Techniques for Scheduling I/O in a High Performance Multimedia-on-Demand Server

One of the key components of a multi-user multimedia-on-demand system is the data server. Digitalization of traditionally analog data such as video and audio, and the feasibility of obtaining network bandwidths above the gigabit-per-second range are two important advances that have made possible the realization, in the near future, of interactive distributed multimedia systems. Secondary-to-main memory I/O technology has not kept pace with advances in networking, main memory and CPU processing power. Consequently, the performance of the server has a direct bearing on the overall performance of such a system. In this paper we present a high-performance solution to the I/O retrieval problem in a distributed multimedia system. We develop a model for the architecture of a server for such a system. Parallelism of data retrieval is achieved by striping the data across multiple disks. We present the algorithms for server operation when servicing a constant number of streams, as well as the admission control policy for accepting requests for new streams. The performance of any server ultimately depends on the data access patterns. Two modifications of the basic retrieval algorithm are presented to exploit data access patterns in order to improve system throughput and response time. Finally, we present preliminary performance results of these algorithms on the IBM SP1 and Intel Paragon parallel computers