud Storage Resource Discovery (CSRD). ACOT introduces a self-organizing well balanced m-way tree which removes the necessity of centralized approaches and adopts dynamic and scalable data access in cloud computing environment. CSRD module provides data integration mechanism and efficient resource discovery from geographically distributes COS systems. In this paper, Hadoop test-bed setup has been deployed for experiment and results analysis. All input and output data have been collected in the Hadoop Distributed File System (HDFS). In the experiments, performance, bandwidth and energy efficiency of the proposed DAIS framework have been demonstrated and compared with three different approaches like, Static DAIS, P2P and DSSM. To make it energy efficient, measurement unit and its mathematical model have been defined. Energy efficiency results have been compared with two popular approaches HBase and Hadoop-MR, and found better in most of the cases.
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