In our work, we have proposed a new framework for the classification and comparative study of ATM congestion control schemes. The different aspects on which we have classified the algorithms are control theoretic approach, action and congestion notification. These three aspects present of the classification present a coherent framework on which congestion control algorithms are to be classified. Such a classification will also help in developing new algorithms.

In this thesis, a discrete Markov chain model for analyzing memory interference in multiprocessors, is presented.

The primary purpose of this work is to propose a new scheduling approach of multimedia data streams in real-time communication and also to study and analyze the various existing scheduling approaches.

Signal Correlation is a digital signal processing technique which has a wide variety of applications, ranging from geophysical exploration to acoustic signal enhancements, or beamforming. This dissertation will consider this technique in an underwater acoustics perspective, but the algorithms illustrated here can be readily applied to other areas. Although beamforming techniques have been studied for the past fifty years, modern beamforming systems still have difficulty in operating in noisy environments, especially in shallow water.

A powerful and efficient algorithm has been designed to deal with the critical timing problem of the MIDI messages. This algorithm can convert note events stored in a natural way to MIDI messages dynamically. Only limited memory space (the buffer) is required to finish the conversion work, and the size of the buffer is independent of the size of the original sequence (notes). This algorithm's real-time variable properties suggest not only the flexible real-time controls in the use of musical aspects, but also the expandability to interactive multi-media applications. A compositional environment called MusicSculptor has been implemented in terms of this algorithm.