TY - BOOK ID - 14233102 TI - Submodularity in dynamics and control of networked systems AU - Clark, Andrew. AU - Alomair, Basel. AU - Bushnell, Linda. AU - Poovendran, Radha. PY - 2016 SN - 3319269755 3319269771 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Mechanical Engineering - General KW - Mechanical Engineering KW - Engineering & Applied Sciences KW - Submodular functions. KW - Computer networks. KW - Communication systems, Computer KW - Computer communication systems KW - Data networks, Computer KW - ECNs (Electronic communication networks) KW - Electronic communication networks KW - Networks, Computer KW - Teleprocessing networks KW - Functions, Submodular KW - Data transmission systems KW - Digital communications KW - Electronic systems KW - Information networks KW - Telecommunication KW - Cyberinfrastructure KW - Electronic data processing KW - Network computers KW - Matroids KW - Distributed processing KW - Systems theory. KW - Telecommunication. KW - Control and Systems Theory. KW - Systems Theory, Control. KW - Communications Engineering, Networks. KW - Electric communication KW - Mass communication KW - Telecom KW - Telecommunication industry KW - Telecommunications KW - Communication KW - Information theory KW - Telecommuting KW - Control engineering. KW - System theory. KW - Electrical engineering. KW - Electric engineering KW - Engineering KW - Systems, Theory of KW - Systems science KW - Science KW - Control engineering KW - Control equipment KW - Control theory KW - Engineering instruments KW - Automation KW - Programmable controllers KW - Philosophy UR - https://www.unicat.be/uniCat?func=search&query=sysid:14233102 AB - This book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllability with provable optimality bounds in static as well as time-varying networks. Throughout the text, the submodular framework is illustrated with the help of numerical examples and application-based case studies in biological, energy and vehicular systems. The book effectively combines two areas of growing interest, and will be especially useful for researchers in control theory, applied mathematics, networking or machine learning with experience in submodular optimization but who are less familiar with the problems and tools available for networked systems (or vice versa). It will also benefit graduate students, offering consistent terminology and notation that greatly reduces the initial effort associated with beginning a course of study in a new area. ER -