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An interdisciplinary approach to understanding queueing andgraphical networks In today's era of interdisciplinary studies and researchactivities, network models are becoming increasingly important invarious areas where they have not regularly been used. Combiningtechniques from stochastic processes and graph theory to analyzethe behavior of networks, Fundamentals of StochasticNetworks provides an interdisciplinary approach by includingpractical applications of these stochastic networks in variousfields of study, from engineering and operations management tocommunications and the physical sciences. The author uniquely unites different types of stochastic,queueing, and graphical networks that are typically studiedindependently of each other. With balanced coverage, the book isorganized into three succinct parts: Part I introduces basic concepts in probability and stochasticprocesses, with coverage on counting, Poisson, renewal, and Markovprocesses Part II addresses basic queueing theory, with a focus onMarkovian queueing systems and also explores advanced queueingtheory, queueing networks, and approximations of queueingnetworks Part III focuses on graphical models, presenting an introductionto graph theory along with Bayesian, Boolean, and randomnetworks The author presents the material in a self-contained style thathelps readers apply the presented methods and techniques to scienceand engineering applications. Numerous practical examples are alsoprovided throughout, including all related mathematicaldetails. Featuring basic results without heavy emphasis on provingtheorems, Fundamentals of Stochastic Networks is a suitablebook for courses on probability and stochastic networks, stochasticnetwork calculus, and stochastic network optimization at theupper-undergraduate and graduate levels. The book also serves as areference for researchers and network professionals who would liketo learn more about the general principles of stochasticnetworks.