A cost oriented algorithm for data set allocation in storage hierarchies
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.