As of 2014, 54% of the earth’s population resides in urban areas, a percentage expected to reach 66% by 2050. This increase would amount to 2.5B people added to urban populations. At the same time, there are now 28 mega-cities (with 10M people) worldwide, accounting for 22% of the world’s urban population, and projections indicate […]
Control and optimization of Stochastic Hybrid Systems (SHS) constitute increasingly active fields of research. Perturbation Analysis (PA) techniques have proven to be particularly useful for SHS, since the size and complexity of such systems frequently render the use of exhaustive verification techniques prohibitive. This book focuses on applying PA to two different problems: Traffic Light Control (TLC) and control of cancer progression, both of which are viewed as dynamic optimization problems in a SHS environment. The TLC problem for a single intersection is modeled as a SHS, for which a quasi-dynamic control policy is proposed based on partial state information defined by detecting whether vehicle backlogs are above or below certain controllable threshold values. The problem of controlling cancer progression is formulated within a Stochastic Hybrid Automaton framework, and an integrative closed-loop framework is proposed for describing the progressive development of cancer and determining optimal personalized therapies. The insights provided by this book should be useful to researchers in the field of SHS and more generally to those interested in cutting-edge optimization solutions.
Energy-Latency Trade-Offs in Real-Time Wireless Sensor Networks Lei Mia and Christos G. Cassandras We study the optimal control of a class of resource allocation problems characterized by energy-latency trade-offs in Wireless Sensor Networks (WSN) using the framework of Discrete Event Systems. Our work is based on the observation that energy of wireless nodes can be […]
The rapid evolution of computing, communication, and sensor technologies has brought about the proliferation of “new” dynamic systems, mostly technological and often highly complex. Examples are all around us: computer and communication networks; automated manufacturing systems; air traffic control systems; and distributed software systems. The “activity” in these systems is governed by operational rules designed by humans; their dynamics are thereforecharacterized by asynchronous occurrences of discrete events. These features lend themselves to the term discrete event system for thiS class of dynamic systems.
Because they incorporate both time- and event-driven dynamics, stochastic hybrid systems (SHS) have become ubiquitous in a variety of fields, from mathematical finance to biological processes to communication networks to engineering. Comprehensively integrating numerous cutting-edge studies, Stochastic Hybrid Systems presents a captivating treatment of some of the most ambitious types of dynamic systems.
The availability of ever increasing amounts of data from multitudes of sources is rapidly transforming the way we approach control and optimization problems. While model-driven methods remain at the heart of how we approach most problems, there is now an increasingly important data-driven component to be incorporated with existing methods, while new ones are continuously […]
The term Cyber-Physical System (CPS) is used to describe dynamic systems which combine components characterized by a physical state (e.g., the location, power level, and temperature of a mobile robot) with components (mostly digital devices empowered by software) characterized by an operational state or mode (e.g., on/off, transmitting/receiving). From a modeling point of view, physical […]
The rapid evolution of computer technology has brought about the proliferation of new dynamic systems, mostly “man-made” and highly complex. Examples abound: computer networks, sensor networks and cyber-physical systems, automated manufacturing systems, traffic control systems, integrated command-control-information systems, etc Historically, scientists and engineers have concentrated on studying and harnessing natural phenomena which are well modeled […]
The multi-agent system framework consists of a team of autonomous agents cooperating to carry out complex tasks within a given environment that is potentially highly dynamic, hazardous, and even adversarial. In general, these tasks entail exploration of the environment to discover or detect various “points of interest.” Once detected, these points of interest become “targets” […]
The Center for Information and Systems Engineering (CISE) partnered with Greg Woolf, CEO of Coalesce.Info and moderator of The Cognitive Computing Group of Boston, to host a community evening focused on Robotics & AI research at Boston University, on February 28, 2017. Click here to read more.
