A Cost Oriented Algorithm for Data Set Allocation in Storage Hierarchies.

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Bibliographic Details
Title:	A Cost Oriented Algorithm for Data Set Allocation in Storage Hierarchies.
Authors:	Lum, V. Y.¹, Senko, M. E.¹, Wang, C. P.¹, Ling, H.¹
Source:	Communications of the ACM. Jun75, Vol. 18 Issue 6, p318-322. 5p. 3 Charts.
Subjects:	Information storage & retrieval systems, Dynamic storage allocation (Computer science), Cost control, Databases, Decision making, Computer programming, Electronic information resources, Algorithms
Abstract:	Data set allocation in today's multilevel storage systems is usually based on qualitative, ad hoc decisions. While it would be desirable to obtain an optimal solution to this allocation problem, it is clear that the number of parameters involved makes it intractable to straight-forward solution. In such a situation, we must find a set of assumptions which simplify the problem greatly, but which still provide a basis for considering all significant cost elements. This paper presents such a first, quantitative allocation step. It considers many of the significant detailed costs of system utilization, data storage, data staging, and data migration. Although many avenues of further improvement are available, the present algorithm seems to be usefully accurate. As such, it can aid in quantifying the problems of data set allocation, storage system configuration, and new device designs. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Data set allocation in today's multilevel storage systems is usually based on qualitative, ad hoc decisions. While it would be desirable to obtain an optimal solution to this allocation problem, it is clear that the number of parameters involved makes it intractable to straight-forward solution. In such a situation, we must find a set of assumptions which simplify the problem greatly, but which still provide a basis for considering all significant cost elements. This paper presents such a first, quantitative allocation step. It considers many of the significant detailed costs of system utilization, data storage, data staging, and data migration. Although many avenues of further improvement are available, the present algorithm seems to be usefully accurate. As such, it can aid in quantifying the problems of data set allocation, storage system configuration, and new device designs. [ABSTRACT FROM AUTHOR]
ISSN:	00010782
DOI:	10.1145/360825.360843