With the rapid development of artificial intelligence technology, we have witnessed the widespread application and tremendous success of generative AI, such as ChatGPT. However, in real-world AI applications, such as autonomous driving, autonomous machines, and embodied robots, despite continuous technological breakthroughs, commercialization still faces many challenges. Among them, how to achieve efficient and seamless interaction […]

Time-Sensitive Networking (TSN) is a set of IEEE standards designed to ensure real-time guarantees for data communication over switched Ethernet. The TSN standards offer a wide range of features, including various traffic shaping mechanisms, precise clock synchronization, and network management. A key challenge arising from this wide array of features is determining how to effectively […]

Real-time systems are special embedded systems that must respond to external events within a strict timeframe. They are the backbone of many critical applications, from industrial automation and automotive systems, to avionics and medical devices. In these domains, a delayed response can have serious consequences, ranging from production downtime to life-threatening situations. The most crucial […]

Discussions about the accuracy of Performance Monitoring Counters (PMCs) are common in forums. These hardware-implemented registers track specific events within a processor’s microarchitecture, providing metrics for performance tuning or monitoring unusual activity. However, the accuracy of these counters can be compromised by system noise, other applications, the operating system, and asynchronous hardware events, especially in […]

The idea of creating machines able to reason like humans is not new and has been introduced by Alan Turing in his seminal paper ”Can Machines Think?” which gave raise to the imitation test, together with other work on computability and the premises of artificial intelligence. Today, with the increased prevalence of i) autonomy, and […]

For the last two years, Chuchu Fan and Stanley Bak have served as the SIGBED Blog editors. The blog has continued to publish a stream of content related to technical topics in embedded systems, such as overviews of best papers and recent NSF CAREER awards, as well as posts aimed for a wider audience. One […]

In the domain of cyber-physical systems, linear hybrid automata have emerged as a pivotal tool for modeling and verifying complex behaviors that involve both event-driven (discrete) and time-driven (continuous) changes. This blog post highlights the significant strides made in symbolic analysis techniques, particularly in the efficiency and scalability of these methods. The concept of Hybrid […]

Welcome to the report on the 23rd ACM SIGBED International Conference on Embedded Software (EMSOFT’23)! EMSOFT is held as part of Embedded Systems Week (ESWEEK), the annual highlight event of the embedded systems community. ESWEEK also features the International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES) and the International Conference on Hardware/Software […]

Introduction Cyber-physical systems (CPS), such as automated vehicles or robotics systems, are often characterized by two common features: i) they are safety-critical, hence formal guarantees of correctness are required, ii) they are affected by uncertainty, which is generally modeled through stochastic noise. Various formal verification and synthesis algorithms have been developed for these systems, with […]

In a nutshell: Flick is a novel network primitive that can establish a binary decision over a large wireless network in a fraction of a millisecond, with order-of-magnitude improvement over state of the art. Introduction: Low-power wireless & concurrent transmissions Low-power wireless networks are used in a wide range of applications, from sensing to localization. […]

SIGBED was proud to sponsor the Second Annual CPS Rising Stars Workshop hosted by the University of Virginia on May 31, 2023. Executive Committee member, Wanli Chang, represented SIGBED and delivered a welcome talk. Thirty-four Rising Stars were selected from a competitive applicant pool of 117. The workshop also exceeded its aim to increase representation […]

Deep Neural Networks (DNNs)  are an incredibly powerful tool for tackling a wide-range of real-world problems, including image recognition, autonomous driving, power grid control, fake news detection, drug synthesis and discovery, and even COVID-19 detection and diagnosis. However, similar to any software system, DNNs can have “bugs” that cause unexpected results when presented with inputs […]

For almost as long as people have been designing control systems, they have been asking “how can we prove that our controller will be safe?” For simple systems (e.g. linear or low-dimensional polynomial dynamics), we might be able to hand-analyze the system and prove that it will be safe, but this manual analysis quickly becomes […]

The Evolution of IoT: Diverging Application Requirements The Internet, long the domain of large and/or expensive devices, is now so pervasive that it is possible for tiny devices ranging from fitness trackers to doorbells to be interconnected, forming a bridge between the physical and digital worlds. Unfortunately, general-purpose operating systems, such as Windows and Linux, […]

As of 2023, the progress in deploying robots in the real world is hard to miss: autonomous vehicles actively drive passengers without safety drivers in San Francisco and Phoenix, personal drones for videography can autonomously track human movement despite hard-to-sense obstacles like tree branches, and lightweight robotic manipulators have become more accessible to people with […]

The second Cyber Physical Systems (CPS) Rising Stars Workshop, which is sponsored by the National Science Foundation, will be held at the University of Virginia (Charlottesville, VA) on May 31, 2023. This workshop aims to identify and mentor outstanding PhD students and postdocs who are interested in pursuing academic careers in CPS related areas. It […]

Deep Samal, Dung Tran, and Marilyn Wolf are organizing a new workshop at CPS-IoT Week this year: the International Workshop on Perception for Safety-Critical Cyber-Physical Systems (PerCPS ’23).  This workshop is intended to provide a bridge between machine learning for perception and cyber-physical systems. Perception is a critical capability for autonomous cyber-physical systems.  Cyber-physical automatons […]

Introduction Autonomous systems with learning-enabled components (LECs) rely on deep neural networks in order to achieve high performance for various applications. It is well known that neural networks are vulnerable to distribution shifts (e.g., weather changes and adversarial perturbations). This vulnerability raises the safety and robustness concerns of learning-enabled cyber-physical systems (CPS) in the real […]

We highlight a dangerous pitfall in the state-of-the-art evaluation methodology of deep learning algorithms, as applied in several CPS and IoT application spaces, where collecting data from physical experiments is difficult. The article is inspired by the real experiences of the authors. An extended version appears in the IoT-AE Workshop in conjunction with MILCOM 2022 […]

Machine learning is en vogue, being applied to many classes of problems. One of them is cybersecurity, where ML is used to find vulnerabilities in code, simulate attacks, and detect when an intruder has breached a system’s defenses. Ignoring that intrusion detection is an admission of defeat (it comes into play when your system is […]