||Designed for graduate computer science and electrical engineering students. Methodologies and technologies for design of embedded systems. Topics include hardware and software platforms for embedded systems, techniques for modeling and specification of system behavior, software organization, real-time operating system scheduling, real-time communication and packet scheduling, low-power battery and energy-aware system design, timing synchronization, fault tolerance and debugging, and techniques for hardware and software architecture optimization. Theoretical foundations as well as practical design methods.
||Energy-Aware Computing and Cyber-Physical Systems
||System-level management and cross-layer methods for power and energy consumption in computing and communication at various scales ranging across embedded, mobile, personal, enterprise, and data-center scale. Computing, networking, sensing and control technologies and algorithms for improving energy sustainability in human-cyber-physical systems. Topics include: modeling of energy consumption, energy sources, and energy storage; dynamic power management; power-performance scaling and energy proportionality; duty-cycling; power- aware scheduling; low-power protocols; battery modeling and management; thermal management; sensing of power consumption.
||pecial Topics in Circuits and Embedded Systems: Security and Privacy for Embedded Systems, Cyber-Physical Systems, and Internet of Things
||The deep and pervasive embedding of computational intelligence into society has led to the emergence of computing systems that tightly couple software with the physical and human world. Driving exciting applications such as autonomous vehicles, smarthomes, and mobile health, these computing systems are variously referred to as Embedded Systems, Cyber-Physical Systems, Internet-of-Things etc. With their tight and often real-time interaction with physical spaces and human agents, these computing systems which are resource constrained, networked and remote, suffer from a much more expanded set of security and privacy vulnerabilities and consequences than traditional computers. Examples include compromise of system state via adversarial manipulation of physical sensor signals and actuator actions, and unauthorized inferencing of private inference by authorized recipients of from high-dimensional sensor data. The course will examine attacks that such systems are vulnerable to, and emerging solution techniques spanning algorithms, software, and hardware.