Queueing Dynamics and Optimization Issues in Parallel and Distributed Processing Systems

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In this project parallel and distributed processing systems will be studied from a queueing theoretic point of view, and related problems of dynamical optimization will be addressed. A fundamental understanding of how concurrency, coordination and scheduling issues, emerging at the level of basic operations, affect the macroscopic dynamics and performance of such systems will be acquired. General analysis techniques and systematic design principles will be identified. The design (synthesis) of efficient operational schemes will be addressed, for the optimization of parallel and distributed processing systems arising in computing and flexible manufacturing, with respect to criteria concerning throughput, delays buffer occupancies, lead balancing, fault-tolerance etc. Basic prototypical models, extracted from various practical processing situations in computing and manufacturing, will be studied in a unified framework, with emphasis on rigorous mathematical results and provable bounds. New queueing models will be developed to capture essential features of concurrency and coordination and allowing the systematic analysis of the dynamics and performance of processing protocols. Real-time scheduling and resource allocation schemes will be studied in a natural stochastic framework. In cases where the relevant optimal scheduling algorithms are of high complexity, the focus will be on exploring simple (low complexity) scheduling schemes. Other aspects of stochastic, dynamic scheduling will also be examined, if necessary by simulation. The research should develop an understanding of the dynamical aspects of parallel and distributed processing in computer systems and flexible manufacturing, at a fundamental mathematical level, and for establishing techniques to optimize performance, based on a solid mathematical methodology. The applied branch of this research will study specific practical systems that motivate the general models.