Scheduling real-time disk transfers for continuous media applications

Abstract

The authors study how continuous media data can be stored and accessed in the Swift distributed input/output (IO) architecture. They provide a scheme for scheduling real-time data transfers that satisfies the strict requirements of continuous-media applications. This scheme allows large data objects to be stored and retrieved concurrently from multiple disks to satisfy the high data rate requirements typical of real-time video and audio data. To do this, data transfer requests are split into smaller requests, which are then handled by the various components by Swift. On-line algorithms are studied that respond to a data request by promising to either satisfy or reject it. Each response must be made before the next request is seen by the algorithm. The authors discuss two different performance measures to evaluate such algorithms and show that no on-line algorithm can optimize these criteria to less than a constant fraction of the optimal. Finally, they propose an algorithm for handling such requests on-line and the related data structures.<>