Abstract

A major design issue facing the designer of a distributed computing system involves the determination of the number of file copies and their locations in the distributed environment. This problem is commonly referred to as the file allocation problem (FAP). This paper considers two FAP models that seek to minimize operating costs (i.e., the total cost of file storage and query/update communication). The first model ensures the attainment of acceptable levels of communication delay during peak network traffic periods (worst-case scenario). The second model considers average communication delay. Unlike previous FAP research, the proposed models treat communication delay on a query-by-query basis, and not as a single, system-wide average delay constraint. For both models, a Lagrangian relaxation-based solution procedure is proposed for the resulting 0/1 integer programming problem. In the case of average delays, we utilize a hybrid model combining analytic and simulation procedures. The results of computational experiments with the proposed solution techniques are reported.

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