Parallel and Distributed Computing and Networks

How East German artists made their country’s experimental art scene a form of (counter) public life.Experimental artists in the final years of the German Democratic Republic did not practice their art in the shadows, on the margins, hiding away from the Stasi’s prying eyes. In fact, as Sara Blaylock shows, many cultivated a critical influence over the very bureaucracies meant to keep them in line, undermining state authority through forthright rather than covert projects. In Parallel Public, Blaylock describes how some East German artists made their country’s experimental art scene a form of (counter) public life, creating an alternative to the crumbling collective underpinnings of the state. Blaylock examines the work of artists who used body-based practices―including performance, film, and photography―to create new vocabularies of representation, sharing their projects through independent networks of dissemination and display. From the collective films and fashion shows

Applications of queueing network models have multiplied in the last generation, including scheduling of large manufacturing systems, control of patient flow in health systems, load balancing in cloud computing, and matching in ride sharing. These problems are too large and complex for exact solution, but their scale allows approximation. This book is the first comprehensive treatment of fluid scaling, diffusion scaling, and many-server scaling in a single text presented at a level suitable for graduate students. Fluid scaling is used to verify stability, in particular treating max weight policies, and to study optimal control of transient queueing networks. Diffusion scaling is used to control systems in balanced heavy traffic, by solving for optimal scheduling, admission control, and routing in Brownian networks. Many-server scaling is studied in the quality and efficiency driven Halfin–Whitt regime and applied to load balancing in the supermarket model and to bipartite matching in ri

Applications of queueing network models have multiplied in the last generation, including scheduling of large manufacturing systems, control of patient flow in health systems, load balancing in cloud computing, and matching in ride sharing. These problems are too large and complex for exact solution, but their scale allows approximation. This book is the first comprehensive treatment of fluid scaling, diffusion scaling, and many-server scaling in a single text presented at a level suitable for graduate students. Fluid scaling is used to verify stability, in particular treating max weight policies, and to study optimal control of transient queueing networks. Diffusion scaling is used to control systems in balanced heavy traffic, by solving for optimal scheduling, admission control, and routing in Brownian networks. Many-server scaling is studied in the quality and efficiency driven Halfin–Whitt regime and applied to load balancing in the supermarket model and to bipartite matching in ri