Application of Inventory Management Principles for Efficient Data Placement in Storage Networks
The principles and strategies found in material management are comparable and analogue with the data management. This paper concentrates on the conversion of product inventory management principles into data inventory management principles. Efforts were made to enumerate various impacting parameters that would be appropriate to consider if any data inventory model could be plotted. The inventory models parameters are carefully tailored to fit in to the data management paradigm so as to match various distributed storage architectural systems. The basic function of storage management is to employ the storage resources efficiently so as to yield the maximum performance. Even though the storage medium is cheaper in cost that doesnt mean that addition or upgrading of the storage capacity alone can solve the problem of storing ever growing nature of data especially in the inter networked data centric applications. In such cases it is necessary to find a most fitting storage policy to bring out a significant improvement in the data retrieval performance. This paper emphasizes on the need for deriving generic principles for data inventory control that includes data inventory parameters which will be the base for proposing mathematical data inventory models.
Keywords: Data inventory management, Inventory models, Parameters, Storage networks, Data placement strategies, Data inventory model.
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ABOUT THE AUTHORS
Arokia Paul Rajan
R Arokia Paul Rajan is working as Associate Professor in Pope John Paul II College of Education, Pondicherry as well as a Ph.D Scholar in the Department of Computer Science & Engineering at Pondicherry Engineering College, Pondicherry, India. He completed M.C.A (1999) from Bharathidasan University, India.
Sagayaraj Francis
F Sagayaraj Francis is working as Associate Professor in the Department of Computer Science & Engineering at Pondicherry Engineering College, Pondicherry, India. He holds Ph.D in Data Management from Pondicherry University, Pondicherry, India. He authored 10 journal and 8 conference publications. Some of his areas of interest include Database Management Systems, Data Mining and Knowledge Discovery, Data Structures and Algorithms, Knowledge and Intelligent Systems and Automata Theory and Applications.
Arokia Paul Rajan
R Arokia Paul Rajan is working as Associate Professor in Pope John Paul II College of Education, Pondicherry as well as a Ph.D Scholar in the Department of Computer Science & Engineering at Pondicherry Engineering College, Pondicherry, India. He completed M.C.A (1999) from Bharathidasan University, India.
Sagayaraj Francis
F Sagayaraj Francis is working as Associate Professor in the Department of Computer Science & Engineering at Pondicherry Engineering College, Pondicherry, India. He holds Ph.D in Data Management from Pondicherry University, Pondicherry, India. He authored 10 journal and 8 conference publications. Some of his areas of interest include Database Management Systems, Data Mining and Knowledge Discovery, Data Structures and Algorithms, Knowledge and Intelligent Systems and Automata Theory and Applications.
