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Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”),

In a computational context, self-awareness (SA) is a capability of an autonomous system to describe the acquired experience about itself and its surrounding environment with appropriate models and correlate them incrementally with the currently perceived situation to expand its knowledge continuously. This article introduces a bio-inspired framework for generative and descriptive dynamic models that

In this article, we describe an approach to autonomous system construction that not only supports self-awareness but also formal verification. This is based on modular construction where the key autonomous decision making is captured within a symbolically described “agent.” So, this article leads us from traditional systems architectures, via agent-based computing, to explainability, reconfigurability

Modern distributed systems and Internet-of-Things applications are governed by fast living and changing requirements. Moreover, they have to struggle with huge amounts of data that they create or have to process. To improve the self-awareness of such systems and enable proactive and autonomous decisions, reliable time series forecasting methods are required. However, selecting a suitable forecasting

To promote engineering self-aware and self-adaptive software systems in a reusable manner, architectural patterns and the related methodology provide an unified solution to handle the recurring problems in the engineering process. However, in existing patterns and methods, domain knowledge and engineers’ expertise that is built over time are not explicitly linked to the self-aware processes. This link

The need to adaptively manage computer systems and networks so as to offer good Quality of Service (QoS) and Quality of Experience (QoE) with secure operation at relatively low levels of energy consumption is challenged by their sheer complexity and the wide variability of the workloads. A possible way forward is through self-awareness, whereby self-measurement and self-observation, together with on-line

A multitude of autonomous robotic platforms collectively organized as a swarm attracts increasing attention for remote sensing and exploration tasks. A navigation system is essential for the swarm to collectively localize itself as well as external sources. In this article, we propose a self-aware swarm navigation system that is conscious of the causality between its position and the localization uncertainty

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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Rail traffic systems are widely acknowledged to be an alternative green transportation for goods and people due to their higher mobility, energy efficiency (EE), and/or substantially lower environmental impact than conventional transportation systems. Railway communications have attracted significant attention due to its potential for not only improving operational mobility, safety, and reliability

Railway communications has attracted significant attention from both academia and industries due to the booming development of railways, especially high-speed railways (HSRs). To be in line with the vision of future smart rail communications, the rail transport industry needs to develop innovative communication network architectures and key technologies that ensure high-quality transmissions for both

The accuracies for many pattern recognition tasks have increased rapidly year by year, achieving or even outperforming human performance. From the perspective of accuracy, pattern recognition seems to be a nearly solved problem. However, once launched in real applications, the high-accuracy pattern recognition systems may become unstable and unreliable due to the lack of robustness in open and changing

This is a survey article on the information transmission capability of haptic devices and ways of maximizing it. It is intended for readers who are engineering professionals interested in developing novel haptic interfaces for a variety of applications but are not necessarily trained in haptic science or human user research. We posit that the ultimate goal of any interface is the exchange of information

Indoor areas, such as offices and shopping malls, are a natural environment for initial millimeter-wave (mmWave) deployments. Although we already have the technology that enables us to realize indoor mmWave deployments, there are many remaining challenges associated with system-level design and planning for such. The objective of this article is to bring together multiple strands of research to provide

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For ac electricity grids, the aim has always been at low-cost and disruption-proof solutions. The power grid is inherently vulnerable to environmental disturbances. However, the introduction of power electronics (PEs) and changes in load and generator characteristics have introduced a game changer at an unprecedented pace over the last decade. During this change, load specifications, load characteristics

Being able to manipulate and control light flows at small scales holds the promise to open groundbreaking opportunities for a variety of technologies. Consider, for instance, the challenges currently faced in the world of computing: as data rates and processing demands increase worldwide at an exponential rate, we are facing unsustainable increases in energy consumption associated with data centers

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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Since its inception, the semiconductor industry has used a physical dimension (the minimum gate length of a transistor) as a means to gauge continuous technology advancement. This metric is all but obsolete today. As a replacement, we propose a density metric, which aims to capture how advances in semiconductor device technologies enable system-level benefits. The proposed metric can be used to gauge

Since its inception, the semiconductor industry has used the physical dimension (the gate length) as a means to gauge its continuous advancement. This metric is all but obsolete today. In this month’s opinion piece, the authors examine historical trends and analyze how device technology provides for benefits at the system level, and propose a new density metric. This density metric aims to capture

Domain-specific hardware is becoming a promising topic in the backdrop of improvement slow down for general-purpose processors due to the foreseeable end of Moore’s Law. Machine learning, especially deep neural networks (DNNs), has become the most dazzling domain witnessing successful applications in a wide spectrum of artificial intelligence (AI) tasks. The incomparable accuracy of DNNs is achieved

Providing connectivity to around half of the world population living in rural or underprivileged areas is a tremendous challenge, but, at the same time, a unique opportunity. Access to the Internet would provide the population living in these areas a possibility to progress on the educational, health, environment, and business levels. In this article, a survey of technologies for providing connectivity

Since its first use by Euler on the problem of the seven bridges of Königsberg, graph theory has shown excellent abilities in solving and unveiling the properties of multiple discrete optimization problems. The study of the structure of some integer programs reveals equivalence with graph theory problems making a large body of the literature readily available for solving and characterizing the complexity

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Recent progress in nanofabrication has led to tremendous technological developments for devices that rely on the interaction of light with nanostructured matter. Nanophotonics has hence experienced a large surge of interest in recent years, from basic research to applied technology. For instance, the increased importance of ultralow-energy data processing at fast speeds has been encouraging the use

In this article, we present an industry perspective on key drivers for autonomous navigation, with a particular focus on resiliency and behavior assurance. We provide a brief survey of current deployed mobile autonomous systems and their capabilities (with a primary focus on the air domain but including other domains—underwater, ground, space, and surface—as well). We discuss techniques that are currently

In this article, we explore neurobiological principles that could be deployed in systems requiring self-preservation, adaptive control, and contextual awareness. We start with low-level control for sensor processing and motor reflexes. We then discuss how critical it is at an intermediate level to maintain homeostasis and predict system set points. We end with a discussion at a high level, or cognitive

Neural network (NN) processors are specially designed to handle deep learning tasks by utilizing multilayer artificial NNs. They have been demonstrated to be useful in broad application fields such as image recognition, speech processing, machine translation, and scientific computing. Meanwhile, innovative self-aware techniques, whereby a system can dynamically react based on continuously sensed information

Embodied self-aware computing systems are embedded in a physical environment with a rich set of sensors and actuators to interact both with their environment and with their own embodiment. Through this interaction, they learn about their situation, their own state, and their performance. Although they are application specific like traditional embedded systems (ESs), they are significantly more flexible

Autonomous systems (ASs) operating in real-world environments are exposed to a plurality and diversity of sounds that carry a wealth of information for perception in cognitive dynamic systems. While the importance of the acoustic modality for humans as “ASs” is obvious, it is investigated to what extent current technical ASs operating in scenarios filled with airborne sound exploit their potential

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Computing systems are conventionally designed to operate as accurately as possible. However, this trend faces severe technology challenges, such as power consumption, circuit reliability, and high performance. For nearly half a century, performance and power consumption of computing systems have been consistently improved by relying mostly on technology scaling. As per Dennard’s scaling, the size of

Computing systems have been facing severe technology challenges in recent years with regard to power consumption, circuit reliability, and high performance. For many years, the issues of power consumption and performance have been addressed with the use of technology scaling.However, as Dennard’s scaling tends toward an end, it has become difficult to further improve the performance under the same

With wide deployment of machine learning (ML)-based systems for a variety of applications including medical, military, automotive, genomic, multimedia, and social networking, there is great potential for damage from adversarial learning (AL) attacks. In this article, we provide a contemporary survey of AL, focused particularly on defenses against attacks on deep neural network classifiers. After introducing

The graphical user interface (GUI) has become the prime means for interacting with computing systems. It leverages human perceptual and motor capabilities for elementary tasks such as command exploration and invocation, information search, and multitasking. For designing a GUI, numerous interconnected decisions must be made such that the outcome strikes a balance between human factors and technical

After being rubbed against cotton or wool, amber acquires a static electric charge and attracts lightweight objects such as pieces of dried grass or dried leaves ( Fig. 1 ). Amber has been prized for its beauty since antiquity; it was gathered at the shores of the Baltic Sea as far back as 10 000 BC [1] . The word electric has its origin in $\acute {\eta }\lambda \varepsilon \kappa \tau \rho {o}$ (ilektro)

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