Processing Networks: Fluid Models and Stability [Kietas viršelis]

'The deep and rich theory of stochastic processing networks has served as the analytical foundation for the study of communication networks, cloud computing systems, and manufacturing networks. This book by two of the pioneers of the theory presents an authoritative and comprehensive treatment of the topic, and will serve as an important reference to researchers in the area.' R. Srikant, University of Illinois at Urbana-Champaign 'A system of interconnected resources can become overloaded and unstable even though each of its individual resources has the capacity to meet the demands on it. This striking observation, first made thirty years ago, has stimulated a major field of research. This book, written by two of the pioneers and leading researchers in the field, is a clear and authoritative account of the state-of-the-art.' Frank Kelly, University of Cambridge 'This book provides an elegant and unified exposition of the general modeling framework of stochastic processing networks (SPNs) and associated theory of stability using fluid models. Much of this material was only previously available in dispersed journal articles. Adopting a continuous-time Markov chain description for SPNs, valid under fairly general assumptions on arrivals, service times and controls, enables a self-contained, accessible treatment. An array of interesting examples and extensions, especially involving applications for telecommunication and data networks, enliven the volume. This monograph will be an invaluable premier resource for graduate students and researchers in computer science, electrical and industrial engineering, applied mathematics and operations management interested in theory and applications of stochastic processing networks.' Ruth J. Williams, University of California, San Diego